AWS Amazon SageMaker Service Limits
1859 quotas for Amazon SageMaker. 1770 can be increased.
| Quota | Default | Status |
|---|---|---|
Studio CodeEditor Apps running on ml.r6id.large instances Studio CodeEditor Apps running on ml.r6id.large instances capacity | 1 count | Adjustable |
ml.c4.xlarge for spot training job usage ml.c4.xlarge for spot training job usage general | 4 count | Adjustable |
Studio CodeEditor Apps running on ml.r5.4xlarge instances Studio CodeEditor Apps running on ml.r5.4xlarge instances capacity | 0 count | Adjustable |
ml.r5d.xlarge for training job usage ml.r5d.xlarge for training job usage general | 0 count | Adjustable |
ml.g6.16xlarge for endpoint usage ml.g6.16xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m6i.8xlarge for cluster spot instance usage ml.m6i.8xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.i3en.16xlarge for cluster spot instance usage ml.i3en.16xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.c6i.2xlarge for cluster spot instance usage ml.c6i.2xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.r5d.24xlarge for spot training job usage ml.r5d.24xlarge for spot training job usage general | 0 count | Adjustable |
Total number of trials a single trial component can be associated to Total number of trials a single trial component can be associated to general | 500 count | Adjustable |
ml.r7i.16xlarge for cluster usage ml.r7i.16xlarge for cluster usage capacity | 0 count | Adjustable |
ml.c7i.12xlarge for endpoint usage ml.c7i.12xlarge for endpoint usage networking | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.m5d.12xlarge instance Studio KernelGateway Apps running on ml.m5d.12xlarge instance networking | 0 count | Adjustable |
ml.c4.xlarge for training job usage ml.c4.xlarge for training job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m7i.2xlarge instances Studio JupyterLab Apps running on ml.m7i.2xlarge instances capacity | 1 count | Adjustable |
ml.c4.8xlarge for notebook instance usage ml.c4.8xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.trn1n.32xlarge for training job usage ml.trn1n.32xlarge for training job usage general | 0 count | Adjustable |
ml.m5d.xlarge for notebook instance usage ml.m5d.xlarge for notebook instance usage capacity | 1 count | Adjustable |
ml.m6i.24xlarge for cluster spot instance usage ml.m6i.24xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.c4.8xlarge for training warm pool usage ml.c4.8xlarge for training warm pool usage general | 0 count | Adjustable |
ml.m5.2xlarge for spot training job usage ml.m5.2xlarge for spot training job usage general | 4 count | Adjustable |
ml.r7i.large for spot training job usage ml.r7i.large for spot training job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c6i.xlarge instances Studio CodeEditor Apps running on ml.c6i.xlarge instances capacity | 1 count | Adjustable |
ml.g5.4xlarge for spot training job usage ml.g5.4xlarge for spot training job usage general | 0 count | Adjustable |
ml.g4dn.16xlarge for training job usage ml.g4dn.16xlarge for training job usage general | 0 count | Adjustable |
ml.c6i.24xlarge for cluster usage ml.c6i.24xlarge for cluster usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c5.large instances Studio CodeEditor Apps running on ml.c5.large instances capacity | 1 count | Adjustable |
ml.r6id.24xlarge for notebook instance usage ml.r6id.24xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.c5.xlarge instance Studio KernelGateway Apps running on ml.c5.xlarge instance networking | 1 count | Adjustable |
ml.g5.16xlarge for transform job usage ml.g5.16xlarge for transform job usage general | 0 count | Adjustable |
ml.c7i.4xlarge for processing job usage ml.c7i.4xlarge for processing job usage general | 0 count | Adjustable |
ml.c5.2xlarge for training job usage ml.c5.2xlarge for training job usage general | 0 count | Adjustable |
ml.c6i.large for cluster usage ml.c6i.large for cluster usage capacity | 0 count | Adjustable |
ml.g4dn.2xlarge for training warm pool usage ml.g4dn.2xlarge for training warm pool usage general | 0 count | Adjustable |
ml.trn2.48xlarge for endpoint usage ml.trn2.48xlarge for endpoint usage networking | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.g5.16xlarge instances Studio JupyterLab Apps running on ml.g5.16xlarge instances capacity | 0 count | Adjustable |
ml.c6i.4xlarge for notebook instance usage ml.c6i.4xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.c7i.16xlarge for processing job usage ml.c7i.16xlarge for processing job usage general | 0 count | Adjustable |
ml.r5d.24xlarge for training warm pool usage ml.r5d.24xlarge for training warm pool usage general | 0 count | Adjustable |
ml.t3.xlarge for cluster spot instance usage ml.t3.xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.i3en.2xlarge for cluster usage ml.i3en.2xlarge for cluster usage capacity | 0 count | Adjustable |
ml.c6gd.large for endpoint usage ml.c6gd.large for endpoint usage networking | 0 count | Adjustable |
ml.m5.xlarge for training job usage ml.m5.xlarge for training job usage general | 0 count | Adjustable |
Rate of ListEndpoints requests Rate of ListEndpoints requests throughput | 2 count | Fixed |
ml.g4dn.12xlarge for transform job usage ml.g4dn.12xlarge for transform job usage general | 0 count | Adjustable |
ml.p6-b200.48xlarge for training warm pool usage ml.p6-b200.48xlarge for training warm pool usage general | 0 count | Adjustable |
ml.r7gd.large for endpoint usage ml.r7gd.large for endpoint usage networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c5.12xlarge instances Studio CodeEditor Apps running on ml.c5.12xlarge instances capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r6id.16xlarge instances Studio JupyterLab Apps running on ml.r6id.16xlarge instances capacity | 0 count | Adjustable |
Number of instances across all spot training jobs Number of instances across all spot training jobs capacity | 4 count | Adjustable |
ml.r5d.large for training job usage ml.r5d.large for training job usage general | 0 count | Adjustable |
ml.c5n.9xlarge for spot training job usage ml.c5n.9xlarge for spot training job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m6i.2xlarge instances Studio CodeEditor Apps running on ml.m6i.2xlarge instances capacity | 1 count | Adjustable |
ml.c5.9xlarge for cluster spot instance usage ml.c5.9xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.r6id.xlarge for notebook instance usage ml.r6id.xlarge for notebook instance usage capacity | 1 count | Adjustable |
Rate of CreateMlflowApp requests Rate of CreateMlflowApp requests throughput | 1 count | Fixed |
ml.p6-b200.48xlarge for training job usage ml.p6-b200.48xlarge for training job usage general | 0 count | Adjustable |
ml.m6g.8xlarge for endpoint usage ml.m6g.8xlarge for endpoint usage networking | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.p3dn.24xlarge instances Studio JupyterLab Apps running on ml.p3dn.24xlarge instances capacity | 0 count | Adjustable |
Rate of CreateLabelingJob requests Rate of CreateLabelingJob requests throughput | 1 count | Fixed |
ml.g5.2xlarge for training warm pool usage ml.g5.2xlarge for training warm pool usage general | 0 count | Adjustable |
ml.p6-b200.48xlarge for cluster usage ml.p6-b200.48xlarge for cluster usage capacity | 0 count | Adjustable |
Rate of CreateFlowDefinition requests Rate of CreateFlowDefinition requests throughput | 1 count | Fixed |
Total number of trial components allowed from a SageMaker context, excluding those automatically created by SageMaker Total number of trial components allowed from a SageMaker context, excluding those automatically created by SageMaker general | 20,000 count | Adjustable |
ml.g5.16xlarge for spot training job usage ml.g5.16xlarge for spot training job usage general | 0 count | Adjustable |
ml.g7e.48xlarge for training warm pool usage ml.g7e.48xlarge for training warm pool usage general | 0 count | Adjustable |
ml.g6.2xlarge for spot training job usage ml.g6.2xlarge for spot training job usage general | 0 count | Adjustable |
ml.m7i.24xlarge for spot training job usage ml.m7i.24xlarge for spot training job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m6id.large instances Studio CodeEditor Apps running on ml.m6id.large instances capacity | 1 count | Adjustable |
ml.c5.18xlarge for endpoint usage ml.c5.18xlarge for endpoint usage networking | 0 count | Adjustable |
Total EBS volume size in GB across all Studio Spaces Total EBS volume size in GB across all Studio Spaces storage | 500 count | Adjustable |
ml.t2.xlarge for endpoint usage ml.t2.xlarge for endpoint usage networking | 0 count | Adjustable |
Rate of StopNotebookInstance requests Rate of StopNotebookInstance requests throughput | 1 count | Fixed |
ml.c6i.2xlarge for spot training job usage ml.c6i.2xlarge for spot training job usage general | 0 count | Adjustable |
ml.g6e.8xlarge for training warm pool usage ml.g6e.8xlarge for training warm pool usage general | 0 count | Adjustable |
ml.r7i.12xlarge for transform job usage ml.r7i.12xlarge for transform job usage general | 0 count | Adjustable |
ml.t3.xlarge for training warm pool usage ml.t3.xlarge for training warm pool usage general | 0 count | Adjustable |
ml.r6id.2xlarge for notebook instance usage ml.r6id.2xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.r5.24xlarge instance Studio KernelGateway Apps running on ml.r5.24xlarge instance networking | 0 count | Adjustable |
Time at which pipeline executions time out Time at which pipeline executions time out compute | 672 count | Fixed |
ml.c7i.xlarge for spot training job usage ml.c7i.xlarge for spot training job usage general | 0 count | Adjustable |
ml.r6i.4xlarge for cluster usage ml.r6i.4xlarge for cluster usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c6i.12xlarge instances Studio CodeEditor Apps running on ml.c6i.12xlarge instances capacity | 0 count | Adjustable |
ml.r7i.2xlarge for training job usage ml.r7i.2xlarge for training job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r6id.24xlarge instances Studio CodeEditor Apps running on ml.r6id.24xlarge instances capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r6i.large instances Studio JupyterLab Apps running on ml.r6i.large instances capacity | 1 count | Adjustable |
ml.c4.4xlarge for endpoint usage ml.c4.4xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m6i.16xlarge for processing job usage ml.m6i.16xlarge for processing job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r6i.2xlarge instances Studio CodeEditor Apps running on ml.r6i.2xlarge instances capacity | 0 count | Adjustable |
ml.trn1.2xlarge for training warm pool usage ml.trn1.2xlarge for training warm pool usage general | 0 count | Adjustable |
ml.r7i.16xlarge for training job usage ml.r7i.16xlarge for training job usage general | 0 count | Adjustable |
ml.r7gd.4xlarge for endpoint usage ml.r7gd.4xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m7i.xlarge for training job usage ml.m7i.xlarge for training job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.g5.2xlarge instances Studio JupyterLab Apps running on ml.g5.2xlarge instances capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.g4dn.2xlarge instances Studio JupyterLab Apps running on ml.g4dn.2xlarge instances capacity | 0 count | Adjustable |
ml.m4.4xlarge for notebook instance usage ml.m4.4xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r5.8xlarge instances Studio CodeEditor Apps running on ml.r5.8xlarge instances capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c7i.48xlarge instances Studio JupyterLab Apps running on ml.c7i.48xlarge instances capacity | 0 count | Adjustable |
ml.m7i.24xlarge for notebook instance usage ml.m7i.24xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.p4de.24xlarge for spot training job usage ml.p4de.24xlarge for spot training job usage general | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.m5d.4xlarge instance Studio KernelGateway Apps running on ml.m5d.4xlarge instance networking | 1 count | Adjustable |
ml.t3.large for training warm pool usage ml.t3.large for training warm pool usage general | 0 count | Adjustable |
ml.m7i.4xlarge for training job usage ml.m7i.4xlarge for training job usage general | 0 count | Adjustable |
ml.m6i.8xlarge for training warm pool usage ml.m6i.8xlarge for training warm pool usage general | 0 count | Adjustable |
ml.c6i.32xlarge for transform job usage ml.c6i.32xlarge for transform job usage general | 0 count | Adjustable |
ml.c7i.12xlarge for training warm pool usage ml.c7i.12xlarge for training warm pool usage general | 0 count | Adjustable |
ml.c5.4xlarge for notebook instance usage ml.c5.4xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.c6i.32xlarge for training job usage ml.c6i.32xlarge for training job usage general | 0 count | Adjustable |
ml.c4.8xlarge for transform job usage ml.c4.8xlarge for transform job usage general | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.r5.12xlarge instance Studio KernelGateway Apps running on ml.r5.12xlarge instance networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c7i.4xlarge instances Studio CodeEditor Apps running on ml.c7i.4xlarge instances capacity | 0 count | Adjustable |
ml.g4dn.xlarge for transform job usage ml.g4dn.xlarge for transform job usage general | 0 count | Adjustable |
ml.m4.16xlarge for training warm pool usage ml.m4.16xlarge for training warm pool usage general | 0 count | Adjustable |
ml.c7i.large for endpoint usage ml.c7i.large for endpoint usage networking | 0 count | Adjustable |
ml.c7i.2xlarge for endpoint usage ml.c7i.2xlarge for endpoint usage networking | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m5.12xlarge instances Studio JupyterLab Apps running on ml.m5.12xlarge instances capacity | 0 count | Adjustable |
ml.c5.18xlarge for cluster spot instance usage ml.c5.18xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.m5.4xlarge instance Studio KernelGateway Apps running on ml.m5.4xlarge instance networking | 1 count | Adjustable |
ml.r7i.48xlarge for notebook instance usage ml.r7i.48xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.m5.12xlarge for cluster usage ml.m5.12xlarge for cluster usage capacity | 0 count | Adjustable |
ml.m5d.large for endpoint usage ml.m5d.large for endpoint usage networking | 0 count | Adjustable |
ml.g5.24xlarge for cluster spot instance usage ml.g5.24xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.r7i.2xlarge for notebook instance usage ml.r7i.2xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.g5.8xlarge for processing job usage ml.g5.8xlarge for processing job usage general | 0 count | Adjustable |
ml.r5d.16xlarge for cluster usage ml.r5d.16xlarge for cluster usage capacity | 0 count | Adjustable |
ml.g5.24xlarge for processing job usage ml.g5.24xlarge for processing job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.g4dn.8xlarge instances Studio CodeEditor Apps running on ml.g4dn.8xlarge instances capacity | 0 count | Adjustable |
ml.c7i.xlarge for endpoint usage ml.c7i.xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g6.8xlarge for endpoint usage ml.g6.8xlarge for endpoint usage networking | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.g4dn.2xlarge instance Studio KernelGateway Apps running on ml.g4dn.2xlarge instance networking | 0 count | Adjustable |
ml.r5d.8xlarge for processing job usage ml.r5d.8xlarge for processing job usage general | 0 count | Adjustable |
Maximum number of A2I human task UIs Maximum number of A2I human task UIs general | 100 count | Adjustable |
Studio JupyterLab Apps running on ml.p5.48xlarge instances Studio JupyterLab Apps running on ml.p5.48xlarge instances capacity | 0 count | Adjustable |
ml.m7i.48xlarge for cluster spot instance usage ml.m7i.48xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c6id.xlarge instances Studio JupyterLab Apps running on ml.c6id.xlarge instances capacity | 1 count | Adjustable |
RSessionGateway Apps running on ml.t3.xlarge instance RSessionGateway Apps running on ml.t3.xlarge instance networking | 0 count | Adjustable |
ml.r6i.2xlarge for notebook instance usage ml.r6i.2xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.r5.24xlarge for training job usage ml.r5.24xlarge for training job usage general | 0 count | Adjustable |
ml.c6i.32xlarge for processing job usage ml.c6i.32xlarge for processing job usage general | 0 count | Adjustable |
ml.m6i.16xlarge for training warm pool usage ml.m6i.16xlarge for training warm pool usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r6i.xlarge instances Studio CodeEditor Apps running on ml.r6i.xlarge instances capacity | 1 count | Adjustable |
ml.c6gd.4xlarge for endpoint usage ml.c6gd.4xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m6g.12xlarge for endpoint usage ml.m6g.12xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r6i.24xlarge for notebook instance usage ml.r6i.24xlarge for notebook instance usage capacity | 0 count | Adjustable |
Maximum number of SageMaker Model Package allowed per account Maximum number of SageMaker Model Package allowed per account general | 10,000 count | Adjustable |
ml.r7i.4xlarge for cluster usage ml.r7i.4xlarge for cluster usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r7i.xlarge instances Studio JupyterLab Apps running on ml.r7i.xlarge instances capacity | 1 count | Adjustable |
ml.c4.4xlarge for training job usage ml.c4.4xlarge for training job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r6i.4xlarge instances Studio JupyterLab Apps running on ml.r6i.4xlarge instances capacity | 0 count | Adjustable |
ml.trn1.32xlarge for cluster usage ml.trn1.32xlarge for cluster usage capacity | 0 count | Adjustable |
ml.gr6.8xlarge for cluster spot instance usage ml.gr6.8xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Rate of DescribeLabelingJob requests Rate of DescribeLabelingJob requests throughput | 5 count | Fixed |
ml.c6i.24xlarge for cluster spot instance usage ml.c6i.24xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.c5n.4xlarge for cluster spot instance usage ml.c5n.4xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.trn1n.32xlarge for cluster usage ml.trn1n.32xlarge for cluster usage capacity | 0 count | Adjustable |
Maximum number of steps allowed per pipeline Maximum number of steps allowed per pipeline general | 50 count | Fixed |
ml.r6i.24xlarge for cluster spot instance usage ml.r6i.24xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c6id.24xlarge instances Studio CodeEditor Apps running on ml.c6id.24xlarge instances capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m6id.12xlarge instances Studio CodeEditor Apps running on ml.m6id.12xlarge instances capacity | 0 count | Adjustable |
ml.g5.12xlarge for training job usage ml.g5.12xlarge for training job usage general | 0 count | Adjustable |
Rate of StopLabelingJob requests Rate of StopLabelingJob requests throughput | 1 count | Fixed |
ml.m5.large for spot training job usage ml.m5.large for spot training job usage general | 4 count | Adjustable |
ml.r8g.4xlarge for endpoint usage ml.r8g.4xlarge for endpoint usage networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m7i.4xlarge instances Studio CodeEditor Apps running on ml.m7i.4xlarge instances capacity | 0 count | Adjustable |
ml.t2.large for notebook instance usage ml.t2.large for notebook instance usage capacity | 6 count | Adjustable |
ml.c6i.2xlarge for processing job usage ml.c6i.2xlarge for processing job usage general | 0 count | Adjustable |
ml.m4.2xlarge for endpoint usage ml.m4.2xlarge for endpoint usage networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r5.24xlarge instances Studio CodeEditor Apps running on ml.r5.24xlarge instances capacity | 0 count | Adjustable |
ml.g6e.8xlarge for cluster spot instance usage ml.g6e.8xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.m6id.24xlarge for notebook instance usage ml.m6id.24xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c6i.12xlarge instances Studio JupyterLab Apps running on ml.c6i.12xlarge instances capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.t3.2xlarge instances Studio CodeEditor Apps running on ml.t3.2xlarge instances capacity | 6 count | Adjustable |
ml.g6e.xlarge for cluster usage ml.g6e.xlarge for cluster usage capacity | 0 count | Adjustable |
ml.g6e.4xlarge for processing job usage ml.g6e.4xlarge for processing job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r6i.large instances Studio CodeEditor Apps running on ml.r6i.large instances capacity | 1 count | Adjustable |
ml.r7i.large for cluster usage ml.r7i.large for cluster usage capacity | 0 count | Adjustable |
ml.p3dn.24xlarge for training job usage ml.p3dn.24xlarge for training job usage general | 0 count | Adjustable |
ml.g6.xlarge for cluster usage ml.g6.xlarge for cluster usage capacity | 0 count | Adjustable |
ml.g7e.8xlarge for cluster usage ml.g7e.8xlarge for cluster usage capacity | 0 count | Adjustable |
ml.m5d.24xlarge for notebook instance usage ml.m5d.24xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.g5.48xlarge for cluster spot instance usage ml.g5.48xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r6i.8xlarge instances Studio JupyterLab Apps running on ml.r6i.8xlarge instances capacity | 0 count | Adjustable |
ml.r6g.2xlarge for endpoint usage ml.r6g.2xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r6id.12xlarge for notebook instance usage ml.r6id.12xlarge for notebook instance usage capacity | 0 count | Adjustable |
Rate of DescribeModel requests Rate of DescribeModel requests throughput | 5 count | Fixed |
ml.c6i.4xlarge for spot training job usage ml.c6i.4xlarge for spot training job usage general | 0 count | Adjustable |
ml.t3.large for notebook instance usage ml.t3.large for notebook instance usage capacity | 6 count | Adjustable |
Number of ml.p5.4xlarge instances in reserved capacity across training plans per Region Number of ml.p5.4xlarge instances in reserved capacity across training plans per Region capacity | 0 count | Adjustable |
ml.m5.16xlarge for cluster spot instance usage ml.m5.16xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.m7i.12xlarge for notebook instance usage ml.m7i.12xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.c6id.16xlarge for notebook instance usage ml.c6id.16xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.g6e.24xlarge for cluster usage ml.g6e.24xlarge for cluster usage capacity | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.g4dn.4xlarge instance Studio KernelGateway Apps running on ml.g4dn.4xlarge instance networking | 0 count | Adjustable |
ml.g6.2xlarge for training job usage ml.g6.2xlarge for training job usage general | 0 count | Adjustable |
ml.r7i.2xlarge for processing job usage ml.r7i.2xlarge for processing job usage general | 0 count | Adjustable |
ml.c5.2xlarge for notebook instance usage ml.c5.2xlarge for notebook instance usage capacity | 1 count | Adjustable |
ml.c6gd.2xlarge for endpoint usage ml.c6gd.2xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r5d.12xlarge for spot training job usage ml.r5d.12xlarge for spot training job usage general | 0 count | Adjustable |
ml.r6i.xlarge for cluster spot instance usage ml.r6i.xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Rate of DeleteNotebookInstance requests Rate of DeleteNotebookInstance requests throughput | 1 count | Fixed |
ml.g6.12xlarge for cluster spot instance usage ml.g6.12xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.c6i.large for transform job usage ml.c6i.large for transform job usage general | 0 count | Adjustable |
ml.m4.16xlarge for transform job usage ml.m4.16xlarge for transform job usage general | 0 count | Adjustable |
RSessionGateway Apps running on ml.m5.2xlarge instance RSessionGateway Apps running on ml.m5.2xlarge instance networking | 1 count | Adjustable |
ml.c4.2xlarge for endpoint usage ml.c4.2xlarge for endpoint usage networking | 0 count | Adjustable |
Rate of CreateStudioLifecycleConfig requests Rate of CreateStudioLifecycleConfig requests throughput | 1 count | Fixed |
ml.g6.16xlarge for training warm pool usage ml.g6.16xlarge for training warm pool usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r5.16xlarge instances Studio JupyterLab Apps running on ml.r5.16xlarge instances capacity | 0 count | Adjustable |
ml.g6e.xlarge for endpoint usage ml.g6e.xlarge for endpoint usage networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m6i.16xlarge instances Studio CodeEditor Apps running on ml.m6i.16xlarge instances capacity | 0 count | Adjustable |
Number of ml.p6-b200.48xlarge instances in reserved capacity across training plans per Region Number of ml.p6-b200.48xlarge instances in reserved capacity across training plans per Region capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c6i.8xlarge instances Studio JupyterLab Apps running on ml.c6i.8xlarge instances capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.g4dn.12xlarge instances Studio CodeEditor Apps running on ml.g4dn.12xlarge instances capacity | 0 count | Adjustable |
ml.g4dn.16xlarge for endpoint usage ml.g4dn.16xlarge for endpoint usage networking | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.g4dn.4xlarge instances Studio JupyterLab Apps running on ml.g4dn.4xlarge instances capacity | 0 count | Adjustable |
ml.m6i.24xlarge for transform job usage ml.m6i.24xlarge for transform job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.g5.12xlarge instances Studio JupyterLab Apps running on ml.g5.12xlarge instances capacity | 0 count | Adjustable |
ml.g7e.2xlarge for training warm pool usage ml.g7e.2xlarge for training warm pool usage general | 0 count | Adjustable |
Longest run time for a processing job Longest run time for a processing job general | 432,000 Seconds | Adjustable |
Studio CodeEditor Apps running on ml.c6id.2xlarge instances Studio CodeEditor Apps running on ml.c6id.2xlarge instances capacity | 1 count | Adjustable |
ml.c5n.xlarge for training job usage ml.c5n.xlarge for training job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c6id.16xlarge instances Studio JupyterLab Apps running on ml.c6id.16xlarge instances capacity | 0 count | Adjustable |
ml.m5.xlarge for endpoint usage ml.m5.xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g7e.4xlarge for processing job usage ml.g7e.4xlarge for processing job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c6id.large instances Studio CodeEditor Apps running on ml.c6id.large instances capacity | 1 count | Adjustable |
Studio JupyterLab Apps running on ml.m6i.12xlarge instances Studio JupyterLab Apps running on ml.m6i.12xlarge instances capacity | 0 count | Adjustable |
ml.t3.2xlarge for notebook instance usage ml.t3.2xlarge for notebook instance usage capacity | 6 count | Adjustable |
Studio JupyterLab Apps running on ml.m5.4xlarge instances Studio JupyterLab Apps running on ml.m5.4xlarge instances capacity | 0 count | Adjustable |
ml.r5d.16xlarge for training warm pool usage ml.r5d.16xlarge for training warm pool usage general | 0 count | Adjustable |
ml.p5.48xlarge for spot training job usage ml.p5.48xlarge for spot training job usage general | 0 count | Adjustable |
ml.inf2.8xlarge for transform job usage ml.inf2.8xlarge for transform job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m5d.xlarge instances Studio JupyterLab Apps running on ml.m5d.xlarge instances capacity | 1 count | Adjustable |
ml.r5.large for training job usage ml.r5.large for training job usage general | 0 count | Adjustable |
ml.r5d.24xlarge for endpoint usage ml.r5d.24xlarge for endpoint usage networking | 0 count | Adjustable |
RStudioServerPro Apps running on ml.c5.9xlarge instances RStudioServerPro Apps running on ml.c5.9xlarge instances capacity | 0 count | Adjustable |
Rate of UpdateMonitoringAlert requests Rate of UpdateMonitoringAlert requests throughput | 1 count | Fixed |
ml.m7i.16xlarge for training warm pool usage ml.m7i.16xlarge for training warm pool usage general | 0 count | Adjustable |
ml.r6i.4xlarge for cluster spot instance usage ml.r6i.4xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.p5en.48xlarge for endpoint usage ml.p5en.48xlarge for endpoint usage networking | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r6id.12xlarge instances Studio JupyterLab Apps running on ml.r6id.12xlarge instances capacity | 0 count | Adjustable |
ml.r7i.2xlarge for transform job usage ml.r7i.2xlarge for transform job usage general | 0 count | Adjustable |
ml.r7i.8xlarge for notebook instance usage ml.r7i.8xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.p5.48xlarge for notebook instance usage ml.p5.48xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.i3en.xlarge for cluster spot instance usage ml.i3en.xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.g6.24xlarge for cluster spot instance usage ml.g6.24xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Maximum number of hyper parameter tuning jobs that can run at once in parallel Maximum number of hyper parameter tuning jobs that can run at once in parallel general | 100 count | Fixed |
ml.c7i.48xlarge for processing job usage ml.c7i.48xlarge for processing job usage general | 0 count | Adjustable |
ml.t3.2xlarge for processing job usage ml.t3.2xlarge for processing job usage general | 0 count | Adjustable |
ml.m7i.4xlarge for endpoint usage ml.m7i.4xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g5.8xlarge for spot training job usage ml.g5.8xlarge for spot training job usage general | 0 count | Adjustable |
Rate of CreateModel requests Rate of CreateModel requests throughput | 1 count | Fixed |
ml.p4de.24xlarge for cluster spot instance usage ml.p4de.24xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m7i.24xlarge instances Studio JupyterLab Apps running on ml.m7i.24xlarge instances capacity | 0 count | Adjustable |
ml.m7i.48xlarge for training warm pool usage ml.m7i.48xlarge for training warm pool usage general | 0 count | Adjustable |
RSessionGateway Apps running on ml.c5.9xlarge instance RSessionGateway Apps running on ml.c5.9xlarge instance networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r6i.12xlarge instances Studio CodeEditor Apps running on ml.r6i.12xlarge instances capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m5.2xlarge instances Studio CodeEditor Apps running on ml.m5.2xlarge instances capacity | 1 count | Adjustable |
ml.m5.24xlarge for training warm pool usage ml.m5.24xlarge for training warm pool usage general | 0 count | Adjustable |
ml.m6i.4xlarge for notebook instance usage ml.m6i.4xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.c6i.12xlarge for cluster spot instance usage ml.c6i.12xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Rate of ListMonitoringAlerts requests Rate of ListMonitoringAlerts requests throughput | 2 count | Fixed |
ml.c6i.xlarge for cluster usage ml.c6i.xlarge for cluster usage capacity | 0 count | Adjustable |
ml.m5.2xlarge for endpoint usage ml.m5.2xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r5d.xlarge for spot training job usage ml.r5d.xlarge for spot training job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r6id.32xlarge instances Studio CodeEditor Apps running on ml.r6id.32xlarge instances capacity | 0 count | Adjustable |
ml.p3.16xlarge for endpoint usage ml.p3.16xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c7i.8xlarge for processing job usage ml.c7i.8xlarge for processing job usage general | 0 count | Adjustable |
ml.m8g.4xlarge for endpoint usage ml.m8g.4xlarge for endpoint usage networking | 0 count | Adjustable |
RSessionGateway Apps running on ml.c5.12xlarge instance RSessionGateway Apps running on ml.c5.12xlarge instance networking | 0 count | Adjustable |
ml.p6-b200.48xlarge for cluster spot instance usage ml.p6-b200.48xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.c6i.8xlarge for training job usage ml.c6i.8xlarge for training job usage general | 0 count | Adjustable |
ml.r7i.4xlarge for processing job usage ml.r7i.4xlarge for processing job usage general | 0 count | Adjustable |
ml.m5.24xlarge for training job usage ml.m5.24xlarge for training job usage general | 0 count | Adjustable |
ml.r7i.12xlarge for endpoint usage ml.r7i.12xlarge for endpoint usage networking | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.g6e.8xlarge instances Studio JupyterLab Apps running on ml.g6e.8xlarge instances capacity | 0 count | Adjustable |
ml.c6i.24xlarge for training job usage ml.c6i.24xlarge for training job usage general | 0 count | Adjustable |
ml.g7e.48xlarge for spot training job usage ml.g7e.48xlarge for spot training job usage general | 0 count | Adjustable |
ml.c6i.24xlarge for training warm pool usage ml.c6i.24xlarge for training warm pool usage general | 0 count | Adjustable |
ml.r7i.2xlarge for training warm pool usage ml.r7i.2xlarge for training warm pool usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.g5.48xlarge instances Studio CodeEditor Apps running on ml.g5.48xlarge instances capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.g4dn.16xlarge instances Studio CodeEditor Apps running on ml.g4dn.16xlarge instances capacity | 0 count | Adjustable |
ml.g5.16xlarge for cluster usage ml.g5.16xlarge for cluster usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.g6e.xlarge instances Studio CodeEditor Apps running on ml.g6e.xlarge instances capacity | 0 count | Adjustable |
Number of workteams Number of workteams general | 25 count | Adjustable |
ml.trn1.2xlarge for endpoint usage ml.trn1.2xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c6i.4xlarge for transform job usage ml.c6i.4xlarge for transform job usage general | 0 count | Adjustable |
ml.m7i.2xlarge for cluster spot instance usage ml.m7i.2xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.g5.48xlarge for endpoint usage ml.g5.48xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r6i.16xlarge for cluster usage ml.r6i.16xlarge for cluster usage capacity | 0 count | Adjustable |
RSessionGateway Apps running on ml.c5.2xlarge instance RSessionGateway Apps running on ml.c5.2xlarge instance networking | 1 count | Adjustable |
ml.i3en.12xlarge for cluster usage ml.i3en.12xlarge for cluster usage capacity | 0 count | Adjustable |
ml.i3en.24xlarge for cluster usage ml.i3en.24xlarge for cluster usage capacity | 0 count | Adjustable |
ml.r7i.12xlarge for training job usage ml.r7i.12xlarge for training job usage general | 0 count | Adjustable |
ml.t3.xlarge for notebook instance usage ml.t3.xlarge for notebook instance usage capacity | 6 count | Adjustable |
RSessionGateway Apps running on ml.m5d.24xlarge instance RSessionGateway Apps running on ml.m5d.24xlarge instance networking | 0 count | Adjustable |
ml.m6i.8xlarge for cluster usage ml.m6i.8xlarge for cluster usage capacity | 0 count | Adjustable |
ml.c7i.12xlarge for training job usage ml.c7i.12xlarge for training job usage general | 0 count | Adjustable |
ml.c7i.8xlarge for endpoint usage ml.c7i.8xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g6.48xlarge for training job usage ml.g6.48xlarge for training job usage general | 0 count | Adjustable |
ml.m5.8xlarge for cluster usage ml.m5.8xlarge for cluster usage capacity | 0 count | Adjustable |
ml.m6i.32xlarge for cluster usage ml.m6i.32xlarge for cluster usage capacity | 0 count | Adjustable |
ml.inf2.48xlarge for notebook instance usage ml.inf2.48xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.m7i.8xlarge for endpoint usage ml.m7i.8xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c4.xlarge for notebook instance usage ml.c4.xlarge for notebook instance usage capacity | 2 count | Adjustable |
ml.m5.4xlarge for notebook instance usage ml.m5.4xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.m5d.8xlarge instance Studio KernelGateway Apps running on ml.m5d.8xlarge instance networking | 0 count | Adjustable |
ml.r5.12xlarge for notebook instance usage ml.r5.12xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.m7i.large for cluster spot instance usage ml.m7i.large for cluster spot instance usage capacity | 0 count | Adjustable |
Maximum number of training jobs that each hyperparameter tuning job with Random search strategy can create Maximum number of training jobs that each hyperparameter tuning job with Random search strategy can create throughput | 500 count | Adjustable |
ml.c6gn.2xlarge for endpoint usage ml.c6gn.2xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m4.xlarge for transform job usage ml.m4.xlarge for transform job usage general | 0 count | Adjustable |
RSessionGateway Apps running on ml.p4d.24xlarge instance RSessionGateway Apps running on ml.p4d.24xlarge instance networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m5d.8xlarge instances Studio CodeEditor Apps running on ml.m5d.8xlarge instances capacity | 0 count | Adjustable |
ml.m5.16xlarge for cluster usage ml.m5.16xlarge for cluster usage capacity | 0 count | Adjustable |
ml.c5.4xlarge for training warm pool usage ml.c5.4xlarge for training warm pool usage general | 0 count | Adjustable |
ml.c5n.2xlarge for training job usage ml.c5n.2xlarge for training job usage general | 0 count | Adjustable |
ml.c4.2xlarge for transform job usage ml.c4.2xlarge for transform job usage general | 0 count | Adjustable |
ml.r7i.large for training warm pool usage ml.r7i.large for training warm pool usage general | 0 count | Adjustable |
ml.m7i.2xlarge for training job usage ml.m7i.2xlarge for training job usage general | 0 count | Adjustable |
ml.g5.24xlarge for training warm pool usage ml.g5.24xlarge for training warm pool usage general | 0 count | Adjustable |
ml.m7i.12xlarge for transform job usage ml.m7i.12xlarge for transform job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c6i.2xlarge instances Studio JupyterLab Apps running on ml.c6i.2xlarge instances capacity | 1 count | Adjustable |
ml.trn2.48xlarge for cluster spot instance usage ml.trn2.48xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c7i.xlarge instances Studio JupyterLab Apps running on ml.c7i.xlarge instances capacity | 1 count | Adjustable |
ml.g6.24xlarge for spot training job usage ml.g6.24xlarge for spot training job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m5.12xlarge instances Studio CodeEditor Apps running on ml.m5.12xlarge instances capacity | 0 count | Adjustable |
ml.m7i.48xlarge for processing job usage ml.m7i.48xlarge for processing job usage general | 0 count | Adjustable |
Number of ml.trn1.32xlarge instances in reserved capacity across training plans per Region Number of ml.trn1.32xlarge instances in reserved capacity across training plans per Region capacity | 0 count | Adjustable |
ml.t3.large for spot training job usage ml.t3.large for spot training job usage general | 0 count | Adjustable |
Maximum number of instances per spot training job Maximum number of instances per spot training job capacity | 20 count | Adjustable |
Studio CodeEditor Apps running on ml.g6e.4xlarge instances Studio CodeEditor Apps running on ml.g6e.4xlarge instances capacity | 0 count | Adjustable |
ml.m6gd.xlarge for endpoint usage ml.m6gd.xlarge for endpoint usage networking | 0 count | Adjustable |
Rate of CreateTransformJob requests Rate of CreateTransformJob requests throughput | 1 count | Fixed |
ml.eia1.medium for endpoint usage ml.eia1.medium for endpoint usage networking | 0 count | Adjustable |
ml.c6i.12xlarge for training job usage ml.c6i.12xlarge for training job usage general | 0 count | Adjustable |
ml.r7i.8xlarge for cluster spot instance usage ml.r7i.8xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.r7i.48xlarge for training warm pool usage ml.r7i.48xlarge for training warm pool usage general | 0 count | Adjustable |
ml.m4.4xlarge for training warm pool usage ml.m4.4xlarge for training warm pool usage general | 0 count | Adjustable |
ml.c4.8xlarge for endpoint usage ml.c4.8xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g6.xlarge for notebook instance usage ml.g6.xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.m5.16xlarge instance Studio KernelGateway Apps running on ml.m5.16xlarge instance networking | 0 count | Adjustable |
ml.g5.4xlarge for transform job usage ml.g5.4xlarge for transform job usage general | 0 count | Adjustable |
ml.m6i.xlarge for spot training job usage ml.m6i.xlarge for spot training job usage general | 0 count | Adjustable |
RSessionGateway Apps running on ml.m5.12xlarge instance RSessionGateway Apps running on ml.m5.12xlarge instance networking | 0 count | Adjustable |
ml.r5.2xlarge for endpoint usage ml.r5.2xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m5.4xlarge for transform job usage ml.m5.4xlarge for transform job usage general | 0 count | Adjustable |
ml.m6i.4xlarge for processing job usage ml.m6i.4xlarge for processing job usage general | 0 count | Adjustable |
ml.c8g.4xlarge for endpoint usage ml.c8g.4xlarge for endpoint usage networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c5.xlarge instances Studio CodeEditor Apps running on ml.c5.xlarge instances capacity | 1 count | Adjustable |
Rate of CreateEndpointConfig requests Rate of CreateEndpointConfig requests throughput | 1 count | Fixed |
ml.c7i.48xlarge for endpoint usage ml.c7i.48xlarge for endpoint usage networking | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m6i.32xlarge instances Studio JupyterLab Apps running on ml.m6i.32xlarge instances capacity | 0 count | Adjustable |
ml.p5.48xlarge for cluster usage ml.p5.48xlarge for cluster usage capacity | 0 count | Adjustable |
ml.c5d.18xlarge for notebook instance usage ml.c5d.18xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.g6e.2xlarge for training warm pool usage ml.g6e.2xlarge for training warm pool usage general | 0 count | Adjustable |
ml.m4.4xlarge for training job usage ml.m4.4xlarge for training job usage general | 0 count | Adjustable |
ml.g4dn.12xlarge for endpoint usage ml.g4dn.12xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g6e.12xlarge for spot training job usage ml.g6e.12xlarge for spot training job usage general | 0 count | Adjustable |
ml.m6i.12xlarge for cluster spot instance usage ml.m6i.12xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.c7g.8xlarge for endpoint usage ml.c7g.8xlarge for endpoint usage networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.g6.24xlarge instances Studio CodeEditor Apps running on ml.g6.24xlarge instances capacity | 0 count | Adjustable |
RSessionGateway Apps running on ml.p3.2xlarge instance RSessionGateway Apps running on ml.p3.2xlarge instance networking | 0 count | Adjustable |
ml.g6.24xlarge for processing job usage ml.g6.24xlarge for processing job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r7i.16xlarge instances Studio JupyterLab Apps running on ml.r7i.16xlarge instances capacity | 0 count | Adjustable |
ml.r5.12xlarge for training job usage ml.r5.12xlarge for training job usage general | 0 count | Adjustable |
Maximum number of parallel compilation jobs Maximum number of parallel compilation jobs general | 2 count | Adjustable |
Studio CodeEditor Apps running on ml.g6.16xlarge instances Studio CodeEditor Apps running on ml.g6.16xlarge instances capacity | 0 count | Adjustable |
ml.c6i.12xlarge for spot training job usage ml.c6i.12xlarge for spot training job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.g4dn.8xlarge instances Studio JupyterLab Apps running on ml.g4dn.8xlarge instances capacity | 0 count | Adjustable |
ml.m6i.large for training warm pool usage ml.m6i.large for training warm pool usage general | 0 count | Adjustable |
ml.r5.16xlarge for training warm pool usage ml.r5.16xlarge for training warm pool usage general | 0 count | Adjustable |
ml.r7i.xlarge for processing job usage ml.r7i.xlarge for processing job usage general | 0 count | Adjustable |
ml.gr6.8xlarge for cluster usage ml.gr6.8xlarge for cluster usage capacity | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.g4dn.16xlarge instance Studio KernelGateway Apps running on ml.g4dn.16xlarge instance networking | 0 count | Adjustable |
ml.m5.large for training warm pool usage ml.m5.large for training warm pool usage general | 0 count | Adjustable |
Large-sized MLflow Tracking Server usage Large-sized MLflow Tracking Server usage storage | 1 count | Adjustable |
ml.c5.4xlarge for processing job usage ml.c5.4xlarge for processing job usage general | 0 count | Adjustable |
ml.c4.8xlarge for spot training job usage ml.c4.8xlarge for spot training job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m6i.xlarge instances Studio CodeEditor Apps running on ml.m6i.xlarge instances capacity | 1 count | Adjustable |
ml.c6i.8xlarge for training warm pool usage ml.c6i.8xlarge for training warm pool usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m6id.2xlarge instances Studio CodeEditor Apps running on ml.m6id.2xlarge instances capacity | 1 count | Adjustable |
ml.g7e.8xlarge for spot training job usage ml.g7e.8xlarge for spot training job usage general | 0 count | Adjustable |
ml.g6e.8xlarge for cluster usage ml.g6e.8xlarge for cluster usage capacity | 0 count | Adjustable |
ml.t3.medium for notebook instance usage ml.t3.medium for notebook instance usage capacity | 6 count | Adjustable |
ml.m4.xlarge for notebook instance usage ml.m4.xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.p3.8xlarge instances Studio CodeEditor Apps running on ml.p3.8xlarge instances capacity | 0 count | Adjustable |
ml.m6i.32xlarge for processing job usage ml.m6i.32xlarge for processing job usage general | 0 count | Adjustable |
ml.r6i.8xlarge for cluster spot instance usage ml.r6i.8xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.c6i.xlarge for cluster spot instance usage ml.c6i.xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Maximum number of SageMakerImage images allowed per account Maximum number of SageMakerImage images allowed per account general | 250 count | Adjustable |
ml.r7i.12xlarge for spot training job usage ml.r7i.12xlarge for spot training job usage general | 0 count | Adjustable |
ml.c8g.24xlarge for endpoint usage ml.c8g.24xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m6i.12xlarge for notebook instance usage ml.m6i.12xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.g5.xlarge for cluster spot instance usage ml.g5.xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.r6i.12xlarge for notebook instance usage ml.r6i.12xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.g5.xlarge for processing job usage ml.g5.xlarge for processing job usage general | 0 count | Adjustable |
ml.g6e.12xlarge for cluster usage ml.g6e.12xlarge for cluster usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c7i.12xlarge instances Studio CodeEditor Apps running on ml.c7i.12xlarge instances capacity | 0 count | Adjustable |
ml.m6i.4xlarge for training warm pool usage ml.m6i.4xlarge for training warm pool usage general | 0 count | Adjustable |
Canvas Apps running on system instances Canvas Apps running on system instances capacity | 10 count | Adjustable |
Studio CodeEditor Apps running on ml.t3.large instances Studio CodeEditor Apps running on ml.t3.large instances capacity | 6 count | Adjustable |
ml.m5.xlarge for transform job usage ml.m5.xlarge for transform job usage general | 0 count | Adjustable |
ml.p4de.24xlarge for endpoint usage ml.p4de.24xlarge for endpoint usage networking | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r6id.32xlarge instances Studio JupyterLab Apps running on ml.r6id.32xlarge instances capacity | 0 count | Adjustable |
ml.c8g.xlarge for endpoint usage ml.c8g.xlarge for endpoint usage networking | 0 count | Adjustable |
ml.inf1.6xlarge for notebook instance usage ml.inf1.6xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.c7i.4xlarge for transform job usage ml.c7i.4xlarge for transform job usage general | 0 count | Adjustable |
ml.i3en.2xlarge for cluster spot instance usage ml.i3en.2xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.r5.12xlarge for endpoint usage ml.r5.12xlarge for endpoint usage networking | 0 count | Adjustable |
Maximum number of instances per endpoint Maximum number of instances per endpoint networking | 4 count | Adjustable |
ml.g6e.12xlarge for training job usage ml.g6e.12xlarge for training job usage general | 0 count | Adjustable |
ml.c8g.large for endpoint usage ml.c8g.large for endpoint usage networking | 0 count | Adjustable |
ml.p5en.48xlarge for spot training job usage ml.p5en.48xlarge for spot training job usage general | 0 count | Adjustable |
ml.g7e.24xlarge for training warm pool usage ml.g7e.24xlarge for training warm pool usage general | 0 count | Adjustable |
ml.g6.4xlarge for training job usage ml.g6.4xlarge for training job usage general | 0 count | Adjustable |
ml.p4de.24xlarge for training warm pool usage ml.p4de.24xlarge for training warm pool usage general | 0 count | Adjustable |
ml.c5.9xlarge for spot training job usage ml.c5.9xlarge for spot training job usage general | 0 count | Adjustable |
ml.r7i.8xlarge for transform job usage ml.r7i.8xlarge for transform job usage general | 0 count | Adjustable |
RSessionGateway Apps running on ml.r5.4xlarge instance RSessionGateway Apps running on ml.r5.4xlarge instance networking | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m6i.4xlarge instances Studio JupyterLab Apps running on ml.m6i.4xlarge instances capacity | 0 count | Adjustable |
The maximum number of MLflow Apps that can be created. The maximum number of MLflow Apps that can be created. general | 3 count | Adjustable |
ml.p5.48xlarge for training job usage ml.p5.48xlarge for training job usage general | 0 count | Adjustable |
ml.m5.2xlarge for notebook instance usage ml.m5.2xlarge for notebook instance usage capacity | 1 count | Adjustable |
ml.g6e.48xlarge for cluster usage ml.g6e.48xlarge for cluster usage capacity | 0 count | Adjustable |
RSessionGateway Apps running on ml.r5.24xlarge instance RSessionGateway Apps running on ml.r5.24xlarge instance networking | 0 count | Adjustable |
ml.c5.xlarge for spot training job usage ml.c5.xlarge for spot training job usage general | 4 count | Adjustable |
ml.c6gd.16xlarge for endpoint usage ml.c6gd.16xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m4.xlarge for spot training job usage ml.m4.xlarge for spot training job usage general | 4 count | Adjustable |
Studio JupyterLab Apps running on ml.c6id.8xlarge instances Studio JupyterLab Apps running on ml.c6id.8xlarge instances capacity | 0 count | Adjustable |
Rate of DeleteWorkteam requests Rate of DeleteWorkteam requests throughput | 1 count | Fixed |
ml.m7i.12xlarge for training job usage ml.m7i.12xlarge for training job usage general | 0 count | Adjustable |
Maximum number of pipelines allowed per account Maximum number of pipelines allowed per account general | 500 count | Adjustable |
Studio JupyterLab Apps running on ml.m6i.24xlarge instances Studio JupyterLab Apps running on ml.m6i.24xlarge instances capacity | 0 count | Adjustable |
RSessionGateway Apps running on ml.c5.xlarge instance RSessionGateway Apps running on ml.c5.xlarge instance networking | 1 count | Adjustable |
ml.t3.large for cluster usage ml.t3.large for cluster usage capacity | 0 count | Adjustable |
RSessionGateway Apps running on ml.r5.large instance RSessionGateway Apps running on ml.r5.large instance networking | 1 count | Adjustable |
ml.g5.12xlarge for notebook instance usage ml.g5.12xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.p5en.48xlarge instances Studio JupyterLab Apps running on ml.p5en.48xlarge instances capacity | 0 count | Adjustable |
ml.c7i.4xlarge for spot training job usage ml.c7i.4xlarge for spot training job usage general | 0 count | Adjustable |
Rate of DescribeSubscribedWorkteam requests Rate of DescribeSubscribedWorkteam requests throughput | 1 count | Fixed |
ml.c7i.48xlarge for spot training job usage ml.c7i.48xlarge for spot training job usage general | 0 count | Adjustable |
RSessionGateway Apps running on ml.r5.16xlarge instance RSessionGateway Apps running on ml.r5.16xlarge instance networking | 0 count | Adjustable |
Maximum number of Ground Truth Streaming labeling jobs Maximum number of Ground Truth Streaming labeling jobs general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r7i.8xlarge instances Studio JupyterLab Apps running on ml.r7i.8xlarge instances capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.t3.xlarge instances Studio JupyterLab Apps running on ml.t3.xlarge instances capacity | 6 count | Adjustable |
ml.g6.2xlarge for cluster usage ml.g6.2xlarge for cluster usage capacity | 0 count | Adjustable |
ml.r7i.large for training job usage ml.r7i.large for training job usage general | 0 count | Adjustable |
ml.g5.8xlarge for cluster usage ml.g5.8xlarge for cluster usage capacity | 0 count | Adjustable |
Maximum number Spot instances allowed per SageMaker HyperPod cluster Maximum number Spot instances allowed per SageMaker HyperPod cluster capacity | 20 count | Adjustable |
ml.c6i.12xlarge for cluster usage ml.c6i.12xlarge for cluster usage capacity | 0 count | Adjustable |
ml.m6i.xlarge for cluster spot instance usage ml.m6i.xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.m7i.12xlarge for endpoint usage ml.m7i.12xlarge for endpoint usage networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r6i.8xlarge instances Studio CodeEditor Apps running on ml.r6i.8xlarge instances capacity | 0 count | Adjustable |
ml.m5.8xlarge for cluster spot instance usage ml.m5.8xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.m7i.2xlarge for transform job usage ml.m7i.2xlarge for transform job usage general | 0 count | Adjustable |
ml.c5n.9xlarge for training job usage ml.c5n.9xlarge for training job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.g6.4xlarge instances Studio JupyterLab Apps running on ml.g6.4xlarge instances capacity | 0 count | Adjustable |
ml.g4dn.4xlarge for training job usage ml.g4dn.4xlarge for training job usage general | 0 count | Adjustable |
ml.c7i.8xlarge for training warm pool usage ml.c7i.8xlarge for training warm pool usage general | 0 count | Adjustable |
ml.c6g.2xlarge for endpoint usage ml.c6g.2xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r7i.4xlarge for cluster spot instance usage ml.r7i.4xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m6id.large instances Studio JupyterLab Apps running on ml.m6id.large instances capacity | 1 count | Adjustable |
ml.inf2.8xlarge for notebook instance usage ml.inf2.8xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.c5.4xlarge instance Studio KernelGateway Apps running on ml.c5.4xlarge instance networking | 0 count | Adjustable |
Maximum number instances allowed per SageMaker HyperPod cluster Maximum number instances allowed per SageMaker HyperPod cluster capacity | 20 count | Adjustable |
ml.g4dn.xlarge for spot training job usage ml.g4dn.xlarge for spot training job usage general | 0 count | Adjustable |
ml.m6gd.16xlarge for endpoint usage ml.m6gd.16xlarge for endpoint usage networking | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.m5d.16xlarge instance Studio KernelGateway Apps running on ml.m5d.16xlarge instance networking | 0 count | Adjustable |
ml.g4dn.8xlarge for notebook instance usage ml.g4dn.8xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.c6i.16xlarge for processing job usage ml.c6i.16xlarge for processing job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c7i.16xlarge instances Studio CodeEditor Apps running on ml.c7i.16xlarge instances capacity | 0 count | Adjustable |
ml.c7i.8xlarge for spot training job usage ml.c7i.8xlarge for spot training job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m6id.16xlarge instances Studio JupyterLab Apps running on ml.m6id.16xlarge instances capacity | 0 count | Adjustable |
ml.c7i.24xlarge for training warm pool usage ml.c7i.24xlarge for training warm pool usage general | 0 count | Adjustable |
ml.g4dn.8xlarge for processing job usage ml.g4dn.8xlarge for processing job usage general | 0 count | Adjustable |
Rate of ListWorkteams requests Rate of ListWorkteams requests throughput | 2 count | Fixed |
ml.g7e.4xlarge for spot training job usage ml.g7e.4xlarge for spot training job usage general | 0 count | Adjustable |
Maximum number of parallel AI benchmark jobs Maximum number of parallel AI benchmark jobs general | 2 count | Adjustable |
ml.c4.large for endpoint usage ml.c4.large for endpoint usage networking | 0 count | Adjustable |
ml.c5.2xlarge for cluster usage ml.c5.2xlarge for cluster usage capacity | 0 count | Adjustable |
ml.c7i.24xlarge for transform job usage ml.c7i.24xlarge for transform job usage general | 0 count | Adjustable |
ml.trn1n.32xlarge for endpoint usage ml.trn1n.32xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g7e.48xlarge for training job usage ml.g7e.48xlarge for training job usage general | 0 count | Adjustable |
ml.m4.4xlarge for transform job usage ml.m4.4xlarge for transform job usage general | 0 count | Adjustable |
ml.m6i.2xlarge for cluster spot instance usage ml.m6i.2xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.r5d.8xlarge for spot training job usage ml.r5d.8xlarge for spot training job usage general | 0 count | Adjustable |
ml.g5.12xlarge for cluster spot instance usage ml.g5.12xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.m7i.16xlarge for cluster usage ml.m7i.16xlarge for cluster usage capacity | 0 count | Adjustable |
ml.c5n.2xlarge for cluster usage ml.c5n.2xlarge for cluster usage capacity | 0 count | Adjustable |
ml.g4dn.4xlarge for transform job usage ml.g4dn.4xlarge for transform job usage general | 0 count | Adjustable |
RSessionGateway Apps running on ml.p3dn.24xlarge instance RSessionGateway Apps running on ml.p3dn.24xlarge instance networking | 0 count | Adjustable |
ml.inf2.48xlarge for transform job usage ml.inf2.48xlarge for transform job usage general | 0 count | Adjustable |
Rate of DeleteFlowDefinition requests Rate of DeleteFlowDefinition requests throughput | 1 count | Fixed |
ml.r6gd.large for endpoint usage ml.r6gd.large for endpoint usage networking | 0 count | Adjustable |
ml.m6i.16xlarge for training job usage ml.m6i.16xlarge for training job usage general | 0 count | Adjustable |
Maximum number of SageMaker Model Package Groups allowed per account Maximum number of SageMaker Model Package Groups allowed per account general | 250 count | Adjustable |
Studio JupyterLab Apps running on ml.p3.8xlarge instances Studio JupyterLab Apps running on ml.p3.8xlarge instances capacity | 0 count | Adjustable |
ml.g6.12xlarge for notebook instance usage ml.g6.12xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.g6.48xlarge for cluster spot instance usage ml.g6.48xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.r6gd.12xlarge for endpoint usage ml.r6gd.12xlarge for endpoint usage networking | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m5d.8xlarge instances Studio JupyterLab Apps running on ml.m5d.8xlarge instances capacity | 0 count | Adjustable |
ml.g5.xlarge for spot training job usage ml.g5.xlarge for spot training job usage general | 0 count | Adjustable |
ml.r6i.8xlarge for notebook instance usage ml.r6i.8xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.m5.4xlarge for spot training job usage ml.m5.4xlarge for spot training job usage general | 2 count | Adjustable |
RSessionGateway Apps running on ml.p3.8xlarge instance RSessionGateway Apps running on ml.p3.8xlarge instance networking | 0 count | Adjustable |
ml.g5.12xlarge for spot training job usage ml.g5.12xlarge for spot training job usage general | 0 count | Adjustable |
ml.c5.2xlarge for endpoint usage ml.c5.2xlarge for endpoint usage networking | 0 count | Adjustable |
Rate of DeleteModel requests Rate of DeleteModel requests throughput | 1 count | Fixed |
Rate of DescribeTransformJob requests Rate of DescribeTransformJob requests throughput | 5 count | Fixed |
Studio CodeEditor Apps running on ml.p3.16xlarge instances Studio CodeEditor Apps running on ml.p3.16xlarge instances capacity | 0 count | Adjustable |
ml.r6g.xlarge for endpoint usage ml.r6g.xlarge for endpoint usage networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c6id.12xlarge instances Studio CodeEditor Apps running on ml.c6id.12xlarge instances capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.g6.12xlarge instances Studio JupyterLab Apps running on ml.g6.12xlarge instances capacity | 0 count | Adjustable |
ml.c6i.12xlarge for training warm pool usage ml.c6i.12xlarge for training warm pool usage general | 0 count | Adjustable |
ml.r6id.32xlarge for notebook instance usage ml.r6id.32xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.p3dn.24xlarge for notebook instance usage ml.p3dn.24xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.g6.12xlarge for processing job usage ml.g6.12xlarge for processing job usage general | 0 count | Adjustable |
ml.r5.2xlarge for notebook instance usage ml.r5.2xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.c5.18xlarge instance Studio KernelGateway Apps running on ml.c5.18xlarge instance networking | 0 count | Adjustable |
ml.r8g.8xlarge for endpoint usage ml.r8g.8xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g6e.16xlarge for training warm pool usage ml.g6e.16xlarge for training warm pool usage general | 0 count | Adjustable |
ml.g6e.24xlarge for spot training job usage ml.g6e.24xlarge for spot training job usage general | 0 count | Adjustable |
ml.g6.16xlarge for cluster usage ml.g6.16xlarge for cluster usage capacity | 0 count | Adjustable |
ml.m5.24xlarge for cluster usage ml.m5.24xlarge for cluster usage capacity | 0 count | Adjustable |
ml.g5.xlarge for endpoint usage ml.g5.xlarge for endpoint usage networking | 0 count | Adjustable |
Maximum number of concurrent pipeline executions allowed per account Maximum number of concurrent pipeline executions allowed per account compute | 20 count | Adjustable |
ml.g6e.xlarge for cluster spot instance usage ml.g6e.xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.r6g.large for endpoint usage ml.r6g.large for endpoint usage networking | 0 count | Adjustable |
ml.g4dn.4xlarge for spot training job usage ml.g4dn.4xlarge for spot training job usage general | 0 count | Adjustable |
ml.g4dn.12xlarge for notebook instance usage ml.g4dn.12xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.t3.2xlarge instances Studio JupyterLab Apps running on ml.t3.2xlarge instances capacity | 6 count | Adjustable |
ml.c7i.4xlarge for training job usage ml.c7i.4xlarge for training job usage general | 0 count | Adjustable |
ml.g5.2xlarge for notebook instance usage ml.g5.2xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.g7e.2xlarge for training job usage ml.g7e.2xlarge for training job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.g6.24xlarge instances Studio JupyterLab Apps running on ml.g6.24xlarge instances capacity | 0 count | Adjustable |
ml.g6e.12xlarge for training warm pool usage ml.g6e.12xlarge for training warm pool usage general | 0 count | Adjustable |
ml.r8g.24xlarge for endpoint usage ml.r8g.24xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m6i.xlarge for transform job usage ml.m6i.xlarge for transform job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r7i.12xlarge instances Studio CodeEditor Apps running on ml.r7i.12xlarge instances capacity | 0 count | Adjustable |
ml.g5.2xlarge for training job usage ml.g5.2xlarge for training job usage general | 0 count | Adjustable |
Rate of StopTransformJob requests Rate of StopTransformJob requests throughput | 1 count | Fixed |
ml.g4dn.2xlarge for processing job usage ml.g4dn.2xlarge for processing job usage general | 0 count | Adjustable |
ml.c6gn.4xlarge for endpoint usage ml.c6gn.4xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m6i.2xlarge for training warm pool usage ml.m6i.2xlarge for training warm pool usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m6i.12xlarge instances Studio CodeEditor Apps running on ml.m6i.12xlarge instances capacity | 0 count | Adjustable |
ml.r5.2xlarge for processing job usage ml.r5.2xlarge for processing job usage general | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.g5.48xlarge instance Studio KernelGateway Apps running on ml.g5.48xlarge instance networking | 0 count | Adjustable |
ml.g6.8xlarge for processing job usage ml.g6.8xlarge for processing job usage general | 0 count | Adjustable |
ml.m5.12xlarge for transform job usage ml.m5.12xlarge for transform job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r5.xlarge instances Studio JupyterLab Apps running on ml.r5.xlarge instances capacity | 1 count | Adjustable |
ml.p6e-gb200.36xlarge for training job usage ml.p6e-gb200.36xlarge for training job usage general | 0 count | Adjustable |
ml.p4d.24xlarge for training job usage ml.p4d.24xlarge for training job usage general | 0 count | Adjustable |
ml.r8g.12xlarge for endpoint usage ml.r8g.12xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g7e.2xlarge for processing job usage ml.g7e.2xlarge for processing job usage general | 0 count | Adjustable |
ml.m6i.xlarge for training job usage ml.m6i.xlarge for training job usage general | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.p3.8xlarge instance Studio KernelGateway Apps running on ml.p3.8xlarge instance networking | 0 count | Adjustable |
ml.r6id.large for notebook instance usage ml.r6id.large for notebook instance usage capacity | 1 count | Adjustable |
RSessionGateway Apps running on ml.g4dn.2xlarge instance RSessionGateway Apps running on ml.g4dn.2xlarge instance networking | 0 count | Adjustable |
ml.g7e.12xlarge for training job usage ml.g7e.12xlarge for training job usage general | 0 count | Adjustable |
ml.m7i.2xlarge for spot training job usage ml.m7i.2xlarge for spot training job usage general | 0 count | Adjustable |
ml.c6g.xlarge for endpoint usage ml.c6g.xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m5d.large for notebook instance usage ml.m5d.large for notebook instance usage capacity | 1 count | Adjustable |
ml.g6.48xlarge for endpoint usage ml.g6.48xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m7i.xlarge for spot training job usage ml.m7i.xlarge for spot training job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.g6e.4xlarge instances Studio JupyterLab Apps running on ml.g6e.4xlarge instances capacity | 0 count | Adjustable |
ml.c6i.32xlarge for cluster usage ml.c6i.32xlarge for cluster usage capacity | 0 count | Adjustable |
ml.g5.2xlarge for transform job usage ml.g5.2xlarge for transform job usage general | 0 count | Adjustable |
ml.r5.4xlarge for endpoint usage ml.r5.4xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c4.2xlarge for training job usage ml.c4.2xlarge for training job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r6id.4xlarge instances Studio JupyterLab Apps running on ml.r6id.4xlarge instances capacity | 0 count | Adjustable |
ml.m4.xlarge for training job usage ml.m4.xlarge for training job usage general | 0 count | Adjustable |
Rate of ListTransformJobs requests Rate of ListTransformJobs requests throughput | 2 count | Fixed |
ml.r6gd.4xlarge for endpoint usage ml.r6gd.4xlarge for endpoint usage networking | 0 count | Adjustable |
ml.inf1.2xlarge for endpoint usage ml.inf1.2xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g6.8xlarge for notebook instance usage ml.g6.8xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r7i.4xlarge instances Studio JupyterLab Apps running on ml.r7i.4xlarge instances capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r5.12xlarge instances Studio CodeEditor Apps running on ml.r5.12xlarge instances capacity | 0 count | Adjustable |
ml.g5.48xlarge for spot training job usage ml.g5.48xlarge for spot training job usage general | 0 count | Adjustable |
ml.r5d.xlarge for endpoint usage ml.r5d.xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g6e.8xlarge for processing job usage ml.g6e.8xlarge for processing job usage general | 0 count | Adjustable |
ml.g6.24xlarge for training job usage ml.g6.24xlarge for training job usage general | 0 count | Adjustable |
ml.m7i.xlarge for cluster usage ml.m7i.xlarge for cluster usage capacity | 0 count | Adjustable |
ml.c6i.32xlarge for endpoint usage ml.c6i.32xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c5.2xlarge for processing job usage ml.c5.2xlarge for processing job usage general | 0 count | Adjustable |
Rate of UpdateEndpointWeightsAndCapacities requests Rate of UpdateEndpointWeightsAndCapacities requests throughput | 1 count | Fixed |
ml.m5.4xlarge for cluster usage ml.m5.4xlarge for cluster usage capacity | 0 count | Adjustable |
ml.r7i.16xlarge for transform job usage ml.r7i.16xlarge for transform job usage general | 0 count | Adjustable |
ml.c5.4xlarge for cluster usage ml.c5.4xlarge for cluster usage capacity | 0 count | Adjustable |
Total EBS volume size in GB across all notebook instances Total EBS volume size in GB across all notebook instances storage | 102,400 count | Adjustable |
ml.c6i.32xlarge for spot training job usage ml.c6i.32xlarge for spot training job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.p4de.24xlarge instances Studio JupyterLab Apps running on ml.p4de.24xlarge instances capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r5.2xlarge instances Studio JupyterLab Apps running on ml.r5.2xlarge instances capacity | 0 count | Adjustable |
ml.p5.4xlarge for spot training job usage ml.p5.4xlarge for spot training job usage general | 0 count | Adjustable |
ml.m6gd.4xlarge for endpoint usage ml.m6gd.4xlarge for endpoint usage networking | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.m5d.2xlarge instance Studio KernelGateway Apps running on ml.m5d.2xlarge instance networking | 1 count | Adjustable |
ml.m4.xlarge for training warm pool usage ml.m4.xlarge for training warm pool usage general | 0 count | Adjustable |
ml.g6.4xlarge for cluster spot instance usage ml.g6.4xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m5.large instances Studio JupyterLab Apps running on ml.m5.large instances capacity | 1 count | Adjustable |
Rate of ListLabelingJobsForWorkteam requests Rate of ListLabelingJobsForWorkteam requests throughput | 2 count | Fixed |
ml.c5n.xlarge for spot training job usage ml.c5n.xlarge for spot training job usage general | 0 count | Adjustable |
ml.c5.4xlarge for endpoint usage ml.c5.4xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c6id.4xlarge for notebook instance usage ml.c6id.4xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c7i.24xlarge instances Studio JupyterLab Apps running on ml.c7i.24xlarge instances capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c7i.2xlarge instances Studio CodeEditor Apps running on ml.c7i.2xlarge instances capacity | 1 count | Adjustable |
ml.m6g.large for endpoint usage ml.m6g.large for endpoint usage networking | 2 count | Adjustable |
ml.r7gd.8xlarge for endpoint usage ml.r7gd.8xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c5d.2xlarge for notebook instance usage ml.c5d.2xlarge for notebook instance usage capacity | 1 count | Adjustable |
ml.g6e.xlarge for training warm pool usage ml.g6e.xlarge for training warm pool usage general | 0 count | Adjustable |
ml.c5.9xlarge for training job usage ml.c5.9xlarge for training job usage general | 0 count | Adjustable |
ml.g6e.xlarge for training job usage ml.g6e.xlarge for training job usage general | 0 count | Adjustable |
ml.r6i.16xlarge for transform job usage ml.r6i.16xlarge for transform job usage general | 0 count | Adjustable |
ml.i3en.3xlarge for cluster spot instance usage ml.i3en.3xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.g4dn.2xlarge instances Studio CodeEditor Apps running on ml.g4dn.2xlarge instances capacity | 0 count | Adjustable |
ml.c6i.2xlarge for cluster usage ml.c6i.2xlarge for cluster usage capacity | 0 count | Adjustable |
ml.g6.48xlarge for training warm pool usage ml.g6.48xlarge for training warm pool usage general | 0 count | Adjustable |
ml.m7i.12xlarge for processing job usage ml.m7i.12xlarge for processing job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.g6e.12xlarge instances Studio JupyterLab Apps running on ml.g6e.12xlarge instances capacity | 0 count | Adjustable |
ml.c5.xlarge for transform job usage ml.c5.xlarge for transform job usage general | 0 count | Adjustable |
ml.g5.2xlarge for spot training job usage ml.g5.2xlarge for spot training job usage general | 0 count | Adjustable |
Maximum number of concurrently running model card export jobs allowed per account. Maximum number of concurrently running model card export jobs allowed per account. compute | 20 count | Adjustable |
ml.g4dn.8xlarge for spot training job usage ml.g4dn.8xlarge for spot training job usage general | 0 count | Adjustable |
ml.c6i.large for notebook instance usage ml.c6i.large for notebook instance usage capacity | 1 count | Adjustable |
ml.g4dn.8xlarge for training warm pool usage ml.g4dn.8xlarge for training warm pool usage general | 0 count | Adjustable |
ml.g6.48xlarge for processing job usage ml.g6.48xlarge for processing job usage general | 0 count | Adjustable |
ml.g4dn.12xlarge for processing job usage ml.g4dn.12xlarge for processing job usage general | 0 count | Adjustable |
ml.g7e.12xlarge for endpoint usage ml.g7e.12xlarge for endpoint usage networking | 0 count | Adjustable |
ml.trn1.32xlarge for notebook instance usage ml.trn1.32xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.c6gd.8xlarge for endpoint usage ml.c6gd.8xlarge for endpoint usage networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r6id.12xlarge instances Studio CodeEditor Apps running on ml.r6id.12xlarge instances capacity | 0 count | Adjustable |
ml.c6i.xlarge for training warm pool usage ml.c6i.xlarge for training warm pool usage general | 0 count | Adjustable |
ml.m6id.12xlarge for notebook instance usage ml.m6id.12xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r6id.2xlarge instances Studio JupyterLab Apps running on ml.r6id.2xlarge instances capacity | 0 count | Adjustable |
ml.m6i.xlarge for cluster usage ml.m6i.xlarge for cluster usage capacity | 0 count | Adjustable |
ml.g4dn.4xlarge for endpoint usage ml.g4dn.4xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c6g.4xlarge for endpoint usage ml.c6g.4xlarge for endpoint usage networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m5d.12xlarge instances Studio CodeEditor Apps running on ml.m5d.12xlarge instances capacity | 0 count | Adjustable |
ml.m4.16xlarge for processing job usage ml.m4.16xlarge for processing job usage general | 0 count | Adjustable |
ml.c5.large for cluster usage ml.c5.large for cluster usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r6i.32xlarge instances Studio JupyterLab Apps running on ml.r6i.32xlarge instances capacity | 0 count | Adjustable |
ml.inf2.48xlarge for endpoint usage ml.inf2.48xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g6.4xlarge for endpoint usage ml.g6.4xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g6e.16xlarge for endpoint usage ml.g6e.16xlarge for endpoint usage networking | 0 count | Adjustable |
Rate of ListNotebookInstances requests Rate of ListNotebookInstances requests throughput | 2 count | Fixed |
ml.c6i.16xlarge for endpoint usage ml.c6i.16xlarge for endpoint usage networking | 0 count | Adjustable |
RSessionGateway Apps running on ml.g4dn.12xlarge instance RSessionGateway Apps running on ml.g4dn.12xlarge instance networking | 0 count | Adjustable |
ml.r6id.4xlarge for notebook instance usage ml.r6id.4xlarge for notebook instance usage capacity | 0 count | Adjustable |
RSessionGateway Apps running on ml.r5.2xlarge instance RSessionGateway Apps running on ml.r5.2xlarge instance networking | 1 count | Adjustable |
ml.r5.4xlarge for spot training job usage ml.r5.4xlarge for spot training job usage general | 0 count | Adjustable |
ml.p3dn.24xlarge for spot training job usage ml.p3dn.24xlarge for spot training job usage general | 0 count | Adjustable |
ml.p4d.24xlarge for cluster usage ml.p4d.24xlarge for cluster usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m5d.24xlarge instances Studio JupyterLab Apps running on ml.m5d.24xlarge instances capacity | 0 count | Adjustable |
ml.m6i.4xlarge for training job usage ml.m6i.4xlarge for training job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r7i.24xlarge instances Studio CodeEditor Apps running on ml.r7i.24xlarge instances capacity | 0 count | Adjustable |
ml.c7i.2xlarge for notebook instance usage ml.c7i.2xlarge for notebook instance usage capacity | 0 count | Adjustable |
Maximum number of training jobs each hyper parameter tuning job can run in parallel at once Maximum number of training jobs each hyper parameter tuning job can run in parallel at once general | 10 count | Fixed |
ml.m4.10xlarge for training warm pool usage ml.m4.10xlarge for training warm pool usage general | 0 count | Adjustable |
ml.m4.4xlarge for spot training job usage ml.m4.4xlarge for spot training job usage general | 2 count | Adjustable |
RSessionGateway Apps running on ml.m5d.12xlarge instance RSessionGateway Apps running on ml.m5d.12xlarge instance networking | 0 count | Adjustable |
ml.c5d.large for endpoint usage ml.c5d.large for endpoint usage networking | 0 count | Adjustable |
ml.g5.xlarge for notebook instance usage ml.g5.xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.p5en.48xlarge instances Studio CodeEditor Apps running on ml.p5en.48xlarge instances capacity | 0 count | Adjustable |
ml.r5.xlarge for endpoint usage ml.r5.xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c5.large for cluster spot instance usage ml.c5.large for cluster spot instance usage capacity | 0 count | Adjustable |
ml.g6.8xlarge for spot training job usage ml.g6.8xlarge for spot training job usage general | 0 count | Adjustable |
ml.m4.4xlarge for endpoint usage ml.m4.4xlarge for endpoint usage networking | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.g6.16xlarge instances Studio JupyterLab Apps running on ml.g6.16xlarge instances capacity | 0 count | Adjustable |
ml.r5d.12xlarge for processing job usage ml.r5d.12xlarge for processing job usage general | 0 count | Adjustable |
Longest run time for a training job Longest run time for a training job general | 432,000 count | Adjustable |
ml.r5.8xlarge for spot training job usage ml.r5.8xlarge for spot training job usage general | 0 count | Adjustable |
ml.m4.2xlarge for notebook instance usage ml.m4.2xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.trn1n.32xlarge instances Studio KernelGateway Apps running on ml.trn1n.32xlarge instances networking | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.t3.xlarge instance Studio KernelGateway Apps running on ml.t3.xlarge instance networking | 0 count | Adjustable |
ml.m5.large for transform job usage ml.m5.large for transform job usage general | 0 count | Adjustable |
ml.m4.10xlarge for training job usage ml.m4.10xlarge for training job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r6i.16xlarge instances Studio JupyterLab Apps running on ml.r6i.16xlarge instances capacity | 0 count | Adjustable |
ml.g6e.2xlarge for cluster spot instance usage ml.g6e.2xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.m5d.2xlarge for notebook instance usage ml.m5d.2xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.r5d.24xlarge for training job usage ml.r5d.24xlarge for training job usage general | 0 count | Adjustable |
ml.g7e.8xlarge for training warm pool usage ml.g7e.8xlarge for training warm pool usage general | 0 count | Adjustable |
ml.g4dn.2xlarge for notebook instance usage ml.g4dn.2xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.r7i.2xlarge for cluster spot instance usage ml.r7i.2xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.c5n.4xlarge for cluster usage ml.c5n.4xlarge for cluster usage capacity | 0 count | Adjustable |
ml.p6-b200.48xlarge for endpoint usage ml.p6-b200.48xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r7i.12xlarge for training warm pool usage ml.r7i.12xlarge for training warm pool usage general | 0 count | Adjustable |
ml.r5d.16xlarge for training job usage ml.r5d.16xlarge for training job usage general | 0 count | Adjustable |
ml.p5.4xlarge for training job usage ml.p5.4xlarge for training job usage general | 0 count | Adjustable |
ml.g5.24xlarge for spot training job usage ml.g5.24xlarge for spot training job usage general | 0 count | Adjustable |
ml.g5.12xlarge for endpoint usage ml.g5.12xlarge for endpoint usage networking | 0 count | Adjustable |
Total number of Spot instances allowed across SageMaker HyperPod clusters Total number of Spot instances allowed across SageMaker HyperPod clusters capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m6i.8xlarge instances Studio CodeEditor Apps running on ml.m6i.8xlarge instances capacity | 0 count | Adjustable |
ml.g6e.24xlarge for training warm pool usage ml.g6e.24xlarge for training warm pool usage general | 0 count | Adjustable |
ml.c5.18xlarge for training warm pool usage ml.c5.18xlarge for training warm pool usage general | 0 count | Adjustable |
ml.m8g.medium for endpoint usage ml.m8g.medium for endpoint usage networking | 0 count | Adjustable |
ml.g5.12xlarge for cluster usage ml.g5.12xlarge for cluster usage capacity | 0 count | Adjustable |
ml.g7e.12xlarge for training warm pool usage ml.g7e.12xlarge for training warm pool usage general | 0 count | Adjustable |
ml.m6i.2xlarge for cluster usage ml.m6i.2xlarge for cluster usage capacity | 0 count | Adjustable |
RSessionGateway Apps running on ml.m5d.xlarge instance RSessionGateway Apps running on ml.m5d.xlarge instance networking | 1 count | Adjustable |
Studio JupyterLab Apps running on ml.m7i.16xlarge instances Studio JupyterLab Apps running on ml.m7i.16xlarge instances capacity | 0 count | Adjustable |
Total domains Total domains general | 2 count | Adjustable |
ml.m6i.2xlarge for transform job usage ml.m6i.2xlarge for transform job usage general | 0 count | Adjustable |
ml.c5n.18xlarge for cluster usage ml.c5n.18xlarge for cluster usage capacity | 0 count | Adjustable |
ml.m5.large for training job usage ml.m5.large for training job usage general | 0 count | Adjustable |
ml.g4dn.xlarge for training job usage ml.g4dn.xlarge for training job usage general | 0 count | Adjustable |
ml.c4.xlarge for transform job usage ml.c4.xlarge for transform job usage general | 0 count | Adjustable |
ml.c6i.xlarge for notebook instance usage ml.c6i.xlarge for notebook instance usage capacity | 1 count | Adjustable |
RSessionGateway Apps running on ml.m5.24xlarge instance RSessionGateway Apps running on ml.m5.24xlarge instance networking | 0 count | Adjustable |
ml.g5.4xlarge for training warm pool usage ml.g5.4xlarge for training warm pool usage general | 0 count | Adjustable |
ml.c6i.4xlarge for processing job usage ml.c6i.4xlarge for processing job usage general | 0 count | Adjustable |
ml.c6id.32xlarge for notebook instance usage ml.c6id.32xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.m7i.xlarge for notebook instance usage ml.m7i.xlarge for notebook instance usage capacity | 1 count | Adjustable |
ml.r5.large for spot training job usage ml.r5.large for spot training job usage general | 0 count | Adjustable |
ml.m6gd.large for endpoint usage ml.m6gd.large for endpoint usage networking | 0 count | Adjustable |
ml.t3.2xlarge for spot training job usage ml.t3.2xlarge for spot training job usage general | 0 count | Adjustable |
ml.m6i.2xlarge for notebook instance usage ml.m6i.2xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.m6i.16xlarge for spot training job usage ml.m6i.16xlarge for spot training job usage general | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.c5.9xlarge instance Studio KernelGateway Apps running on ml.c5.9xlarge instance networking | 0 count | Adjustable |
ml.c6i.2xlarge for transform job usage ml.c6i.2xlarge for transform job usage general | 0 count | Adjustable |
ml.m7i.2xlarge for cluster usage ml.m7i.2xlarge for cluster usage capacity | 0 count | Adjustable |
ml.g7e.8xlarge for processing job usage ml.g7e.8xlarge for processing job usage general | 0 count | Adjustable |
ml.m4.10xlarge for spot training job usage ml.m4.10xlarge for spot training job usage general | 0 count | Adjustable |
ml.r6g.16xlarge for endpoint usage ml.r6g.16xlarge for endpoint usage networking | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.g4dn.xlarge instances Studio JupyterLab Apps running on ml.g4dn.xlarge instances capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c5.2xlarge instances Studio CodeEditor Apps running on ml.c5.2xlarge instances capacity | 1 count | Adjustable |
Studio JupyterLab Apps running on ml.g6.xlarge instances Studio JupyterLab Apps running on ml.g6.xlarge instances capacity | 0 count | Adjustable |
Rate of UpdateNotebookInstanceLifecycleConfig requests Rate of UpdateNotebookInstanceLifecycleConfig requests throughput | 1 count | Fixed |
ml.inf1.24xlarge for endpoint usage ml.inf1.24xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c5.18xlarge for spot training job usage ml.c5.18xlarge for spot training job usage general | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.p3.16xlarge instance Studio KernelGateway Apps running on ml.p3.16xlarge instance networking | 0 count | Adjustable |
ml.m5.4xlarge for training warm pool usage ml.m5.4xlarge for training warm pool usage general | 0 count | Adjustable |
ml.m6i.16xlarge for transform job usage ml.m6i.16xlarge for transform job usage general | 0 count | Adjustable |
ml.m4.16xlarge for spot training job usage ml.m4.16xlarge for spot training job usage general | 0 count | Adjustable |
ml.m5.2xlarge for transform job usage ml.m5.2xlarge for transform job usage general | 0 count | Adjustable |
ml.g6.xlarge for spot training job usage ml.g6.xlarge for spot training job usage general | 0 count | Adjustable |
ml.m7i.48xlarge for cluster usage ml.m7i.48xlarge for cluster usage capacity | 0 count | Adjustable |
ml.c5.9xlarge for training warm pool usage ml.c5.9xlarge for training warm pool usage general | 0 count | Adjustable |
ml.c4.xlarge for training warm pool usage ml.c4.xlarge for training warm pool usage general | 0 count | Adjustable |
Total number of instances allowed across SageMaker HyperPod clusters Total number of instances allowed across SageMaker HyperPod clusters capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.g6.4xlarge instances Studio CodeEditor Apps running on ml.g6.4xlarge instances capacity | 0 count | Adjustable |
ml.c5.18xlarge for training job usage ml.c5.18xlarge for training job usage general | 0 count | Adjustable |
ml.m5.4xlarge for training job usage ml.m5.4xlarge for training job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.g4dn.16xlarge instances Studio JupyterLab Apps running on ml.g4dn.16xlarge instances capacity | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.trn1.32xlarge instances Studio KernelGateway Apps running on ml.trn1.32xlarge instances networking | 0 count | Adjustable |
Total number of experiments allowed, excluding those automatically created by SageMaker Total number of experiments allowed, excluding those automatically created by SageMaker general | 5,000 count | Adjustable |
ml.m6i.large for processing job usage ml.m6i.large for processing job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m6i.24xlarge instances Studio CodeEditor Apps running on ml.m6i.24xlarge instances capacity | 0 count | Adjustable |
ml.m7i.48xlarge for endpoint usage ml.m7i.48xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g6e.2xlarge for spot training job usage ml.g6e.2xlarge for spot training job usage general | 0 count | Adjustable |
ml.r7i.16xlarge for cluster spot instance usage ml.r7i.16xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Rate of ListLabelingJobs requests Rate of ListLabelingJobs requests throughput | 2 count | Fixed |
ml.c6g.16xlarge for endpoint usage ml.c6g.16xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m7i.12xlarge for cluster spot instance usage ml.m7i.12xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.t3.xlarge instances Studio CodeEditor Apps running on ml.t3.xlarge instances capacity | 6 count | Adjustable |
Studio KernelGateway Apps running on ml.t3.large instance Studio KernelGateway Apps running on ml.t3.large instance networking | 0 count | Adjustable |
ml.i3en.large for cluster spot instance usage ml.i3en.large for cluster spot instance usage capacity | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.g5.4xlarge instance Studio KernelGateway Apps running on ml.g5.4xlarge instance networking | 0 count | Adjustable |
ml.r7i.24xlarge for cluster spot instance usage ml.r7i.24xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.g4dn.4xlarge for processing job usage ml.g4dn.4xlarge for processing job usage general | 0 count | Adjustable |
ml.r5d.xlarge for processing job usage ml.r5d.xlarge for processing job usage general | 0 count | Adjustable |
ml.p3.8xlarge for transform job usage ml.p3.8xlarge for transform job usage general | 0 count | Adjustable |
ml.c5.4xlarge for transform job usage ml.c5.4xlarge for transform job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c7i.large instances Studio CodeEditor Apps running on ml.c7i.large instances capacity | 1 count | Adjustable |
ml.t2.medium for notebook instance usage ml.t2.medium for notebook instance usage capacity | 6 count | Adjustable |
Studio CodeEditor Apps running on ml.g4dn.xlarge instances Studio CodeEditor Apps running on ml.g4dn.xlarge instances capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c7i.4xlarge instances Studio JupyterLab Apps running on ml.c7i.4xlarge instances capacity | 0 count | Adjustable |
ml.c6id.8xlarge for notebook instance usage ml.c6id.8xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r6id.8xlarge instances Studio JupyterLab Apps running on ml.r6id.8xlarge instances capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r6id.xlarge instances Studio JupyterLab Apps running on ml.r6id.xlarge instances capacity | 1 count | Adjustable |
Maximum number of dataset objects per labeling job Maximum number of dataset objects per labeling job storage | 10,000 count | Fixed |
ml.c7i.24xlarge for notebook instance usage ml.c7i.24xlarge for notebook instance usage capacity | 0 count | Adjustable |
RSessionGateway Apps running on ml.c5.large instance RSessionGateway Apps running on ml.c5.large instance networking | 1 count | Adjustable |
Studio JupyterLab Apps running on ml.m7i.12xlarge instances Studio JupyterLab Apps running on ml.m7i.12xlarge instances capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c6i.16xlarge instances Studio CodeEditor Apps running on ml.c6i.16xlarge instances capacity | 0 count | Adjustable |
ml.r6gd.8xlarge for endpoint usage ml.r6gd.8xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c7i.48xlarge for training warm pool usage ml.c7i.48xlarge for training warm pool usage general | 0 count | Adjustable |
ml.r5d.large for spot training job usage ml.r5d.large for spot training job usage general | 0 count | Adjustable |
ml.r6i.2xlarge for transform job usage ml.r6i.2xlarge for transform job usage general | 0 count | Adjustable |
RSessionGateway Apps running on ml.t3.2xlarge instance RSessionGateway Apps running on ml.t3.2xlarge instance networking | 0 count | Adjustable |
ml.g5.12xlarge for transform job usage ml.g5.12xlarge for transform job usage general | 0 count | Adjustable |
ml.c5.xlarge for notebook instance usage ml.c5.xlarge for notebook instance usage capacity | 1 count | Adjustable |
Studio CodeEditor Apps running on ml.p4de.24xlarge instances Studio CodeEditor Apps running on ml.p4de.24xlarge instances capacity | 0 count | Adjustable |
ml.g6.xlarge for training job usage ml.g6.xlarge for training job usage general | 0 count | Adjustable |
RSessionGateway Apps running on ml.g4dn.xlarge instance RSessionGateway Apps running on ml.g4dn.xlarge instance networking | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.p4de.24xlarge instances Studio KernelGateway Apps running on ml.p4de.24xlarge instances networking | 0 count | Adjustable |
ml.r5d.2xlarge for processing job usage ml.r5d.2xlarge for processing job usage general | 0 count | Adjustable |
ml.trn1.32xlarge for transform job usage ml.trn1.32xlarge for transform job usage general | 0 count | Adjustable |
ml.m6i.12xlarge for transform job usage ml.m6i.12xlarge for transform job usage general | 0 count | Adjustable |
ml.c4.8xlarge for processing job usage ml.c4.8xlarge for processing job usage general | 0 count | Adjustable |
Rate of DescribeWorkteam requests Rate of DescribeWorkteam requests throughput | 5 count | Fixed |
Rate of StartNotebookInstance requests Rate of StartNotebookInstance requests throughput | 1 count | Fixed |
ml.g6e.8xlarge for training job usage ml.g6e.8xlarge for training job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c6id.32xlarge instances Studio CodeEditor Apps running on ml.c6id.32xlarge instances capacity | 0 count | Adjustable |
ml.p5en.48xlarge for training warm pool usage ml.p5en.48xlarge for training warm pool usage general | 0 count | Adjustable |
ml.g6.12xlarge for training job usage ml.g6.12xlarge for training job usage general | 0 count | Adjustable |
Number of ml.p5en.48xlarge instances in reserved capacity across training plans per Region Number of ml.p5en.48xlarge instances in reserved capacity across training plans per Region capacity | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.g5.8xlarge instance Studio KernelGateway Apps running on ml.g5.8xlarge instance networking | 0 count | Adjustable |
ml.m6g.xlarge for endpoint usage ml.m6g.xlarge for endpoint usage networking | 1 count | Adjustable |
ml.m7i.24xlarge for cluster spot instance usage ml.m7i.24xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.r7i.16xlarge for endpoint usage ml.r7i.16xlarge for endpoint usage networking | 0 count | Adjustable |
ml.p3.16xlarge for transform job usage ml.p3.16xlarge for transform job usage general | 0 count | Adjustable |
Maximum number of cluster scheduler config versions allowed per account in each region. Maximum number of cluster scheduler config versions allowed per account in each region. capacity | 100 count | Adjustable |
Studio CodeEditor Apps running on ml.c6i.4xlarge instances Studio CodeEditor Apps running on ml.c6i.4xlarge instances capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c6id.4xlarge instances Studio CodeEditor Apps running on ml.c6id.4xlarge instances capacity | 0 count | Adjustable |
ml.c4.4xlarge for notebook instance usage ml.c4.4xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.g4dn.16xlarge for notebook instance usage ml.g4dn.16xlarge for notebook instance usage capacity | 0 count | Adjustable |
Maximum dataset size AutoML job can be run on Maximum dataset size AutoML job can be run on storage | 100 count | Fixed |
ml.c7i.24xlarge for training job usage ml.c7i.24xlarge for training job usage general | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.p4d.24xlarge instances Studio KernelGateway Apps running on ml.p4d.24xlarge instances networking | 0 count | Adjustable |
ml.p5e.48xlarge for cluster usage ml.p5e.48xlarge for cluster usage capacity | 0 count | Adjustable |
ml.g4dn.2xlarge for transform job usage ml.g4dn.2xlarge for transform job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.g6e.2xlarge instances Studio JupyterLab Apps running on ml.g6e.2xlarge instances capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m6id.8xlarge instances Studio CodeEditor Apps running on ml.m6id.8xlarge instances capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.t3.medium instances Studio CodeEditor Apps running on ml.t3.medium instances capacity | 6 count | Adjustable |
ml.r7i.large for cluster spot instance usage ml.r7i.large for cluster spot instance usage capacity | 0 count | Adjustable |
RSessionGateway Apps running on ml.m5.8xlarge instance RSessionGateway Apps running on ml.m5.8xlarge instance networking | 0 count | Adjustable |
ml.r7gd.2xlarge for endpoint usage ml.r7gd.2xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m5d.4xlarge for notebook instance usage ml.m5d.4xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.m6i.8xlarge for processing job usage ml.m6i.8xlarge for processing job usage general | 0 count | Adjustable |
RSessionGateway Apps running on ml.r5.8xlarge instance RSessionGateway Apps running on ml.r5.8xlarge instance networking | 0 count | Adjustable |
ml.r5.12xlarge for training warm pool usage ml.r5.12xlarge for training warm pool usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c6id.24xlarge instances Studio JupyterLab Apps running on ml.c6id.24xlarge instances capacity | 0 count | Adjustable |
ml.g6e.16xlarge for training job usage ml.g6e.16xlarge for training job usage general | 0 count | Adjustable |
ml.r6i.4xlarge for transform job usage ml.r6i.4xlarge for transform job usage general | 0 count | Adjustable |
ml.g7e.24xlarge for training job usage ml.g7e.24xlarge for training job usage general | 0 count | Adjustable |
ml.r7i.large for processing job usage ml.r7i.large for processing job usage general | 0 count | Adjustable |
ml.g4dn.xlarge for processing job usage ml.g4dn.xlarge for processing job usage general | 0 count | Adjustable |
Rate of InvokeEndpoint requests Rate of InvokeEndpoint requests throughput | 10,000 count | Fixed |
ml.c5n.18xlarge for training warm pool usage ml.c5n.18xlarge for training warm pool usage general | 0 count | Adjustable |
ml.c5n.9xlarge for cluster spot instance usage ml.c5n.9xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.trn2.48xlarge for cluster usage ml.trn2.48xlarge for cluster usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m5d.large instances Studio CodeEditor Apps running on ml.m5d.large instances capacity | 1 count | Adjustable |
ml.trn1n.32xlarge for spot training job usage ml.trn1n.32xlarge for spot training job usage general | 0 count | Adjustable |
ml.c7i.large for transform job usage ml.c7i.large for transform job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.g5.16xlarge instances Studio CodeEditor Apps running on ml.g5.16xlarge instances capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m7i.24xlarge instances Studio CodeEditor Apps running on ml.m7i.24xlarge instances capacity | 0 count | Adjustable |
ml.m7i.large for transform job usage ml.m7i.large for transform job usage general | 0 count | Adjustable |
ml.m7i.large for training warm pool usage ml.m7i.large for training warm pool usage general | 0 count | Adjustable |
ml.c5.4xlarge for spot training job usage ml.c5.4xlarge for spot training job usage general | 1 count | Adjustable |
Studio CodeEditor Apps running on ml.g6.8xlarge instances Studio CodeEditor Apps running on ml.g6.8xlarge instances capacity | 0 count | Adjustable |
ml.g6e.24xlarge for training job usage ml.g6e.24xlarge for training job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m5d.large instances Studio JupyterLab Apps running on ml.m5d.large instances capacity | 1 count | Adjustable |
ml.c5d.18xlarge for endpoint usage ml.c5d.18xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g6.8xlarge for cluster usage ml.g6.8xlarge for cluster usage capacity | 0 count | Adjustable |
ml.m6i.12xlarge for processing job usage ml.m6i.12xlarge for processing job usage general | 0 count | Adjustable |
ml.g6.48xlarge for cluster usage ml.g6.48xlarge for cluster usage capacity | 0 count | Adjustable |
Maximum number of training jobs that each hyperparameter tuning job can create Maximum number of training jobs that each hyperparameter tuning job can create general | 750 count | Fixed |
ml.g5.16xlarge for endpoint usage ml.g5.16xlarge for endpoint usage networking | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m5.xlarge instances Studio JupyterLab Apps running on ml.m5.xlarge instances capacity | 1 count | Adjustable |
Studio JupyterLab Apps running on ml.g6e.24xlarge instances Studio JupyterLab Apps running on ml.g6e.24xlarge instances capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.g6.48xlarge instances Studio JupyterLab Apps running on ml.g6.48xlarge instances capacity | 0 count | Adjustable |
ml.g4dn.12xlarge for training job usage ml.g4dn.12xlarge for training job usage general | 0 count | Adjustable |
ml.m5d.24xlarge for endpoint usage ml.m5d.24xlarge for endpoint usage networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r7i.xlarge instances Studio CodeEditor Apps running on ml.r7i.xlarge instances capacity | 1 count | Adjustable |
ml.g7e.2xlarge for endpoint usage ml.g7e.2xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r7i.48xlarge for endpoint usage ml.r7i.48xlarge for endpoint usage networking | 0 count | Adjustable |
Rate of DeleteTrainingJob requests Rate of DeleteTrainingJob requests throughput | 1 count | Fixed |
ml.trn1.32xlarge for endpoint usage ml.trn1.32xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m7i.large for cluster usage ml.m7i.large for cluster usage capacity | 0 count | Adjustable |
ml.r5.xlarge for processing job usage ml.r5.xlarge for processing job usage general | 0 count | Adjustable |
ml.g5.48xlarge for training job usage ml.g5.48xlarge for training job usage general | 0 count | Adjustable |
ml.m7i.8xlarge for processing job usage ml.m7i.8xlarge for processing job usage general | 0 count | Adjustable |
ml.r7i.8xlarge for training warm pool usage ml.r7i.8xlarge for training warm pool usage general | 0 count | Adjustable |
ml.c8g.16xlarge for endpoint usage ml.c8g.16xlarge for endpoint usage networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.p4d.24xlarge instances Studio CodeEditor Apps running on ml.p4d.24xlarge instances capacity | 0 count | Adjustable |
ml.c5n.9xlarge for cluster usage ml.c5n.9xlarge for cluster usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r7i.8xlarge instances Studio CodeEditor Apps running on ml.r7i.8xlarge instances capacity | 0 count | Adjustable |
ml.c6i.large for endpoint usage ml.c6i.large for endpoint usage networking | 0 count | Adjustable |
ml.p3.16xlarge for notebook instance usage ml.p3.16xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.g5.8xlarge for transform job usage ml.g5.8xlarge for transform job usage general | 0 count | Adjustable |
ml.eia2.xlarge for endpoint usage ml.eia2.xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r6i.32xlarge for cluster spot instance usage ml.r6i.32xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.c6i.16xlarge for notebook instance usage ml.c6i.16xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.m7i.xlarge for transform job usage ml.m7i.xlarge for transform job usage general | 0 count | Adjustable |
ml.p5en.48xlarge for training job usage ml.p5en.48xlarge for training job usage general | 0 count | Adjustable |
ml.i3en.24xlarge for cluster spot instance usage ml.i3en.24xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.c5n.large for cluster spot instance usage ml.c5n.large for cluster spot instance usage capacity | 0 count | Adjustable |
ml.m6i.large for training job usage ml.m6i.large for training job usage general | 0 count | Adjustable |
ml.r5d.2xlarge for training job usage ml.r5d.2xlarge for training job usage general | 0 count | Adjustable |
ml.m7i.24xlarge for training warm pool usage ml.m7i.24xlarge for training warm pool usage general | 0 count | Adjustable |
ml.r7i.16xlarge for training warm pool usage ml.r7i.16xlarge for training warm pool usage general | 0 count | Adjustable |
ml.g6.4xlarge for processing job usage ml.g6.4xlarge for processing job usage general | 0 count | Adjustable |
Medium-sized MLflow Tracking Server usage Medium-sized MLflow Tracking Server usage storage | 5 count | Adjustable |
Studio JupyterLab Apps running on ml.r7i.2xlarge instances Studio JupyterLab Apps running on ml.r7i.2xlarge instances capacity | 0 count | Adjustable |
ml.m5.4xlarge for processing job usage ml.m5.4xlarge for processing job usage general | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.c5.large instance Studio KernelGateway Apps running on ml.c5.large instance networking | 1 count | Adjustable |
Canvas Apps running on ml.m5.4xlarge instances Canvas Apps running on ml.m5.4xlarge instances capacity | 10 count | Adjustable |
Studio JupyterLab Apps running on ml.c5.4xlarge instances Studio JupyterLab Apps running on ml.c5.4xlarge instances capacity | 0 count | Adjustable |
Maximum number of running Studio apps allowed per account Maximum number of running Studio apps allowed per account general | 40 count | Adjustable |
RSessionGateway Apps running on ml.c5.4xlarge instance RSessionGateway Apps running on ml.c5.4xlarge instance networking | 0 count | Adjustable |
ml.c7i.16xlarge for training warm pool usage ml.c7i.16xlarge for training warm pool usage general | 0 count | Adjustable |
ml.m5.12xlarge for endpoint usage ml.m5.12xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m5d.8xlarge for notebook instance usage ml.m5d.8xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.r5.8xlarge for training warm pool usage ml.r5.8xlarge for training warm pool usage general | 0 count | Adjustable |
ml.g5.2xlarge for processing job usage ml.g5.2xlarge for processing job usage general | 0 count | Adjustable |
ml.r5d.2xlarge for spot training job usage ml.r5d.2xlarge for spot training job usage general | 0 count | Adjustable |
ml.c6i.4xlarge for training job usage ml.c6i.4xlarge for training job usage general | 0 count | Adjustable |
ml.m5.2xlarge for cluster spot instance usage ml.m5.2xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.g4dn.12xlarge instances Studio JupyterLab Apps running on ml.g4dn.12xlarge instances capacity | 0 count | Adjustable |
ml.r6i.large for cluster usage ml.r6i.large for cluster usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r7i.2xlarge instances Studio CodeEditor Apps running on ml.r7i.2xlarge instances capacity | 0 count | Adjustable |
ml.m5.2xlarge for training job usage ml.m5.2xlarge for training job usage general | 0 count | Adjustable |
ml.g7e.12xlarge for spot training job usage ml.g7e.12xlarge for spot training job usage general | 0 count | Adjustable |
ml.m6id.xlarge for notebook instance usage ml.m6id.xlarge for notebook instance usage capacity | 1 count | Adjustable |
ml.c6i.32xlarge for notebook instance usage ml.c6i.32xlarge for notebook instance usage capacity | 0 count | Adjustable |
Number of instances across all transform jobs Number of instances across all transform jobs capacity | 4 count | Adjustable |
ml.m8g.16xlarge for endpoint usage ml.m8g.16xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c6i.xlarge for processing job usage ml.c6i.xlarge for processing job usage general | 0 count | Adjustable |
RSessionGateway Apps running on ml.r5.xlarge instance RSessionGateway Apps running on ml.r5.xlarge instance networking | 1 count | Adjustable |
ml.g6.4xlarge for cluster usage ml.g6.4xlarge for cluster usage capacity | 0 count | Adjustable |
ml.c5.xlarge for endpoint usage ml.c5.xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m6i.xlarge for notebook instance usage ml.m6i.xlarge for notebook instance usage capacity | 1 count | Adjustable |
ml.g5.48xlarge for transform job usage ml.g5.48xlarge for transform job usage general | 0 count | Adjustable |
Number of training plans per Region Number of training plans per Region general | 25 count | Adjustable |
ml.g6.xlarge for processing job usage ml.g6.xlarge for processing job usage general | 0 count | Adjustable |
ml.r6i.24xlarge for transform job usage ml.r6i.24xlarge for transform job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c6id.8xlarge instances Studio CodeEditor Apps running on ml.c6id.8xlarge instances capacity | 0 count | Adjustable |
ml.m4.16xlarge for endpoint usage ml.m4.16xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c4.2xlarge for spot training job usage ml.c4.2xlarge for spot training job usage general | 4 count | Adjustable |
ml.r7i.48xlarge for transform job usage ml.r7i.48xlarge for transform job usage general | 0 count | Adjustable |
ml.g5.12xlarge for training warm pool usage ml.g5.12xlarge for training warm pool usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r6id.2xlarge instances Studio CodeEditor Apps running on ml.r6id.2xlarge instances capacity | 0 count | Adjustable |
ml.m5.large for cluster spot instance usage ml.m5.large for cluster spot instance usage capacity | 0 count | Adjustable |
ml.r7i.48xlarge for training job usage ml.r7i.48xlarge for training job usage general | 0 count | Adjustable |
Rate of DeleteStudioLifecycleConfig requests Rate of DeleteStudioLifecycleConfig requests throughput | 1 count | Fixed |
ml.r7i.48xlarge for processing job usage ml.r7i.48xlarge for processing job usage general | 0 count | Adjustable |
ml.g7e.24xlarge for spot training job usage ml.g7e.24xlarge for spot training job usage general | 0 count | Adjustable |
ml.r7i.8xlarge for training job usage ml.r7i.8xlarge for training job usage general | 0 count | Adjustable |
ml.r8g.2xlarge for endpoint usage ml.r8g.2xlarge for endpoint usage networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r6i.16xlarge instances Studio CodeEditor Apps running on ml.r6i.16xlarge instances capacity | 0 count | Adjustable |
ml.g4dn.16xlarge for spot training job usage ml.g4dn.16xlarge for spot training job usage general | 0 count | Adjustable |
ml.m6id.2xlarge for notebook instance usage ml.m6id.2xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r6id.xlarge instances Studio CodeEditor Apps running on ml.r6id.xlarge instances capacity | 1 count | Adjustable |
ml.r6i.xlarge for transform job usage ml.r6i.xlarge for transform job usage general | 0 count | Adjustable |
ml.c5.24xlarge for cluster spot instance usage ml.c5.24xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r5.12xlarge instances Studio JupyterLab Apps running on ml.r5.12xlarge instances capacity | 0 count | Adjustable |
ml.m6i.24xlarge for training job usage ml.m6i.24xlarge for training job usage general | 0 count | Adjustable |
Maximum number of compute quota versions allowed per account in each region. Maximum number of compute quota versions allowed per account in each region. compute | 100 count | Adjustable |
ml.m7i.12xlarge for spot training job usage ml.m7i.12xlarge for spot training job usage general | 0 count | Adjustable |
RSessionGateway Apps running on ml.m5.xlarge instance RSessionGateway Apps running on ml.m5.xlarge instance networking | 1 count | Adjustable |
ml.m5.xlarge for cluster usage ml.m5.xlarge for cluster usage capacity | 0 count | Adjustable |
Rate of UpdateTrainingJob requests Rate of UpdateTrainingJob requests throughput | 1 count | Fixed |
ml.m6i.12xlarge for cluster usage ml.m6i.12xlarge for cluster usage capacity | 0 count | Adjustable |
ml.inf2.24xlarge for transform job usage ml.inf2.24xlarge for transform job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r6id.8xlarge instances Studio CodeEditor Apps running on ml.r6id.8xlarge instances capacity | 0 count | Adjustable |
ml.t3.medium for processing job usage ml.t3.medium for processing job usage general | 4 count | Adjustable |
ml.m5.xlarge for notebook instance usage ml.m5.xlarge for notebook instance usage capacity | 1 count | Adjustable |
ml.m7i.2xlarge for endpoint usage ml.m7i.2xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m6i.large for cluster spot instance usage ml.m6i.large for cluster spot instance usage capacity | 0 count | Adjustable |
Rate of DeleteHumanTaskUi requests Rate of DeleteHumanTaskUi requests throughput | 1 count | Fixed |
Size of EBS volume for a transform job instance Size of EBS volume for a transform job instance storage | 1,024 count | Fixed |
ml.m5.large for endpoint usage ml.m5.large for endpoint usage networking | 0 count | Adjustable |
RSessionGateway Apps running on ml.g4dn.8xlarge instance RSessionGateway Apps running on ml.g4dn.8xlarge instance networking | 0 count | Adjustable |
ml.m5.12xlarge for notebook instance usage ml.m5.12xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.r5d.4xlarge for training warm pool usage ml.r5d.4xlarge for training warm pool usage general | 0 count | Adjustable |
ml.r8g.xlarge for endpoint usage ml.r8g.xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r5.xlarge for training job usage ml.r5.xlarge for training job usage general | 0 count | Adjustable |
ml.c7i.16xlarge for notebook instance usage ml.c7i.16xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.m5.8xlarge instance Studio KernelGateway Apps running on ml.m5.8xlarge instance networking | 0 count | Adjustable |
ml.m6i.8xlarge for training job usage ml.m6i.8xlarge for training job usage general | 0 count | Adjustable |
ml.r5.large for endpoint usage ml.r5.large for endpoint usage networking | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.g4dn.12xlarge instance Studio KernelGateway Apps running on ml.g4dn.12xlarge instance networking | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m6id.32xlarge instances Studio JupyterLab Apps running on ml.m6id.32xlarge instances capacity | 0 count | Adjustable |
ml.m7i.12xlarge for cluster usage ml.m7i.12xlarge for cluster usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c7i.48xlarge instances Studio CodeEditor Apps running on ml.c7i.48xlarge instances capacity | 0 count | Adjustable |
ml.c6i.12xlarge for processing job usage ml.c6i.12xlarge for processing job usage general | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.c5.12xlarge instance Studio KernelGateway Apps running on ml.c5.12xlarge instance networking | 0 count | Adjustable |
ml.g7e.8xlarge for training job usage ml.g7e.8xlarge for training job usage general | 0 count | Adjustable |
ml.p5e.48xlarge for training warm pool usage ml.p5e.48xlarge for training warm pool usage general | 0 count | Adjustable |
ml.c5.18xlarge for processing job usage ml.c5.18xlarge for processing job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c6i.32xlarge instances Studio JupyterLab Apps running on ml.c6i.32xlarge instances capacity | 0 count | Adjustable |
ml.r7i.8xlarge for endpoint usage ml.r7i.8xlarge for endpoint usage networking | 0 count | Adjustable |
Size of EBS volume for a processing job instance Size of EBS volume for a processing job instance storage | 1,024 count | Adjustable |
Studio JupyterLab Apps running on ml.m5d.12xlarge instances Studio JupyterLab Apps running on ml.m5d.12xlarge instances capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m5d.4xlarge instances Studio JupyterLab Apps running on ml.m5d.4xlarge instances capacity | 0 count | Adjustable |
ml.m6i.large for notebook instance usage ml.m6i.large for notebook instance usage capacity | 1 count | Adjustable |
ml.r6i.12xlarge for transform job usage ml.r6i.12xlarge for transform job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m6i.large instances Studio CodeEditor Apps running on ml.m6i.large instances capacity | 1 count | Adjustable |
ml.trn1n.32xlarge for cluster spot instance usage ml.trn1n.32xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.r8g.48xlarge for endpoint usage ml.r8g.48xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c6i.12xlarge for endpoint usage ml.c6i.12xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m7i.24xlarge for transform job usage ml.m7i.24xlarge for transform job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m5d.2xlarge instances Studio CodeEditor Apps running on ml.m5d.2xlarge instances capacity | 0 count | Adjustable |
ml.m7i.2xlarge for processing job usage ml.m7i.2xlarge for processing job usage general | 0 count | Adjustable |
ml.g7e.8xlarge for endpoint usage ml.g7e.8xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r7i.4xlarge for notebook instance usage ml.r7i.4xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.g6.48xlarge instances Studio CodeEditor Apps running on ml.g6.48xlarge instances capacity | 0 count | Adjustable |
ml.g6.xlarge for training warm pool usage ml.g6.xlarge for training warm pool usage general | 0 count | Adjustable |
ml.c7i.12xlarge for processing job usage ml.c7i.12xlarge for processing job usage general | 0 count | Adjustable |
ml.r7i.xlarge for transform job usage ml.r7i.xlarge for transform job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m6id.8xlarge instances Studio JupyterLab Apps running on ml.m6id.8xlarge instances capacity | 0 count | Adjustable |
ml.g6e.4xlarge for cluster usage ml.g6e.4xlarge for cluster usage capacity | 0 count | Adjustable |
ml.r6i.8xlarge for cluster usage ml.r6i.8xlarge for cluster usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r7i.16xlarge instances Studio CodeEditor Apps running on ml.r7i.16xlarge instances capacity | 0 count | Adjustable |
ml.trn1n.32xlarge for training warm pool usage ml.trn1n.32xlarge for training warm pool usage general | 0 count | Adjustable |
ml.m5.xlarge for cluster spot instance usage ml.m5.xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.g5.24xlarge for training job usage ml.g5.24xlarge for training job usage general | 0 count | Adjustable |
ml.c4.xlarge for endpoint usage ml.c4.xlarge for endpoint usage networking | 0 count | Adjustable |
Number of ml.p4de.24xlarge instances in reserved capacity across training plans per Region Number of ml.p4de.24xlarge instances in reserved capacity across training plans per Region capacity | 0 count | Adjustable |
ml.m7i.16xlarge for notebook instance usage ml.m7i.16xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.g7e.12xlarge for processing job usage ml.g7e.12xlarge for processing job usage general | 0 count | Adjustable |
Rate of DescribeEndpoint requests Rate of DescribeEndpoint requests throughput | 5 count | Fixed |
Rate of DeleteMlflowApp requests Rate of DeleteMlflowApp requests throughput | 2 count | Fixed |
ml.g5.24xlarge for notebook instance usage ml.g5.24xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.c4.4xlarge for processing job usage ml.c4.4xlarge for processing job usage general | 0 count | Adjustable |
ml.t3.xlarge for cluster usage ml.t3.xlarge for cluster usage capacity | 0 count | Adjustable |
ml.g6e.48xlarge for processing job usage ml.g6e.48xlarge for processing job usage general | 0 count | Adjustable |
ml.c5.9xlarge for cluster usage ml.c5.9xlarge for cluster usage capacity | 0 count | Adjustable |
ml.m7i.large for spot training job usage ml.m7i.large for spot training job usage general | 0 count | Adjustable |
ml.p3.2xlarge for transform job usage ml.p3.2xlarge for transform job usage general | 0 count | Adjustable |
ml.r5d.4xlarge for endpoint usage ml.r5d.4xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r5.large for notebook instance usage ml.r5.large for notebook instance usage capacity | 1 count | Adjustable |
Studio KernelGateway Apps running on ml.t3.medium instance Studio KernelGateway Apps running on ml.t3.medium instance networking | 2 count | Adjustable |
ml.m5d.16xlarge for notebook instance usage ml.m5d.16xlarge for notebook instance usage capacity | 0 count | Adjustable |
RSessionGateway Apps running on ml.p3.16xlarge instance RSessionGateway Apps running on ml.p3.16xlarge instance networking | 0 count | Adjustable |
ml.m6i.large for transform job usage ml.m6i.large for transform job usage general | 0 count | Adjustable |
ml.g5.4xlarge for notebook instance usage ml.g5.4xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r7i.large instances Studio JupyterLab Apps running on ml.r7i.large instances capacity | 1 count | Adjustable |
ml.p4d.24xlarge for endpoint usage ml.p4d.24xlarge for endpoint usage networking | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c7i.large instances Studio JupyterLab Apps running on ml.c7i.large instances capacity | 1 count | Adjustable |
ml.trn1.2xlarge for notebook instance usage ml.trn1.2xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.c5d.9xlarge for endpoint usage ml.c5d.9xlarge for endpoint usage networking | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.m5d.24xlarge instance Studio KernelGateway Apps running on ml.m5d.24xlarge instance networking | 0 count | Adjustable |
ml.r5d.4xlarge for training job usage ml.r5d.4xlarge for training job usage general | 0 count | Adjustable |
ml.r7i.xlarge for cluster spot instance usage ml.r7i.xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Maximum number of concurrent AutoML Jobs Maximum number of concurrent AutoML Jobs compute | 1 count | Adjustable |
ml.g4dn.8xlarge for transform job usage ml.g4dn.8xlarge for transform job usage general | 0 count | Adjustable |
ml.p5.4xlarge for training warm pool usage ml.p5.4xlarge for training warm pool usage general | 0 count | Adjustable |
Maximum number of Studio user profiles allowed per account Maximum number of Studio user profiles allowed per account storage | 2 count | Adjustable |
ml.r7i.4xlarge for spot training job usage ml.r7i.4xlarge for spot training job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.g6e.2xlarge instances Studio CodeEditor Apps running on ml.g6e.2xlarge instances capacity | 0 count | Adjustable |
ml.m5.12xlarge for spot training job usage ml.m5.12xlarge for spot training job usage general | 0 count | Adjustable |
ml.c7g.large for endpoint usage ml.c7g.large for endpoint usage networking | 0 count | Adjustable |
ml.c8g.48xlarge for endpoint usage ml.c8g.48xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m8g.24xlarge for endpoint usage ml.m8g.24xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g6.xlarge for endpoint usage ml.g6.xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c7i.8xlarge for training job usage ml.c7i.8xlarge for training job usage general | 0 count | Adjustable |
ml.p5.48xlarge for cluster spot instance usage ml.p5.48xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Maximum total FSx Lustre capacity in TiB across SageMaker HyperPod restricted instance groups Maximum total FSx Lustre capacity in TiB across SageMaker HyperPod restricted instance groups capacity | 0 count | Adjustable |
Rate of CreatePresignedMlflowAppUrl requests Rate of CreatePresignedMlflowAppUrl requests throughput | 5 count | Fixed |
ml.c6i.12xlarge for notebook instance usage ml.c6i.12xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.c6i.32xlarge for cluster spot instance usage ml.c6i.32xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.m5.2xlarge for cluster usage ml.m5.2xlarge for cluster usage capacity | 0 count | Adjustable |
ml.c5n.18xlarge for training job usage ml.c5n.18xlarge for training job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m5d.16xlarge instances Studio CodeEditor Apps running on ml.m5d.16xlarge instances capacity | 0 count | Adjustable |
ml.c6i.24xlarge for endpoint usage ml.c6i.24xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g5.2xlarge for cluster spot instance usage ml.g5.2xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.g5.xlarge for cluster usage ml.g5.xlarge for cluster usage capacity | 0 count | Adjustable |
ml.t3.xlarge for processing job usage ml.t3.xlarge for processing job usage general | 2 count | Adjustable |
ml.inf2.24xlarge for notebook instance usage ml.inf2.24xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.g6.2xlarge for notebook instance usage ml.g6.2xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.c5.xlarge for cluster usage ml.c5.xlarge for cluster usage capacity | 0 count | Adjustable |
ml.r7i.4xlarge for endpoint usage ml.r7i.4xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c7i.48xlarge for notebook instance usage ml.c7i.48xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.c6i.16xlarge for spot training job usage ml.c6i.16xlarge for spot training job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c6i.24xlarge instances Studio JupyterLab Apps running on ml.c6i.24xlarge instances capacity | 0 count | Adjustable |
ml.g5.2xlarge for endpoint usage ml.g5.2xlarge for endpoint usage networking | 0 count | Adjustable |
ml.t2.2xlarge for notebook instance usage ml.t2.2xlarge for notebook instance usage capacity | 6 count | Adjustable |
Maximum number of Ground Truth labeling jobs Maximum number of Ground Truth labeling jobs general | 1 count | Adjustable |
ml.r6gd.16xlarge for endpoint usage ml.r6gd.16xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g6e.48xlarge for cluster spot instance usage ml.g6e.48xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.inf2.8xlarge for endpoint usage ml.inf2.8xlarge for endpoint usage networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r6i.4xlarge instances Studio CodeEditor Apps running on ml.r6i.4xlarge instances capacity | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.r5.4xlarge instance Studio KernelGateway Apps running on ml.r5.4xlarge instance networking | 1 count | Adjustable |
ml.g6.16xlarge for spot training job usage ml.g6.16xlarge for spot training job usage general | 0 count | Adjustable |
ml.g6.4xlarge for spot training job usage ml.g6.4xlarge for spot training job usage general | 0 count | Adjustable |
ml.c7i.24xlarge for processing job usage ml.c7i.24xlarge for processing job usage general | 0 count | Adjustable |
ml.r5.large for processing job usage ml.r5.large for processing job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c5.12xlarge instances Studio JupyterLab Apps running on ml.c5.12xlarge instances capacity | 0 count | Adjustable |
ml.t3.medium for cluster spot instance usage ml.t3.medium for cluster spot instance usage capacity | 0 count | Adjustable |
Number of ml.p4d.24xlarge instances in reserved capacity across training plans per Region Number of ml.p4d.24xlarge instances in reserved capacity across training plans per Region capacity | 0 count | Adjustable |
Rate of DescribeFlowDefinition requests Rate of DescribeFlowDefinition requests throughput | 5 count | Fixed |
ml.c5n.2xlarge for cluster spot instance usage ml.c5n.2xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.i3en.6xlarge for cluster spot instance usage ml.i3en.6xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.c6i.xlarge for training job usage ml.c6i.xlarge for training job usage general | 0 count | Adjustable |
ml.c7i.large for training job usage ml.c7i.large for training job usage general | 0 count | Adjustable |
Number of ml.p5.48xlarge instances in reserved capacity across training plans per Region Number of ml.p5.48xlarge instances in reserved capacity across training plans per Region capacity | 0 count | Adjustable |
ml.c7i.4xlarge for endpoint usage ml.c7i.4xlarge for endpoint usage networking | 0 count | Adjustable |
Rate of CreateEndpoint requests Rate of CreateEndpoint requests throughput | 1 count | Fixed |
ml.m7i.48xlarge for notebook instance usage ml.m7i.48xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.g5.8xlarge for notebook instance usage ml.g5.8xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c7i.24xlarge instances Studio CodeEditor Apps running on ml.c7i.24xlarge instances capacity | 0 count | Adjustable |
Total number of trials allowed in a single experiment, excluding those automatically created by SageMaker Total number of trials allowed in a single experiment, excluding those automatically created by SageMaker general | 300 count | Adjustable |
ml.g6e.2xlarge for training job usage ml.g6e.2xlarge for training job usage general | 0 count | Adjustable |
ml.r5.4xlarge for notebook instance usage ml.r5.4xlarge for notebook instance usage capacity | 0 count | Adjustable |
Rate of ListModels requests Rate of ListModels requests throughput | 2 count | Fixed |
ml.m6i.32xlarge for cluster spot instance usage ml.m6i.32xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.g4dn.12xlarge for training warm pool usage ml.g4dn.12xlarge for training warm pool usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.t3.medium instances Studio JupyterLab Apps running on ml.t3.medium instances capacity | 6 count | Adjustable |
ml.c4.2xlarge for training warm pool usage ml.c4.2xlarge for training warm pool usage general | 0 count | Adjustable |
ml.m4.16xlarge for notebook instance usage ml.m4.16xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.g6e.4xlarge for training job usage ml.g6e.4xlarge for training job usage general | 0 count | Adjustable |
ml.m4.2xlarge for processing job usage ml.m4.2xlarge for processing job usage general | 0 count | Adjustable |
ml.g6.24xlarge for endpoint usage ml.g6.24xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r5d.12xlarge for training warm pool usage ml.r5d.12xlarge for training warm pool usage general | 0 count | Adjustable |
ml.g5.48xlarge for processing job usage ml.g5.48xlarge for processing job usage general | 0 count | Adjustable |
ml.m7i.large for processing job usage ml.m7i.large for processing job usage general | 0 count | Adjustable |
ml.c5.4xlarge for training job usage ml.c5.4xlarge for training job usage general | 0 count | Adjustable |
ml.c5.2xlarge for transform job usage ml.c5.2xlarge for transform job usage general | 0 count | Adjustable |
ml.m6i.2xlarge for spot training job usage ml.m6i.2xlarge for spot training job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m7i.large instances Studio JupyterLab Apps running on ml.m7i.large instances capacity | 1 count | Adjustable |
Total number of trial components allowed in a single trial, excluding those automatically created by SageMaker Total number of trial components allowed in a single trial, excluding those automatically created by SageMaker general | 50 count | Adjustable |
ml.m5d.2xlarge for endpoint usage ml.m5d.2xlarge for endpoint usage networking | 0 count | Adjustable |
Rate of DeleteNotebookInstanceLifecycleConfig requests Rate of DeleteNotebookInstanceLifecycleConfig requests throughput | 1 count | Fixed |
Studio JupyterLab Apps running on ml.r7i.12xlarge instances Studio JupyterLab Apps running on ml.r7i.12xlarge instances capacity | 0 count | Adjustable |
ml.m7i.4xlarge for spot training job usage ml.m7i.4xlarge for spot training job usage general | 0 count | Adjustable |
ml.r5d.large for training warm pool usage ml.r5d.large for training warm pool usage general | 0 count | Adjustable |
ml.c7i.2xlarge for training warm pool usage ml.c7i.2xlarge for training warm pool usage general | 0 count | Adjustable |
ml.m5.24xlarge for processing job usage ml.m5.24xlarge for processing job usage general | 0 count | Adjustable |
ml.g4dn.16xlarge for training warm pool usage ml.g4dn.16xlarge for training warm pool usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r6id.4xlarge instances Studio CodeEditor Apps running on ml.r6id.4xlarge instances capacity | 0 count | Adjustable |
ml.c6gn.16xlarge for endpoint usage ml.c6gn.16xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c5n.2xlarge for training warm pool usage ml.c5n.2xlarge for training warm pool usage general | 0 count | Adjustable |
ml.m7i.16xlarge for endpoint usage ml.m7i.16xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m6i.2xlarge for training job usage ml.m6i.2xlarge for training job usage general | 0 count | Adjustable |
ml.r6i.2xlarge for cluster spot instance usage ml.r6i.2xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.m4.2xlarge for training warm pool usage ml.m4.2xlarge for training warm pool usage general | 0 count | Adjustable |
ml.c4.4xlarge for spot training job usage ml.c4.4xlarge for spot training job usage general | 0 count | Adjustable |
Maximum number of serverless endpoints Maximum number of serverless endpoints networking | 5 count | Adjustable |
ml.m6i.24xlarge for notebook instance usage ml.m6i.24xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.m7i.16xlarge for cluster spot instance usage ml.m7i.16xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.g6.8xlarge for training warm pool usage ml.g6.8xlarge for training warm pool usage general | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.r5.16xlarge instance Studio KernelGateway Apps running on ml.r5.16xlarge instance networking | 0 count | Adjustable |
Rate of UpdateWorkforce requests Rate of UpdateWorkforce requests throughput | 1 count | Fixed |
ml.c6gd.12xlarge for endpoint usage ml.c6gd.12xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r6i.16xlarge for notebook instance usage ml.r6i.16xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.trn1.32xlarge for training job usage ml.trn1.32xlarge for training job usage general | 0 count | Adjustable |
ml.c6i.xlarge for spot training job usage ml.c6i.xlarge for spot training job usage general | 0 count | Adjustable |
ml.c6i.24xlarge for spot training job usage ml.c6i.24xlarge for spot training job usage general | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.m5.12xlarge instance Studio KernelGateway Apps running on ml.m5.12xlarge instance networking | 0 count | Adjustable |
ml.g6e.12xlarge for cluster spot instance usage ml.g6e.12xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.p5.4xlarge for endpoint usage ml.p5.4xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r5.16xlarge for processing job usage ml.r5.16xlarge for processing job usage general | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.c5.24xlarge instance Studio KernelGateway Apps running on ml.c5.24xlarge instance networking | 0 count | Adjustable |
cluster-ml-r7i-12xlarge for cluster usage cluster-ml-r7i-12xlarge for cluster usage capacity | 0 count | Adjustable |
ml.m5d.12xlarge for endpoint usage ml.m5d.12xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c6i.2xlarge for notebook instance usage ml.c6i.2xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.r5d.24xlarge for processing job usage ml.r5d.24xlarge for processing job usage general | 0 count | Adjustable |
RSessionGateway Apps running on ml.m5d.8xlarge instance RSessionGateway Apps running on ml.m5d.8xlarge instance networking | 0 count | Adjustable |
ml.g5.4xlarge for training job usage ml.g5.4xlarge for training job usage general | 0 count | Adjustable |
ml.c4.2xlarge for processing job usage ml.c4.2xlarge for processing job usage general | 0 count | Adjustable |
ml.r7i.24xlarge for transform job usage ml.r7i.24xlarge for transform job usage general | 0 count | Adjustable |
ml.m7i.2xlarge for training warm pool usage ml.m7i.2xlarge for training warm pool usage general | 0 count | Adjustable |
Rate of DeleteWorkforce requests Rate of DeleteWorkforce requests throughput | 1 count | Fixed |
Rate of UpdateNotebookInstance requests Rate of UpdateNotebookInstance requests throughput | 1 count | Fixed |
Studio CodeEditor Apps running on ml.m7i.16xlarge instances Studio CodeEditor Apps running on ml.m7i.16xlarge instances capacity | 0 count | Adjustable |
ml.r5d.large for endpoint usage ml.r5d.large for endpoint usage networking | 0 count | Adjustable |
ml.g6e.12xlarge for endpoint usage ml.g6e.12xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m6i.2xlarge for processing job usage ml.m6i.2xlarge for processing job usage general | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.g5.24xlarge instance Studio KernelGateway Apps running on ml.g5.24xlarge instance networking | 0 count | Adjustable |
ml.r7i.12xlarge for notebook instance usage ml.r7i.12xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.i3en.xlarge for cluster usage ml.i3en.xlarge for cluster usage capacity | 0 count | Adjustable |
ml.c7i.xlarge for notebook instance usage ml.c7i.xlarge for notebook instance usage capacity | 1 count | Adjustable |
ml.m6id.16xlarge for notebook instance usage ml.m6id.16xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.m6i.4xlarge for spot training job usage ml.m6i.4xlarge for spot training job usage general | 0 count | Adjustable |
ml.c5d.4xlarge for endpoint usage ml.c5d.4xlarge for endpoint usage networking | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m5d.16xlarge instances Studio JupyterLab Apps running on ml.m5d.16xlarge instances capacity | 0 count | Adjustable |
Number of instances across all training jobs Number of instances across all training jobs capacity | 4 count | Adjustable |
Maximum subsampled dataset size AutoML job can be run on Maximum subsampled dataset size AutoML job can be run on storage | 5 count | Fixed |
ml.c7i.xlarge for transform job usage ml.c7i.xlarge for transform job usage general | 0 count | Adjustable |
Total number of notebook instances Total number of notebook instances capacity | 8 count | Adjustable |
ml.g5.xlarge for transform job usage ml.g5.xlarge for transform job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m7i.large instances Studio CodeEditor Apps running on ml.m7i.large instances capacity | 1 count | Adjustable |
ml.t2.2xlarge for endpoint usage ml.t2.2xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r5.2xlarge for training job usage ml.r5.2xlarge for training job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.p5.48xlarge instances Studio CodeEditor Apps running on ml.p5.48xlarge instances capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r5.large instances Studio JupyterLab Apps running on ml.r5.large instances capacity | 1 count | Adjustable |
TensorBoard Apps running on system instances TensorBoard Apps running on system instances capacity | 10 count | Adjustable |
Maximum number of instances per processing job Maximum number of instances per processing job capacity | 20 count | Adjustable |
ml.c7g.xlarge for endpoint usage ml.c7g.xlarge for endpoint usage networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.g5.8xlarge instances Studio CodeEditor Apps running on ml.g5.8xlarge instances capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.t3.large instances Studio JupyterLab Apps running on ml.t3.large instances capacity | 6 count | Adjustable |
ml.p6e-gb200.36xlarge for training warm pool usage ml.p6e-gb200.36xlarge for training warm pool usage general | 0 count | Adjustable |
Rate of CreateWorkteam requests Rate of CreateWorkteam requests throughput | 1 count | Fixed |
ml.c6i.4xlarge for endpoint usage ml.c6i.4xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g6e.2xlarge for cluster usage ml.g6e.2xlarge for cluster usage capacity | 0 count | Adjustable |
ml.r5.2xlarge for spot training job usage ml.r5.2xlarge for spot training job usage general | 0 count | Adjustable |
ml.m7i.4xlarge for cluster spot instance usage ml.m7i.4xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.g6e.24xlarge for cluster spot instance usage ml.g6e.24xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.m7i.48xlarge for transform job usage ml.m7i.48xlarge for transform job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c7i.2xlarge instances Studio JupyterLab Apps running on ml.c7i.2xlarge instances capacity | 1 count | Adjustable |
ml.m6g.4xlarge for endpoint usage ml.m6g.4xlarge for endpoint usage networking | 0 count | Adjustable |
Number of instances across active endpoints Number of instances across active endpoints networking | 4 count | Adjustable |
Studio JupyterLab Apps running on ml.c5.24xlarge instances Studio JupyterLab Apps running on ml.c5.24xlarge instances capacity | 0 count | Adjustable |
ml.r5.8xlarge for notebook instance usage ml.r5.8xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.g6.16xlarge for training job usage ml.g6.16xlarge for training job usage general | 0 count | Adjustable |
ml.r5.12xlarge for spot training job usage ml.r5.12xlarge for spot training job usage general | 0 count | Adjustable |
ml.c6gn.large for endpoint usage ml.c6gn.large for endpoint usage networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m5.16xlarge instances Studio CodeEditor Apps running on ml.m5.16xlarge instances capacity | 0 count | Adjustable |
ml.c6id.12xlarge for notebook instance usage ml.c6id.12xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.c7i.12xlarge for notebook instance usage ml.c7i.12xlarge for notebook instance usage capacity | 0 count | Adjustable |
Rate of ListMlflowApps requests Rate of ListMlflowApps requests throughput | 1 count | Fixed |
ml.m8g.xlarge for endpoint usage ml.m8g.xlarge for endpoint usage networking | 0 count | Adjustable |
ml.t3.2xlarge for training warm pool usage ml.t3.2xlarge for training warm pool usage general | 0 count | Adjustable |
ml.c6i.large for cluster spot instance usage ml.c6i.large for cluster spot instance usage capacity | 0 count | Adjustable |
ml.r6g.12xlarge for endpoint usage ml.r6g.12xlarge for endpoint usage networking | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r6i.2xlarge instances Studio JupyterLab Apps running on ml.r6i.2xlarge instances capacity | 0 count | Adjustable |
ml.m7i.4xlarge for training warm pool usage ml.m7i.4xlarge for training warm pool usage general | 0 count | Adjustable |
ml.g5.8xlarge for training warm pool usage ml.g5.8xlarge for training warm pool usage general | 0 count | Adjustable |
ml.p3.8xlarge for notebook instance usage ml.p3.8xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.m7i.8xlarge for cluster usage ml.m7i.8xlarge for cluster usage capacity | 0 count | Adjustable |
ml.r5d.2xlarge for endpoint usage ml.r5d.2xlarge for endpoint usage networking | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c5.9xlarge instances Studio JupyterLab Apps running on ml.c5.9xlarge instances capacity | 0 count | Adjustable |
ml.r7i.xlarge for cluster usage ml.r7i.xlarge for cluster usage capacity | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.r5.xlarge instance Studio KernelGateway Apps running on ml.r5.xlarge instance networking | 1 count | Adjustable |
ml.m4.10xlarge for endpoint usage ml.m4.10xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r7i.12xlarge for cluster spot instance usage ml.r7i.12xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.m4.10xlarge for notebook instance usage ml.m4.10xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.m5d.xlarge for endpoint usage ml.m5d.xlarge for endpoint usage networking | 0 count | Adjustable |
Maximum total concurrency that can be allocated across all serverless endpoints Maximum total concurrency that can be allocated across all serverless endpoints networking | 10 count | Adjustable |
ml.g6e.2xlarge for processing job usage ml.g6e.2xlarge for processing job usage general | 0 count | Adjustable |
ml.g4dn.2xlarge for training job usage ml.g4dn.2xlarge for training job usage general | 0 count | Adjustable |
ml.c7i.16xlarge for endpoint usage ml.c7i.16xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c4.xlarge for processing job usage ml.c4.xlarge for processing job usage general | 0 count | Adjustable |
ml.c6i.16xlarge for training job usage ml.c6i.16xlarge for training job usage general | 0 count | Adjustable |
ml.m7i.24xlarge for endpoint usage ml.m7i.24xlarge for endpoint usage networking | 0 count | Adjustable |
ml.p4d.24xlarge for spot training job usage ml.p4d.24xlarge for spot training job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.g6e.48xlarge instances Studio CodeEditor Apps running on ml.g6e.48xlarge instances capacity | 0 count | Adjustable |
ml.g6.12xlarge for endpoint usage ml.g6.12xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m6i.24xlarge for spot training job usage ml.m6i.24xlarge for spot training job usage general | 0 count | Adjustable |
Rate of ListFlowDefinitions requests Rate of ListFlowDefinitions requests throughput | 2 count | Fixed |
ml.r6i.xlarge for notebook instance usage ml.r6i.xlarge for notebook instance usage capacity | 1 count | Adjustable |
ml.r7i.2xlarge for endpoint usage ml.r7i.2xlarge for endpoint usage networking | 0 count | Adjustable |
Rate of StopTrainingJob requests Rate of StopTrainingJob requests throughput | 1 count | Fixed |
ml.g7e.4xlarge for cluster usage ml.g7e.4xlarge for cluster usage capacity | 0 count | Adjustable |
ml.m6i.8xlarge for spot training job usage ml.m6i.8xlarge for spot training job usage general | 0 count | Adjustable |
ml.g5.4xlarge for endpoint usage ml.g5.4xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r6i.large for cluster spot instance usage ml.r6i.large for cluster spot instance usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c5.4xlarge instances Studio CodeEditor Apps running on ml.c5.4xlarge instances capacity | 0 count | Adjustable |
ml.c4.4xlarge for transform job usage ml.c4.4xlarge for transform job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m7i.2xlarge instances Studio CodeEditor Apps running on ml.m7i.2xlarge instances capacity | 1 count | Adjustable |
ml.m6i.32xlarge for training warm pool usage ml.m6i.32xlarge for training warm pool usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c5.2xlarge instances Studio JupyterLab Apps running on ml.c5.2xlarge instances capacity | 1 count | Adjustable |
ml.m6g.2xlarge for endpoint usage ml.m6g.2xlarge for endpoint usage networking | 0 count | Adjustable |
ml.p5.48xlarge for endpoint usage ml.p5.48xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c6i.16xlarge for cluster usage ml.c6i.16xlarge for cluster usage capacity | 0 count | Adjustable |
Rate of ListSubscribedWorkteams requests Rate of ListSubscribedWorkteams requests throughput | 2 count | Fixed |
ml.c6g.large for endpoint usage ml.c6g.large for endpoint usage networking | 0 count | Adjustable |
ml.r7i.xlarge for notebook instance usage ml.r7i.xlarge for notebook instance usage capacity | 1 count | Adjustable |
Rate of DescribeTrainingJob requests Rate of DescribeTrainingJob requests throughput | 5 count | Fixed |
Studio JupyterLab Apps running on ml.r5.24xlarge instances Studio JupyterLab Apps running on ml.r5.24xlarge instances capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c6i.xlarge instances Studio JupyterLab Apps running on ml.c6i.xlarge instances capacity | 1 count | Adjustable |
ml.c6i.xlarge for transform job usage ml.c6i.xlarge for transform job usage general | 0 count | Adjustable |
RSessionGateway Apps running on ml.g4dn.16xlarge instance RSessionGateway Apps running on ml.g4dn.16xlarge instance networking | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.g5.xlarge instances Studio JupyterLab Apps running on ml.g5.xlarge instances capacity | 0 count | Adjustable |
ml.g6.xlarge for cluster spot instance usage ml.g6.xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.g5.12xlarge instances Studio CodeEditor Apps running on ml.g5.12xlarge instances capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m6i.16xlarge instances Studio JupyterLab Apps running on ml.m6i.16xlarge instances capacity | 0 count | Adjustable |
ml.m7i.xlarge for training warm pool usage ml.m7i.xlarge for training warm pool usage general | 0 count | Adjustable |
ml.m6gd.2xlarge for endpoint usage ml.m6gd.2xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c6i.16xlarge for transform job usage ml.c6i.16xlarge for transform job usage general | 0 count | Adjustable |
ml.p5.48xlarge for training warm pool usage ml.p5.48xlarge for training warm pool usage general | 0 count | Adjustable |
ml.r7i.8xlarge for cluster usage ml.r7i.8xlarge for cluster usage capacity | 0 count | Adjustable |
ml.c6i.8xlarge for cluster spot instance usage ml.c6i.8xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.r5.large for training warm pool usage ml.r5.large for training warm pool usage general | 0 count | Adjustable |
RSessionGateway Apps running on ml.m5d.large instance RSessionGateway Apps running on ml.m5d.large instance networking | 1 count | Adjustable |
Studio Jupyter Apps running on system instances Studio Jupyter Apps running on system instances capacity | 10 count | Adjustable |
ml.g6e.12xlarge for processing job usage ml.g6e.12xlarge for processing job usage general | 0 count | Adjustable |
ml.c7i.large for notebook instance usage ml.c7i.large for notebook instance usage capacity | 1 count | Adjustable |
ml.t3.2xlarge for cluster spot instance usage ml.t3.2xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Size of EBS volume for a training job instance Size of EBS volume for a training job instance storage | 1,024 count | Adjustable |
ml.m7i.large for notebook instance usage ml.m7i.large for notebook instance usage capacity | 1 count | Adjustable |
Studio KernelGateway Apps running on ml.g4dn.xlarge instance Studio KernelGateway Apps running on ml.g4dn.xlarge instance networking | 0 count | Adjustable |
ml.inf2.xlarge for transform job usage ml.inf2.xlarge for transform job usage general | 0 count | Adjustable |
Number of elastic inference accelerators across active endpoints Number of elastic inference accelerators across active endpoints networking | 0 count | Adjustable |
ml.r7i.24xlarge for spot training job usage ml.r7i.24xlarge for spot training job usage general | 0 count | Adjustable |
ml.r7i.2xlarge for spot training job usage ml.r7i.2xlarge for spot training job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.g5.48xlarge instances Studio JupyterLab Apps running on ml.g5.48xlarge instances capacity | 0 count | Adjustable |
ml.m5.4xlarge for endpoint usage ml.m5.4xlarge for endpoint usage networking | 0 count | Adjustable |
RSessionGateway Apps running on ml.g4dn.4xlarge instance RSessionGateway Apps running on ml.g4dn.4xlarge instance networking | 0 count | Adjustable |
ml.g4dn.4xlarge for training warm pool usage ml.g4dn.4xlarge for training warm pool usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c7i.12xlarge instances Studio JupyterLab Apps running on ml.c7i.12xlarge instances capacity | 0 count | Adjustable |
ml.c6gn.8xlarge for endpoint usage ml.c6gn.8xlarge for endpoint usage networking | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.p3.2xlarge instances Studio JupyterLab Apps running on ml.p3.2xlarge instances capacity | 0 count | Adjustable |
ml.c5.9xlarge for transform job usage ml.c5.9xlarge for transform job usage general | 0 count | Adjustable |
ml.m7i.4xlarge for transform job usage ml.m7i.4xlarge for transform job usage general | 0 count | Adjustable |
ml.m5.24xlarge for notebook instance usage ml.m5.24xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.c7i.2xlarge for training job usage ml.c7i.2xlarge for training job usage general | 0 count | Adjustable |
ml.trn1.32xlarge for cluster spot instance usage ml.trn1.32xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Maximum number of model card versions allowed per account. Maximum number of model card versions allowed per account. general | 100 count | Adjustable |
ml.t3.medium for cluster usage ml.t3.medium for cluster usage capacity | 0 count | Adjustable |
ml.r7i.16xlarge for processing job usage ml.r7i.16xlarge for processing job usage general | 0 count | Adjustable |
ml.m7i.4xlarge for notebook instance usage ml.m7i.4xlarge for notebook instance usage capacity | 0 count | Adjustable |
Maximum number of A2I flow definitions Maximum number of A2I flow definitions general | 100 count | Adjustable |
ml.g4dn.16xlarge for processing job usage ml.g4dn.16xlarge for processing job usage general | 0 count | Adjustable |
ml.g4dn.xlarge for endpoint usage ml.g4dn.xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m7i.2xlarge for notebook instance usage ml.m7i.2xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.m4.2xlarge for training job usage ml.m4.2xlarge for training job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c7i.xlarge instances Studio CodeEditor Apps running on ml.c7i.xlarge instances capacity | 1 count | Adjustable |
ml.m7i.16xlarge for processing job usage ml.m7i.16xlarge for processing job usage general | 0 count | Adjustable |
ml.g6.8xlarge for cluster spot instance usage ml.g6.8xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.t3.xlarge for training job usage ml.t3.xlarge for training job usage general | 0 count | Adjustable |
ml.trn1.2xlarge for training job usage ml.trn1.2xlarge for training job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m6i.2xlarge instances Studio JupyterLab Apps running on ml.m6i.2xlarge instances capacity | 1 count | Adjustable |
Studio CodeEditor Apps running on ml.g6.2xlarge instances Studio CodeEditor Apps running on ml.g6.2xlarge instances capacity | 0 count | Adjustable |
RSessionGateway Apps running on ml.m5.large instance RSessionGateway Apps running on ml.m5.large instance networking | 1 count | Adjustable |
ml.r7gd.medium for endpoint usage ml.r7gd.medium for endpoint usage networking | 0 count | Adjustable |
ml.p4d.24xlarge for cluster spot instance usage ml.p4d.24xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.m5.12xlarge for training job usage ml.m5.12xlarge for training job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m6i.xlarge instances Studio JupyterLab Apps running on ml.m6i.xlarge instances capacity | 1 count | Adjustable |
ml.r5d.16xlarge for processing job usage ml.r5d.16xlarge for processing job usage general | 0 count | Adjustable |
ml.g6.16xlarge for notebook instance usage ml.g6.16xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.m5.xlarge for spot training job usage ml.m5.xlarge for spot training job usage general | 4 count | Adjustable |
ml.m4.16xlarge for training job usage ml.m4.16xlarge for training job usage general | 0 count | Adjustable |
Rate of CreateHumanTaskUi requests Rate of CreateHumanTaskUi requests throughput | 1 count | Fixed |
ml.r5d.2xlarge for training warm pool usage ml.r5d.2xlarge for training warm pool usage general | 0 count | Adjustable |
ml.c6i.4xlarge for cluster usage ml.c6i.4xlarge for cluster usage capacity | 0 count | Adjustable |
ml.g6.24xlarge for cluster usage ml.g6.24xlarge for cluster usage capacity | 0 count | Adjustable |
ml.g7e.4xlarge for training warm pool usage ml.g7e.4xlarge for training warm pool usage general | 0 count | Adjustable |
ml.m6i.32xlarge for transform job usage ml.m6i.32xlarge for transform job usage general | 0 count | Adjustable |
Maximum number of parameters allowed per pipeline Maximum number of parameters allowed per pipeline general | 200 count | Fixed |
ml.m4.xlarge for processing job usage ml.m4.xlarge for processing job usage general | 0 count | Adjustable |
ml.r5.xlarge for notebook instance usage ml.r5.xlarge for notebook instance usage capacity | 1 count | Adjustable |
ml.t3.large for training job usage ml.t3.large for training job usage general | 0 count | Adjustable |
ml.g5.xlarge for training job usage ml.g5.xlarge for training job usage general | 0 count | Adjustable |
ml.g4dn.2xlarge for spot training job usage ml.g4dn.2xlarge for spot training job usage general | 0 count | Adjustable |
ml.g5.16xlarge for notebook instance usage ml.g5.16xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.m5.24xlarge for transform job usage ml.m5.24xlarge for transform job usage general | 0 count | Adjustable |
Number of instances across all processing jobs Number of instances across all processing jobs capacity | 4 count | Adjustable |
ml.m6id.large for notebook instance usage ml.m6id.large for notebook instance usage capacity | 1 count | Adjustable |
ml.p5e.48xlarge for training job usage ml.p5e.48xlarge for training job usage general | 0 count | Adjustable |
ml.m4.10xlarge for transform job usage ml.m4.10xlarge for transform job usage general | 0 count | Adjustable |
ml.m5.2xlarge for training warm pool usage ml.m5.2xlarge for training warm pool usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m7i.8xlarge instances Studio JupyterLab Apps running on ml.m7i.8xlarge instances capacity | 0 count | Adjustable |
ml.r7i.large for transform job usage ml.r7i.large for transform job usage general | 0 count | Adjustable |
ml.g4dn.4xlarge for notebook instance usage ml.g4dn.4xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.c7i.24xlarge for spot training job usage ml.c7i.24xlarge for spot training job usage general | 0 count | Adjustable |
SageMaker Profiler Apps running on system instances SageMaker Profiler Apps running on system instances storage | 5 count | Adjustable |
Rate of DescribeEndpointConfig requests Rate of DescribeEndpointConfig requests throughput | 5 count | Fixed |
ml.p6-b200.48xlarge for spot training job usage ml.p6-b200.48xlarge for spot training job usage general | 0 count | Adjustable |
ml.c6i.xlarge for endpoint usage ml.c6i.xlarge for endpoint usage networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m7i.48xlarge instances Studio CodeEditor Apps running on ml.m7i.48xlarge instances capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m5.24xlarge instances Studio CodeEditor Apps running on ml.m5.24xlarge instances capacity | 0 count | Adjustable |
ml.t3.2xlarge for cluster usage ml.t3.2xlarge for cluster usage capacity | 0 count | Adjustable |
ml.r5.12xlarge for processing job usage ml.r5.12xlarge for processing job usage general | 0 count | Adjustable |
ml.r5.16xlarge for training job usage ml.r5.16xlarge for training job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c6id.12xlarge instances Studio JupyterLab Apps running on ml.c6id.12xlarge instances capacity | 0 count | Adjustable |
ml.p5en.48xlarge for cluster usage ml.p5en.48xlarge for cluster usage capacity | 0 count | Adjustable |
ml.g6.4xlarge for training warm pool usage ml.g6.4xlarge for training warm pool usage general | 0 count | Adjustable |
ml.g5.8xlarge for cluster spot instance usage ml.g5.8xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Total Monitoring Schedules Total Monitoring Schedules general | 10 count | Fixed |
ml.g5.4xlarge for cluster usage ml.g5.4xlarge for cluster usage capacity | 0 count | Adjustable |
ml.t2.xlarge for notebook instance usage ml.t2.xlarge for notebook instance usage capacity | 6 count | Adjustable |
ml.m6g.16xlarge for endpoint usage ml.m6g.16xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m5.xlarge for training warm pool usage ml.m5.xlarge for training warm pool usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c7i.16xlarge instances Studio JupyterLab Apps running on ml.c7i.16xlarge instances capacity | 0 count | Adjustable |
ml.g7e.24xlarge for endpoint usage ml.g7e.24xlarge for endpoint usage networking | 0 count | Adjustable |
ml.p3.2xlarge for notebook instance usage ml.p3.2xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.g6e.4xlarge for training warm pool usage ml.g6e.4xlarge for training warm pool usage general | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.g5.2xlarge instance Studio KernelGateway Apps running on ml.g5.2xlarge instance networking | 0 count | Adjustable |
ml.c7i.12xlarge for spot training job usage ml.c7i.12xlarge for spot training job usage general | 0 count | Adjustable |
ml.c6i.8xlarge for processing job usage ml.c6i.8xlarge for processing job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c7i.8xlarge instances Studio JupyterLab Apps running on ml.c7i.8xlarge instances capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c6id.2xlarge instances Studio JupyterLab Apps running on ml.c6id.2xlarge instances capacity | 1 count | Adjustable |
RSessionGateway Apps running on ml.m5d.4xlarge instance RSessionGateway Apps running on ml.m5d.4xlarge instance networking | 1 count | Adjustable |
Studio JupyterLab Apps running on ml.g6.2xlarge instances Studio JupyterLab Apps running on ml.g6.2xlarge instances capacity | 0 count | Adjustable |
Maximum number of hub contents per private hub Maximum number of hub contents per private hub general | 10,000 count | Adjustable |
Studio JupyterLab Apps running on ml.r7i.48xlarge instances Studio JupyterLab Apps running on ml.r7i.48xlarge instances capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c5.18xlarge instances Studio CodeEditor Apps running on ml.c5.18xlarge instances capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.g6e.8xlarge instances Studio CodeEditor Apps running on ml.g6e.8xlarge instances capacity | 0 count | Adjustable |
Rate of ListStudioLifecycleConfigs requests Rate of ListStudioLifecycleConfigs requests throughput | 2 count | Fixed |
ml.r7gd.12xlarge for endpoint usage ml.r7gd.12xlarge for endpoint usage networking | 0 count | Adjustable |
Rate of ListMonitoringAlertHistory requests Rate of ListMonitoringAlertHistory requests throughput | 2 count | Fixed |
ml.r7i.24xlarge for training warm pool usage ml.r7i.24xlarge for training warm pool usage general | 0 count | Adjustable |
ml.r5.16xlarge for spot training job usage ml.r5.16xlarge for spot training job usage general | 0 count | Adjustable |
ml.r6gd.2xlarge for endpoint usage ml.r6gd.2xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c6i.8xlarge for notebook instance usage ml.c6i.8xlarge for notebook instance usage capacity | 0 count | Adjustable |
RStudioServerPro Apps running on ml.c5.4xlarge instances RStudioServerPro Apps running on ml.c5.4xlarge instances capacity | 0 count | Adjustable |
ml.c8g.8xlarge for endpoint usage ml.c8g.8xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c6i.8xlarge for endpoint usage ml.c6i.8xlarge for endpoint usage networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m6id.32xlarge instances Studio CodeEditor Apps running on ml.m6id.32xlarge instances capacity | 0 count | Adjustable |
ml.m5.12xlarge for processing job usage ml.m5.12xlarge for processing job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m6id.24xlarge instances Studio JupyterLab Apps running on ml.m6id.24xlarge instances capacity | 0 count | Adjustable |
ml.g6.16xlarge for cluster spot instance usage ml.g6.16xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.g4dn.8xlarge instance Studio KernelGateway Apps running on ml.g4dn.8xlarge instance networking | 0 count | Adjustable |
ml.g5.24xlarge for endpoint usage ml.g5.24xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c5.18xlarge for transform job usage ml.c5.18xlarge for transform job usage general | 0 count | Adjustable |
ml.r5d.12xlarge for endpoint usage ml.r5d.12xlarge for endpoint usage networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m5d.24xlarge instances Studio CodeEditor Apps running on ml.m5d.24xlarge instances capacity | 0 count | Adjustable |
ml.c6gn.12xlarge for endpoint usage ml.c6gn.12xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g6.12xlarge for cluster usage ml.g6.12xlarge for cluster usage capacity | 0 count | Adjustable |
Small-sized MLflow Tracking Server usage Small-sized MLflow Tracking Server usage storage | 5 count | Adjustable |
ml.m7i.24xlarge for cluster usage ml.m7i.24xlarge for cluster usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m5.xlarge instances Studio CodeEditor Apps running on ml.m5.xlarge instances capacity | 1 count | Adjustable |
Studio CodeEditor Apps running on ml.c6i.8xlarge instances Studio CodeEditor Apps running on ml.c6i.8xlarge instances capacity | 0 count | Adjustable |
ml.g6.24xlarge for notebook instance usage ml.g6.24xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.c7i.48xlarge for training job usage ml.c7i.48xlarge for training job usage general | 0 count | Adjustable |
Number of ml.p6e-gb200.36xlarge instances in reserved capacity across training plans per Region Number of ml.p6e-gb200.36xlarge instances in reserved capacity across training plans per Region capacity | 0 count | Adjustable |
Maximum number of concurrent model customization serverless jobs per Region Maximum number of concurrent model customization serverless jobs per Region compute | 0 count | Adjustable |
ml.c6id.24xlarge for notebook instance usage ml.c6id.24xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.g5.2xlarge instances Studio CodeEditor Apps running on ml.g5.2xlarge instances capacity | 0 count | Adjustable |
ml.m5.24xlarge for endpoint usage ml.m5.24xlarge for endpoint usage networking | 0 count | Adjustable |
ml.trn1.32xlarge for spot training job usage ml.trn1.32xlarge for spot training job usage general | 0 count | Adjustable |
ml.m8g.48xlarge for endpoint usage ml.m8g.48xlarge for endpoint usage networking | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r6id.large instances Studio JupyterLab Apps running on ml.r6id.large instances capacity | 1 count | Adjustable |
Studio CodeEditor Apps running on ml.g5.xlarge instances Studio CodeEditor Apps running on ml.g5.xlarge instances capacity | 0 count | Adjustable |
ml.c6i.16xlarge for cluster spot instance usage ml.c6i.16xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.r6i.32xlarge for notebook instance usage ml.r6i.32xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.g5.4xlarge instances Studio JupyterLab Apps running on ml.g5.4xlarge instances capacity | 0 count | Adjustable |
ml.i3en.6xlarge for cluster usage ml.i3en.6xlarge for cluster usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c5.24xlarge instances Studio CodeEditor Apps running on ml.c5.24xlarge instances capacity | 0 count | Adjustable |
ml.c5d.2xlarge for endpoint usage ml.c5d.2xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g4dn.xlarge for training warm pool usage ml.g4dn.xlarge for training warm pool usage general | 0 count | Adjustable |
ml.r5.4xlarge for training warm pool usage ml.r5.4xlarge for training warm pool usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r7i.large instances Studio CodeEditor Apps running on ml.r7i.large instances capacity | 1 count | Adjustable |
Rate of CreateTrainingJob requests Rate of CreateTrainingJob requests throughput | 1 count | Fixed |
Studio JupyterLab Apps running on ml.r6i.24xlarge instances Studio JupyterLab Apps running on ml.r6i.24xlarge instances capacity | 0 count | Adjustable |
ml.g6e.xlarge for spot training job usage ml.g6e.xlarge for spot training job usage general | 0 count | Adjustable |
ml.c8g.12xlarge for endpoint usage ml.c8g.12xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g6.12xlarge for spot training job usage ml.g6.12xlarge for spot training job usage general | 0 count | Adjustable |
ml.c5n.large for cluster usage ml.c5n.large for cluster usage capacity | 0 count | Adjustable |
ml.r8g.medium for endpoint usage ml.r8g.medium for endpoint usage networking | 0 count | Adjustable |
ml.inf1.24xlarge for notebook instance usage ml.inf1.24xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.m5.24xlarge instance Studio KernelGateway Apps running on ml.m5.24xlarge instance networking | 0 count | Adjustable |
ml.c6i.4xlarge for training warm pool usage ml.c6i.4xlarge for training warm pool usage general | 0 count | Adjustable |
RSessionGateway Apps running on ml.r5.12xlarge instance RSessionGateway Apps running on ml.r5.12xlarge instance networking | 0 count | Adjustable |
ml.m6gd.8xlarge for endpoint usage ml.m6gd.8xlarge for endpoint usage networking | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m5.2xlarge instances Studio JupyterLab Apps running on ml.m5.2xlarge instances capacity | 1 count | Adjustable |
Rate of DescribeStudioLifecycleConfig requests Rate of DescribeStudioLifecycleConfig requests throughput | 5 count | Fixed |
Studio JupyterLab Apps running on ml.m5.8xlarge instances Studio JupyterLab Apps running on ml.m5.8xlarge instances capacity | 0 count | Adjustable |
ml.g6.12xlarge for training warm pool usage ml.g6.12xlarge for training warm pool usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c7i.8xlarge instances Studio CodeEditor Apps running on ml.c7i.8xlarge instances capacity | 0 count | Adjustable |
ml.r5.4xlarge for processing job usage ml.r5.4xlarge for processing job usage general | 0 count | Adjustable |
ml.c6i.16xlarge for training warm pool usage ml.c6i.16xlarge for training warm pool usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m6id.xlarge instances Studio JupyterLab Apps running on ml.m6id.xlarge instances capacity | 1 count | Adjustable |
ml.g6e.16xlarge for processing job usage ml.g6e.16xlarge for processing job usage general | 0 count | Adjustable |
ml.c7i.xlarge for training job usage ml.c7i.xlarge for training job usage general | 0 count | Adjustable |
ml.c6g.8xlarge for endpoint usage ml.c6g.8xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g6.2xlarge for cluster spot instance usage ml.g6.2xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.m5.24xlarge for spot training job usage ml.m5.24xlarge for spot training job usage general | 0 count | Adjustable |
ml.g6e.24xlarge for endpoint usage ml.g6e.24xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g6e.24xlarge for processing job usage ml.g6e.24xlarge for processing job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m7i.4xlarge instances Studio JupyterLab Apps running on ml.m7i.4xlarge instances capacity | 0 count | Adjustable |
ml.g4dn.12xlarge for spot training job usage ml.g4dn.12xlarge for spot training job usage general | 0 count | Adjustable |
ml.g5.4xlarge for cluster spot instance usage ml.g5.4xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.c7i.2xlarge for processing job usage ml.c7i.2xlarge for processing job usage general | 0 count | Adjustable |
ml.g6.2xlarge for endpoint usage ml.g6.2xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g4dn.8xlarge for endpoint usage ml.g4dn.8xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g4dn.8xlarge for training job usage ml.g4dn.8xlarge for training job usage general | 0 count | Adjustable |
ml.r5d.16xlarge for spot training job usage ml.r5d.16xlarge for spot training job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m5.16xlarge instances Studio JupyterLab Apps running on ml.m5.16xlarge instances capacity | 0 count | Adjustable |
ml.c6i.24xlarge for notebook instance usage ml.c6i.24xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c6i.32xlarge instances Studio CodeEditor Apps running on ml.c6i.32xlarge instances capacity | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.g5.16xlarge instance Studio KernelGateway Apps running on ml.g5.16xlarge instance networking | 0 count | Adjustable |
RSessionGateway Apps running on ml.c5.18xlarge instance RSessionGateway Apps running on ml.c5.18xlarge instance networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m7i.12xlarge instances Studio CodeEditor Apps running on ml.m7i.12xlarge instances capacity | 0 count | Adjustable |
ml.g6e.4xlarge for spot training job usage ml.g6e.4xlarge for spot training job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m6id.4xlarge instances Studio CodeEditor Apps running on ml.m6id.4xlarge instances capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r5.large instances Studio CodeEditor Apps running on ml.r5.large instances capacity | 1 count | Adjustable |
ml.m5.large for processing job usage ml.m5.large for processing job usage general | 0 count | Adjustable |
ml.r5.8xlarge for processing job usage ml.r5.8xlarge for processing job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.p3.2xlarge instances Studio CodeEditor Apps running on ml.p3.2xlarge instances capacity | 0 count | Adjustable |
ml.r6g.4xlarge for endpoint usage ml.r6g.4xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r5.xlarge for spot training job usage ml.r5.xlarge for spot training job usage general | 0 count | Adjustable |
ml.r5d.12xlarge for training job usage ml.r5d.12xlarge for training job usage general | 0 count | Adjustable |
ml.inf1.6xlarge for endpoint usage ml.inf1.6xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m7i.8xlarge for transform job usage ml.m7i.8xlarge for transform job usage general | 0 count | Adjustable |
ml.m6i.12xlarge for spot training job usage ml.m6i.12xlarge for spot training job usage general | 0 count | Adjustable |
ml.m6i.8xlarge for transform job usage ml.m6i.8xlarge for transform job usage general | 0 count | Adjustable |
ml.m4.2xlarge for spot training job usage ml.m4.2xlarge for spot training job usage general | 4 count | Adjustable |
ml.g6e.2xlarge for endpoint usage ml.g6e.2xlarge for endpoint usage networking | 0 count | Adjustable |
ml.p6e-gb200.36xlarge for cluster spot instance usage ml.p6e-gb200.36xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.trn1.2xlarge for spot training job usage ml.trn1.2xlarge for spot training job usage general | 0 count | Adjustable |
ml.g5.12xlarge for processing job usage ml.g5.12xlarge for processing job usage general | 0 count | Adjustable |
ml.g7e.48xlarge for endpoint usage ml.g7e.48xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g6e.4xlarge for cluster spot instance usage ml.g6e.4xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.c7g.2xlarge for endpoint usage ml.c7g.2xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r5d.8xlarge for training job usage ml.r5d.8xlarge for training job usage general | 0 count | Adjustable |
ml.m8g.2xlarge for endpoint usage ml.m8g.2xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g6.48xlarge for spot training job usage ml.g6.48xlarge for spot training job usage general | 0 count | Adjustable |
ml.m7i.8xlarge for training warm pool usage ml.m7i.8xlarge for training warm pool usage general | 0 count | Adjustable |
ml.c8g.2xlarge for endpoint usage ml.c8g.2xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r6i.large for transform job usage ml.r6i.large for transform job usage general | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.m5d.large instance Studio KernelGateway Apps running on ml.m5d.large instance networking | 1 count | Adjustable |
ml.r7i.4xlarge for training job usage ml.r7i.4xlarge for training job usage general | 0 count | Adjustable |
ml.m7i.48xlarge for training job usage ml.m7i.48xlarge for training job usage general | 0 count | Adjustable |
ml.m7i.4xlarge for cluster usage ml.m7i.4xlarge for cluster usage capacity | 0 count | Adjustable |
ml.m6i.32xlarge for notebook instance usage ml.m6i.32xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r7i.24xlarge instances Studio JupyterLab Apps running on ml.r7i.24xlarge instances capacity | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.t3.2xlarge instance Studio KernelGateway Apps running on ml.t3.2xlarge instance networking | 0 count | Adjustable |
Rate of UpdateWorkteam requests Rate of UpdateWorkteam requests throughput | 1 count | Fixed |
ml.g5.8xlarge for endpoint usage ml.g5.8xlarge for endpoint usage networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r6i.24xlarge instances Studio CodeEditor Apps running on ml.r6i.24xlarge instances capacity | 0 count | Adjustable |
ml.p4d.24xlarge for training warm pool usage ml.p4d.24xlarge for training warm pool usage general | 0 count | Adjustable |
ml.m6i.large for cluster usage ml.m6i.large for cluster usage capacity | 0 count | Adjustable |
ml.g5.2xlarge for cluster usage ml.g5.2xlarge for cluster usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.g6.12xlarge instances Studio CodeEditor Apps running on ml.g6.12xlarge instances capacity | 0 count | Adjustable |
Maximum number of parallel AI recommendation jobs Maximum number of parallel AI recommendation jobs general | 2 count | Adjustable |
ml.m6i.12xlarge for training job usage ml.m6i.12xlarge for training job usage general | 0 count | Adjustable |
ml.m7i.8xlarge for notebook instance usage ml.m7i.8xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.t2.medium for endpoint usage ml.t2.medium for endpoint usage networking | 2 count | Adjustable |
ml.r7gd.xlarge for endpoint usage ml.r7gd.xlarge for endpoint usage networking | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.g6e.48xlarge instances Studio JupyterLab Apps running on ml.g6e.48xlarge instances capacity | 0 count | Adjustable |
ml.r5.xlarge for training warm pool usage ml.r5.xlarge for training warm pool usage general | 0 count | Adjustable |
ml.inf2.xlarge for endpoint usage ml.inf2.xlarge for endpoint usage networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r6id.16xlarge instances Studio CodeEditor Apps running on ml.r6id.16xlarge instances capacity | 0 count | Adjustable |
ml.g6e.48xlarge for endpoint usage ml.g6e.48xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c7i.8xlarge for transform job usage ml.c7i.8xlarge for transform job usage general | 0 count | Adjustable |
ml.trn1.2xlarge for transform job usage ml.trn1.2xlarge for transform job usage general | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.m5.large instance Studio KernelGateway Apps running on ml.m5.large instance networking | 1 count | Adjustable |
ml.c6i.8xlarge for spot training job usage ml.c6i.8xlarge for spot training job usage general | 0 count | Adjustable |
ml.m6i.4xlarge for cluster spot instance usage ml.m6i.4xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.g4dn.4xlarge instances Studio CodeEditor Apps running on ml.g4dn.4xlarge instances capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m6i.8xlarge instances Studio JupyterLab Apps running on ml.m6i.8xlarge instances capacity | 0 count | Adjustable |
ml.g6e.16xlarge for cluster spot instance usage ml.g6e.16xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.g6e.48xlarge for training job usage ml.g6e.48xlarge for training job usage general | 0 count | Adjustable |
ml.inf1.xlarge for notebook instance usage ml.inf1.xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c5.9xlarge instances Studio CodeEditor Apps running on ml.c5.9xlarge instances capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.g5.24xlarge instances Studio CodeEditor Apps running on ml.g5.24xlarge instances capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.g6e.16xlarge instances Studio CodeEditor Apps running on ml.g6e.16xlarge instances capacity | 0 count | Adjustable |
ml.g6e.16xlarge for spot training job usage ml.g6e.16xlarge for spot training job usage general | 0 count | Adjustable |
ml.m6id.4xlarge for notebook instance usage ml.m6id.4xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.r6i.xlarge for cluster usage ml.r6i.xlarge for cluster usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.p3dn.24xlarge instances Studio CodeEditor Apps running on ml.p3dn.24xlarge instances capacity | 0 count | Adjustable |
ml.g5.24xlarge for transform job usage ml.g5.24xlarge for transform job usage general | 0 count | Adjustable |
ml.g6.24xlarge for training warm pool usage ml.g6.24xlarge for training warm pool usage general | 0 count | Adjustable |
ml.g4dn.16xlarge for transform job usage ml.g4dn.16xlarge for transform job usage general | 0 count | Adjustable |
ml.g6e.xlarge for processing job usage ml.g6e.xlarge for processing job usage general | 0 count | Adjustable |
ml.i3en.large for cluster usage ml.i3en.large for cluster usage capacity | 0 count | Adjustable |
ml.c7i.16xlarge for spot training job usage ml.c7i.16xlarge for spot training job usage general | 0 count | Adjustable |
ml.c4.8xlarge for training job usage ml.c4.8xlarge for training job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m6id.2xlarge instances Studio JupyterLab Apps running on ml.m6id.2xlarge instances capacity | 1 count | Adjustable |
ml.g7e.48xlarge for cluster usage ml.g7e.48xlarge for cluster usage capacity | 0 count | Adjustable |
ml.m6i.24xlarge for cluster usage ml.m6i.24xlarge for cluster usage capacity | 0 count | Adjustable |
ml.inf2.xlarge for notebook instance usage ml.inf2.xlarge for notebook instance usage capacity | 0 count | Adjustable |
Number of ml.p5e.48xlarge instances in reserved capacity across training plans per Region Number of ml.p5e.48xlarge instances in reserved capacity across training plans per Region capacity | 0 count | Adjustable |
Rate of CreateNotebookInstanceLifecycleConfig requests Rate of CreateNotebookInstanceLifecycleConfig requests throughput | 1 count | Fixed |
ml.g7e.2xlarge for cluster usage ml.g7e.2xlarge for cluster usage capacity | 0 count | Adjustable |
ml.c5d.9xlarge for notebook instance usage ml.c5d.9xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.g6.48xlarge for notebook instance usage ml.g6.48xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.g7e.2xlarge for spot training job usage ml.g7e.2xlarge for spot training job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r5.16xlarge instances Studio CodeEditor Apps running on ml.r5.16xlarge instances capacity | 0 count | Adjustable |
ml.c7i.48xlarge for transform job usage ml.c7i.48xlarge for transform job usage general | 0 count | Adjustable |
ml.m7i.24xlarge for processing job usage ml.m7i.24xlarge for processing job usage general | 0 count | Adjustable |
ml.c5.xlarge for training job usage ml.c5.xlarge for training job usage general | 0 count | Adjustable |
ml.r5d.4xlarge for processing job usage ml.r5d.4xlarge for processing job usage general | 0 count | Adjustable |
Rate of ListWorkforces requests Rate of ListWorkforces requests throughput | 2 count | Fixed |
ml.r7i.48xlarge for cluster spot instance usage ml.r7i.48xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c5.xlarge instances Studio JupyterLab Apps running on ml.c5.xlarge instances capacity | 1 count | Adjustable |
ml.c6i.24xlarge for processing job usage ml.c6i.24xlarge for processing job usage general | 0 count | Adjustable |
ml.r7i.8xlarge for spot training job usage ml.r7i.8xlarge for spot training job usage general | 0 count | Adjustable |
ml.m4.10xlarge for processing job usage ml.m4.10xlarge for processing job usage general | 0 count | Adjustable |
ml.m6i.16xlarge for cluster spot instance usage ml.m6i.16xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.p6-b300.48xlarge for cluster usage ml.p6-b300.48xlarge for cluster usage capacity | 0 count | Adjustable |
ml.c7i.4xlarge for training warm pool usage ml.c7i.4xlarge for training warm pool usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m6id.12xlarge instances Studio JupyterLab Apps running on ml.m6id.12xlarge instances capacity | 0 count | Adjustable |
ml.r7i.16xlarge for notebook instance usage ml.r7i.16xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.c7i.24xlarge for endpoint usage ml.c7i.24xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r7i.12xlarge for processing job usage ml.r7i.12xlarge for processing job usage general | 0 count | Adjustable |
ml.r6i.12xlarge for cluster usage ml.r6i.12xlarge for cluster usage capacity | 0 count | Adjustable |
ml.r6gd.xlarge for endpoint usage ml.r6gd.xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r6i.32xlarge for cluster usage ml.r6i.32xlarge for cluster usage capacity | 0 count | Adjustable |
ml.r6i.12xlarge for cluster spot instance usage ml.r6i.12xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Rate of ListTrainingJobs requests Rate of ListTrainingJobs requests throughput | 2 count | Fixed |
Rate of UpdateEndpoint requests Rate of UpdateEndpoint requests throughput | 1 count | Fixed |
ml.t2.large for endpoint usage ml.t2.large for endpoint usage networking | 0 count | Adjustable |
ml.g7e.48xlarge for processing job usage ml.g7e.48xlarge for processing job usage general | 0 count | Adjustable |
ml.c7g.12xlarge for endpoint usage ml.c7g.12xlarge for endpoint usage networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m6id.xlarge instances Studio CodeEditor Apps running on ml.m6id.xlarge instances capacity | 1 count | Adjustable |
Studio JupyterLab Apps running on ml.m7i.xlarge instances Studio JupyterLab Apps running on ml.m7i.xlarge instances capacity | 1 count | Adjustable |
ml.r7i.large for notebook instance usage ml.r7i.large for notebook instance usage capacity | 1 count | Adjustable |
ml.c5.12xlarge for cluster usage ml.c5.12xlarge for cluster usage capacity | 0 count | Adjustable |
ml.m7i.xlarge for endpoint usage ml.m7i.xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r5.2xlarge for training warm pool usage ml.r5.2xlarge for training warm pool usage general | 0 count | Adjustable |
ml.m6i.12xlarge for training warm pool usage ml.m6i.12xlarge for training warm pool usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r5.2xlarge instances Studio CodeEditor Apps running on ml.r5.2xlarge instances capacity | 0 count | Adjustable |
ml.r7i.xlarge for training warm pool usage ml.r7i.xlarge for training warm pool usage general | 0 count | Adjustable |
ml.r7i.4xlarge for transform job usage ml.r7i.4xlarge for transform job usage general | 0 count | Adjustable |
ml.gr6.4xlarge for cluster spot instance usage ml.gr6.4xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.r7i.48xlarge for cluster usage ml.r7i.48xlarge for cluster usage capacity | 0 count | Adjustable |
ml.g6.2xlarge for training warm pool usage ml.g6.2xlarge for training warm pool usage general | 0 count | Adjustable |
ml.c7i.8xlarge for notebook instance usage ml.c7i.8xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.g7e.24xlarge for processing job usage ml.g7e.24xlarge for processing job usage general | 0 count | Adjustable |
ml.g5.16xlarge for training warm pool usage ml.g5.16xlarge for training warm pool usage general | 0 count | Adjustable |
ml.m8g.12xlarge for endpoint usage ml.m8g.12xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m7i.8xlarge for training job usage ml.m7i.8xlarge for training job usage general | 0 count | Adjustable |
ml.p4d.24xlarge for notebook instance usage ml.p4d.24xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.m4.2xlarge for transform job usage ml.m4.2xlarge for transform job usage general | 0 count | Adjustable |
ml.m5.large for cluster usage ml.m5.large for cluster usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m6id.4xlarge instances Studio JupyterLab Apps running on ml.m6id.4xlarge instances capacity | 0 count | Adjustable |
ml.c5.2xlarge for training warm pool usage ml.c5.2xlarge for training warm pool usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m6i.4xlarge instances Studio CodeEditor Apps running on ml.m6i.4xlarge instances capacity | 0 count | Adjustable |
ml.g7e.4xlarge for training job usage ml.g7e.4xlarge for training job usage general | 0 count | Adjustable |
ml.r7i.16xlarge for spot training job usage ml.r7i.16xlarge for spot training job usage general | 0 count | Adjustable |
ml.m6i.8xlarge for notebook instance usage ml.m6i.8xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.m7i.24xlarge for training job usage ml.m7i.24xlarge for training job usage general | 0 count | Adjustable |
ml.r5d.4xlarge for spot training job usage ml.r5d.4xlarge for spot training job usage general | 0 count | Adjustable |
ml.c5.9xlarge for endpoint usage ml.c5.9xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c5.2xlarge for cluster spot instance usage ml.c5.2xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.g5.12xlarge instance Studio KernelGateway Apps running on ml.g5.12xlarge instance networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.g5.4xlarge instances Studio CodeEditor Apps running on ml.g5.4xlarge instances capacity | 0 count | Adjustable |
ml.trn1.32xlarge for training warm pool usage ml.trn1.32xlarge for training warm pool usage general | 0 count | Adjustable |
ml.m7i.large for endpoint usage ml.m7i.large for endpoint usage networking | 0 count | Adjustable |
ml.r6i.8xlarge for transform job usage ml.r6i.8xlarge for transform job usage general | 0 count | Adjustable |
ml.r5.4xlarge for training job usage ml.r5.4xlarge for training job usage general | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.r5.large instance Studio KernelGateway Apps running on ml.r5.large instance networking | 1 count | Adjustable |
Studio CodeEditor Apps running on ml.r5.xlarge instances Studio CodeEditor Apps running on ml.r5.xlarge instances capacity | 1 count | Adjustable |
Rate of ListEndpointConfigs requests Rate of ListEndpointConfigs requests throughput | 2 count | Fixed |
ml.t3.large for cluster spot instance usage ml.t3.large for cluster spot instance usage capacity | 0 count | Adjustable |
ml.g5.16xlarge for training job usage ml.g5.16xlarge for training job usage general | 0 count | Adjustable |
Rate of DescribeWorkforce requests Rate of DescribeWorkforce requests throughput | 5 count | Fixed |
Rate of DescribeNotebookInstanceLifecycleConfig requests Rate of DescribeNotebookInstanceLifecycleConfig requests throughput | 5 count | Fixed |
ml.c7g.4xlarge for endpoint usage ml.c7g.4xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c5n.xlarge for training warm pool usage ml.c5n.xlarge for training warm pool usage general | 0 count | Adjustable |
ml.m5d.4xlarge for endpoint usage ml.m5d.4xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r5.24xlarge for processing job usage ml.r5.24xlarge for processing job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r7i.48xlarge instances Studio CodeEditor Apps running on ml.r7i.48xlarge instances capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m6i.large instances Studio JupyterLab Apps running on ml.m6i.large instances capacity | 1 count | Adjustable |
ml.m5.12xlarge for training warm pool usage ml.m5.12xlarge for training warm pool usage general | 0 count | Adjustable |
ml.m7i.xlarge for processing job usage ml.m7i.xlarge for processing job usage general | 0 count | Adjustable |
ml.gr6.4xlarge for cluster usage ml.gr6.4xlarge for cluster usage capacity | 0 count | Adjustable |
ml.r7i.2xlarge for cluster usage ml.r7i.2xlarge for cluster usage capacity | 0 count | Adjustable |
ml.r7i.24xlarge for processing job usage ml.r7i.24xlarge for processing job usage general | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.c5.2xlarge instance Studio KernelGateway Apps running on ml.c5.2xlarge instance networking | 1 count | Adjustable |
Studio CodeEditor Apps running on ml.m6id.16xlarge instances Studio CodeEditor Apps running on ml.m6id.16xlarge instances capacity | 0 count | Adjustable |
ml.m6i.24xlarge for training warm pool usage ml.m6i.24xlarge for training warm pool usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.p4d.24xlarge instances Studio JupyterLab Apps running on ml.p4d.24xlarge instances capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m5.24xlarge instances Studio JupyterLab Apps running on ml.m5.24xlarge instances capacity | 0 count | Adjustable |
ml.p3.8xlarge for endpoint usage ml.p3.8xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r7i.xlarge for endpoint usage ml.r7i.xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r7i.xlarge for spot training job usage ml.r7i.xlarge for spot training job usage general | 0 count | Adjustable |
ml.i3en.12xlarge for cluster spot instance usage ml.i3en.12xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Rate of DescribeMlflowApp requests Rate of DescribeMlflowApp requests throughput | 1 count | Fixed |
ml.m7i.16xlarge for training job usage ml.m7i.16xlarge for training job usage general | 0 count | Adjustable |
ml.c6i.32xlarge for training warm pool usage ml.c6i.32xlarge for training warm pool usage general | 0 count | Adjustable |
ml.r7i.8xlarge for processing job usage ml.r7i.8xlarge for processing job usage general | 0 count | Adjustable |
RSessionGateway Apps running on ml.m5.4xlarge instance RSessionGateway Apps running on ml.m5.4xlarge instance networking | 1 count | Adjustable |
Studio CodeEditor Apps running on ml.g6.xlarge instances Studio CodeEditor Apps running on ml.g6.xlarge instances capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.g6e.12xlarge instances Studio CodeEditor Apps running on ml.g6e.12xlarge instances capacity | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.p3dn.24xlarge instance Studio KernelGateway Apps running on ml.p3dn.24xlarge instance networking | 0 count | Adjustable |
RStudioServerPro Apps running on system instances RStudioServerPro Apps running on system instances capacity | 1 count | Adjustable |
ml.inf1.xlarge for endpoint usage ml.inf1.xlarge for endpoint usage networking | 0 count | Adjustable |
ml.g6e.8xlarge for spot training job usage ml.g6e.8xlarge for spot training job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c6id.xlarge instances Studio CodeEditor Apps running on ml.c6id.xlarge instances capacity | 1 count | Adjustable |
ml.r7i.4xlarge for training warm pool usage ml.r7i.4xlarge for training warm pool usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c6id.4xlarge instances Studio JupyterLab Apps running on ml.c6id.4xlarge instances capacity | 0 count | Adjustable |
ml.c7i.16xlarge for transform job usage ml.c7i.16xlarge for transform job usage general | 0 count | Adjustable |
ml.g5.xlarge for training warm pool usage ml.g5.xlarge for training warm pool usage general | 0 count | Adjustable |
ml.r5.16xlarge for notebook instance usage ml.r5.16xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m7i.xlarge instances Studio CodeEditor Apps running on ml.m7i.xlarge instances capacity | 1 count | Adjustable |
ml.m7i.48xlarge for spot training job usage ml.m7i.48xlarge for spot training job usage general | 0 count | Adjustable |
ml.m6i.32xlarge for spot training job usage ml.m6i.32xlarge for spot training job usage general | 0 count | Adjustable |
ml.g6.8xlarge for training job usage ml.g6.8xlarge for training job usage general | 0 count | Adjustable |
RSessionGateway Apps running on ml.c5.24xlarge instance RSessionGateway Apps running on ml.c5.24xlarge instance networking | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r6i.12xlarge instances Studio JupyterLab Apps running on ml.r6i.12xlarge instances capacity | 0 count | Adjustable |
ml.c6id.xlarge for notebook instance usage ml.c6id.xlarge for notebook instance usage capacity | 1 count | Adjustable |
Rate of CreateProcessingJob requests Rate of CreateProcessingJob requests throughput | 1 count | Fixed |
ml.c7i.xlarge for training warm pool usage ml.c7i.xlarge for training warm pool usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c6i.4xlarge instances Studio JupyterLab Apps running on ml.c6i.4xlarge instances capacity | 0 count | Adjustable |
ml.c5.18xlarge for notebook instance usage ml.c5.18xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.c5n.18xlarge for cluster spot instance usage ml.c5n.18xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.p3.2xlarge for endpoint usage ml.p3.2xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r5.8xlarge for training job usage ml.r5.8xlarge for training job usage general | 0 count | Adjustable |
RSessionGateway Apps running on ml.m5.16xlarge instance RSessionGateway Apps running on ml.m5.16xlarge instance networking | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.g5.24xlarge instances Studio JupyterLab Apps running on ml.g5.24xlarge instances capacity | 0 count | Adjustable |
ml.eia1.large for endpoint usage ml.eia1.large for endpoint usage networking | 0 count | Adjustable |
ml.m6i.large for spot training job usage ml.m6i.large for spot training job usage general | 0 count | Adjustable |
ml.m5d.12xlarge for notebook instance usage ml.m5d.12xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.p5en.48xlarge for cluster spot instance usage ml.p5en.48xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r5.4xlarge instances Studio JupyterLab Apps running on ml.r5.4xlarge instances capacity | 0 count | Adjustable |
ml.p4de.24xlarge for training job usage ml.p4de.24xlarge for training job usage general | 0 count | Adjustable |
ml.c5.2xlarge for spot training job usage ml.c5.2xlarge for spot training job usage general | 4 count | Adjustable |
ml.c5.xlarge for processing job usage ml.c5.xlarge for processing job usage general | 0 count | Adjustable |
ml.c5.xlarge for cluster spot instance usage ml.c5.xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.c6id.large for notebook instance usage ml.c6id.large for notebook instance usage capacity | 1 count | Adjustable |
ml.c6gn.xlarge for endpoint usage ml.c6gn.xlarge for endpoint usage networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c6i.24xlarge instances Studio CodeEditor Apps running on ml.c6i.24xlarge instances capacity | 0 count | Adjustable |
Rate of DescribeHumanTaskUi requests Rate of DescribeHumanTaskUi requests throughput | 5 count | Fixed |
ml.g6e.48xlarge for training warm pool usage ml.g6e.48xlarge for training warm pool usage general | 0 count | Adjustable |
ml.p3dn.24xlarge for training warm pool usage ml.p3dn.24xlarge for training warm pool usage general | 0 count | Adjustable |
Rate of CreatePresignedNotebookInstanceUrl requests Rate of CreatePresignedNotebookInstanceUrl requests throughput | 1 count | Fixed |
ml.r5d.xlarge for training warm pool usage ml.r5d.xlarge for training warm pool usage general | 0 count | Adjustable |
Rate of ListHumanTaskUis requests Rate of ListHumanTaskUis requests throughput | 2 count | Fixed |
Maximum number of MLflow Tracking Servers Maximum number of MLflow Tracking Servers general | 10 count | Adjustable |
ml.m6i.24xlarge for processing job usage ml.m6i.24xlarge for processing job usage general | 0 count | Adjustable |
ml.g5.16xlarge for processing job usage ml.g5.16xlarge for processing job usage general | 0 count | Adjustable |
ml.r7i.large for endpoint usage ml.r7i.large for endpoint usage networking | 0 count | Adjustable |
ml.g5.8xlarge for training job usage ml.g5.8xlarge for training job usage general | 0 count | Adjustable |
ml.c7g.16xlarge for endpoint usage ml.c7g.16xlarge for endpoint usage networking | 0 count | Adjustable |
Maximum number of SageMaker Projects allowed per account Maximum number of SageMaker Projects allowed per account general | 500 count | Adjustable |
ml.m6gd.12xlarge for endpoint usage ml.m6gd.12xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m7i.16xlarge for spot training job usage ml.m7i.16xlarge for spot training job usage general | 0 count | Adjustable |
ml.m6i.xlarge for processing job usage ml.m6i.xlarge for processing job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m6id.24xlarge instances Studio CodeEditor Apps running on ml.m6id.24xlarge instances capacity | 0 count | Adjustable |
RSessionGateway Apps running on ml.m5d.2xlarge instance RSessionGateway Apps running on ml.m5d.2xlarge instance networking | 1 count | Adjustable |
ml.g6e.8xlarge for endpoint usage ml.g6e.8xlarge for endpoint usage networking | 0 count | Adjustable |
ml.p4de.24xlarge for cluster usage ml.p4de.24xlarge for cluster usage capacity | 0 count | Adjustable |
ml.r5d.large for processing job usage ml.r5d.large for processing job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r6id.24xlarge instances Studio JupyterLab Apps running on ml.r6id.24xlarge instances capacity | 0 count | Adjustable |
ml.g7e.12xlarge for cluster usage ml.g7e.12xlarge for cluster usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c6i.16xlarge instances Studio JupyterLab Apps running on ml.c6i.16xlarge instances capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m5.4xlarge instances Studio CodeEditor Apps running on ml.m5.4xlarge instances capacity | 0 count | Adjustable |
Maximum number of private hubs per account Maximum number of private hubs per account general | 100 count | Adjustable |
ml.g6e.4xlarge for endpoint usage ml.g6e.4xlarge for endpoint usage networking | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.g6e.16xlarge instances Studio JupyterLab Apps running on ml.g6e.16xlarge instances capacity | 0 count | Adjustable |
ml.eia2.large for endpoint usage ml.eia2.large for endpoint usage networking | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.m5d.xlarge instance Studio KernelGateway Apps running on ml.m5d.xlarge instance networking | 0 count | Adjustable |
ml.c6i.8xlarge for transform job usage ml.c6i.8xlarge for transform job usage general | 0 count | Adjustable |
ml.m6i.16xlarge for cluster usage ml.m6i.16xlarge for cluster usage capacity | 0 count | Adjustable |
Rate of UpdateMlflowApp requests Rate of UpdateMlflowApp requests throughput | 1 count | Fixed |
ml.r5.24xlarge for spot training job usage ml.r5.24xlarge for spot training job usage general | 0 count | Adjustable |
ml.c7i.16xlarge for training job usage ml.c7i.16xlarge for training job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m5d.xlarge instances Studio CodeEditor Apps running on ml.m5d.xlarge instances capacity | 1 count | Adjustable |
ml.c5.9xlarge for processing job usage ml.c5.9xlarge for processing job usage general | 0 count | Adjustable |
ml.m6i.xlarge for training warm pool usage ml.m6i.xlarge for training warm pool usage general | 0 count | Adjustable |
ml.m6i.4xlarge for cluster usage ml.m6i.4xlarge for cluster usage capacity | 0 count | Adjustable |
ml.g6.2xlarge for processing job usage ml.g6.2xlarge for processing job usage general | 0 count | Adjustable |
ml.c6g.12xlarge for endpoint usage ml.c6g.12xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c5d.xlarge for notebook instance usage ml.c5d.xlarge for notebook instance usage capacity | 1 count | Adjustable |
ml.m6id.32xlarge for notebook instance usage ml.m6id.32xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.c7i.large for training warm pool usage ml.c7i.large for training warm pool usage general | 0 count | Adjustable |
ml.m7i.16xlarge for transform job usage ml.m7i.16xlarge for transform job usage general | 0 count | Adjustable |
Rate of CreateWorkforce requests Rate of CreateWorkforce requests throughput | 1 count | Fixed |
ml.r5d.8xlarge for training warm pool usage ml.r5d.8xlarge for training warm pool usage general | 0 count | Adjustable |
RSessionGateway Apps running on ml.m5d.16xlarge instance RSessionGateway Apps running on ml.m5d.16xlarge instance networking | 0 count | Adjustable |
ml.c7i.2xlarge for transform job usage ml.c7i.2xlarge for transform job usage general | 0 count | Adjustable |
ml.g7e.4xlarge for endpoint usage ml.g7e.4xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r7gd.16xlarge for endpoint usage ml.r7gd.16xlarge for endpoint usage networking | 0 count | Adjustable |
ml.p4de.24xlarge for notebook instance usage ml.p4de.24xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c5.18xlarge instances Studio JupyterLab Apps running on ml.c5.18xlarge instances capacity | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.p3.2xlarge instance Studio KernelGateway Apps running on ml.p3.2xlarge instance networking | 0 count | Adjustable |
ml.r8g.16xlarge for endpoint usage ml.r8g.16xlarge for endpoint usage networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m6i.32xlarge instances Studio CodeEditor Apps running on ml.m6i.32xlarge instances capacity | 0 count | Adjustable |
ml.c5n.18xlarge for spot training job usage ml.c5n.18xlarge for spot training job usage general | 0 count | Adjustable |
ml.p5e.48xlarge for cluster spot instance usage ml.p5e.48xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.i3en.16xlarge for cluster usage ml.i3en.16xlarge for cluster usage capacity | 0 count | Adjustable |
ml.m6i.4xlarge for transform job usage ml.m6i.4xlarge for transform job usage general | 0 count | Adjustable |
RSessionGateway Apps running on ml.t3.medium instance RSessionGateway Apps running on ml.t3.medium instance networking | 2 count | Adjustable |
ml.r6i.2xlarge for cluster usage ml.r6i.2xlarge for cluster usage capacity | 0 count | Adjustable |
ml.m5.2xlarge for processing job usage ml.m5.2xlarge for processing job usage general | 0 count | Adjustable |
ml.g6e.48xlarge for spot training job usage ml.g6e.48xlarge for spot training job usage general | 0 count | Adjustable |
Longest run time for an AutoML job, from creation to termination Longest run time for an AutoML job, from creation to termination general | 2,592,000 Seconds | Fixed |
ml.c5.xlarge for training warm pool usage ml.c5.xlarge for training warm pool usage general | 0 count | Adjustable |
ml.m4.xlarge for endpoint usage ml.m4.xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m5.24xlarge for cluster spot instance usage ml.m5.24xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.r8g.large for endpoint usage ml.r8g.large for endpoint usage networking | 0 count | Adjustable |
ml.c6i.4xlarge for cluster spot instance usage ml.c6i.4xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Rate of DeleteEndpoint requests Rate of DeleteEndpoint requests throughput | 1 count | Fixed |
ml.m5.4xlarge for cluster spot instance usage ml.m5.4xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.r7i.24xlarge for notebook instance usage ml.r7i.24xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.trn1n.32xlarge for notebook instance usage ml.trn1n.32xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.m6id.8xlarge for notebook instance usage ml.m6id.8xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.eia1.xlarge for endpoint usage ml.eia1.xlarge for endpoint usage networking | 0 count | Adjustable |
ml.r5.24xlarge for training warm pool usage ml.r5.24xlarge for training warm pool usage general | 0 count | Adjustable |
ml.g6.16xlarge for processing job usage ml.g6.16xlarge for processing job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c6i.large instances Studio CodeEditor Apps running on ml.c6i.large instances capacity | 1 count | Adjustable |
Studio KernelGateway Apps running on ml.r5.8xlarge instance Studio KernelGateway Apps running on ml.r5.8xlarge instance networking | 0 count | Adjustable |
ml.r6i.large for notebook instance usage ml.r6i.large for notebook instance usage capacity | 1 count | Adjustable |
ml.c5d.xlarge for endpoint usage ml.c5d.xlarge for endpoint usage networking | 0 count | Adjustable |
ml.t3.large for processing job usage ml.t3.large for processing job usage general | 4 count | Adjustable |
ml.p3.2xlarge for training job usage ml.p3.2xlarge for training job usage general | 0 count | Adjustable |
ml.c7i.12xlarge for transform job usage ml.c7i.12xlarge for transform job usage general | 0 count | Adjustable |
Maximum number of concurrent model evaluation serverless jobs per Region Maximum number of concurrent model evaluation serverless jobs per Region compute | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.g6e.xlarge instances Studio JupyterLab Apps running on ml.g6e.xlarge instances capacity | 0 count | Adjustable |
ml.i3en.3xlarge for cluster usage ml.i3en.3xlarge for cluster usage capacity | 0 count | Adjustable |
ml.c5d.4xlarge for notebook instance usage ml.c5d.4xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.t3.2xlarge for training job usage ml.t3.2xlarge for training job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m5.8xlarge instances Studio CodeEditor Apps running on ml.m5.8xlarge instances capacity | 0 count | Adjustable |
ml.c5n.9xlarge for training warm pool usage ml.c5n.9xlarge for training warm pool usage general | 0 count | Adjustable |
ml.r7i.24xlarge for endpoint usage ml.r7i.24xlarge for endpoint usage networking | 0 count | Adjustable |
ml.inf2.24xlarge for endpoint usage ml.inf2.24xlarge for endpoint usage networking | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.c6id.16xlarge instances Studio CodeEditor Apps running on ml.c6id.16xlarge instances capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.m5.large instances Studio CodeEditor Apps running on ml.m5.large instances capacity | 1 count | Adjustable |
ml.m7i.4xlarge for processing job usage ml.m7i.4xlarge for processing job usage general | 0 count | Adjustable |
ml.c5n.2xlarge for spot training job usage ml.c5n.2xlarge for spot training job usage general | 0 count | Adjustable |
ml.r6id.16xlarge for notebook instance usage ml.r6id.16xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.p3.16xlarge instances Studio JupyterLab Apps running on ml.p3.16xlarge instances capacity | 0 count | Adjustable |
ml.c5.12xlarge for cluster spot instance usage ml.c5.12xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.m7i.large for training job usage ml.m7i.large for training job usage general | 0 count | Adjustable |
ml.c6i.8xlarge for cluster usage ml.c6i.8xlarge for cluster usage capacity | 0 count | Adjustable |
Maximum size of EBS volume in GB for a SageMaker HyperPod cluster instance Maximum size of EBS volume in GB for a SageMaker HyperPod cluster instance storage | 0 count | Adjustable |
ml.c6i.12xlarge for transform job usage ml.c6i.12xlarge for transform job usage general | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.m5.xlarge instance Studio KernelGateway Apps running on ml.m5.xlarge instance networking | 1 count | Adjustable |
Studio JupyterLab Apps running on ml.c6id.32xlarge instances Studio JupyterLab Apps running on ml.c6id.32xlarge instances capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m5d.2xlarge instances Studio JupyterLab Apps running on ml.m5d.2xlarge instances capacity | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.trn1.2xlarge instances Studio KernelGateway Apps running on ml.trn1.2xlarge instances networking | 0 count | Adjustable |
ml.r5.24xlarge for endpoint usage ml.r5.24xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c6i.2xlarge for endpoint usage ml.c6i.2xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m4.4xlarge for processing job usage ml.m4.4xlarge for processing job usage general | 0 count | Adjustable |
ml.m6i.16xlarge for notebook instance usage ml.m6i.16xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.r7i.48xlarge for spot training job usage ml.r7i.48xlarge for spot training job usage general | 0 count | Adjustable |
ml.g7e.24xlarge for cluster usage ml.g7e.24xlarge for cluster usage capacity | 0 count | Adjustable |
ml.c6i.2xlarge for training warm pool usage ml.c6i.2xlarge for training warm pool usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.r6i.xlarge instances Studio JupyterLab Apps running on ml.r6i.xlarge instances capacity | 1 count | Adjustable |
Studio JupyterLab Apps running on ml.r5.8xlarge instances Studio JupyterLab Apps running on ml.r5.8xlarge instances capacity | 0 count | Adjustable |
ml.r6i.32xlarge for transform job usage ml.r6i.32xlarge for transform job usage general | 0 count | Adjustable |
ml.c6id.2xlarge for notebook instance usage ml.c6id.2xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.m7i.48xlarge instances Studio JupyterLab Apps running on ml.m7i.48xlarge instances capacity | 0 count | Adjustable |
ml.g4dn.2xlarge for endpoint usage ml.g4dn.2xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m7i.xlarge for cluster spot instance usage ml.m7i.xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.c6i.2xlarge for training job usage ml.c6i.2xlarge for training job usage general | 0 count | Adjustable |
ml.c6gd.xlarge for endpoint usage ml.c6gd.xlarge for endpoint usage networking | 0 count | Adjustable |
ml.t3.xlarge for spot training job usage ml.t3.xlarge for spot training job usage general | 0 count | Adjustable |
ml.c5.9xlarge for notebook instance usage ml.c5.9xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.g5.24xlarge for cluster usage ml.g5.24xlarge for cluster usage capacity | 0 count | Adjustable |
ml.c4.4xlarge for training warm pool usage ml.c4.4xlarge for training warm pool usage general | 0 count | Adjustable |
Rate of DeleteTransformJob requests Rate of DeleteTransformJob requests throughput | 1 count | Fixed |
Studio CodeEditor Apps running on ml.m7i.8xlarge instances Studio CodeEditor Apps running on ml.m7i.8xlarge instances capacity | 0 count | Adjustable |
ml.r6g.8xlarge for endpoint usage ml.r6g.8xlarge for endpoint usage networking | 0 count | Adjustable |
ml.m8g.large for endpoint usage ml.m8g.large for endpoint usage networking | 0 count | Adjustable |
ml.m8g.8xlarge for endpoint usage ml.m8g.8xlarge for endpoint usage networking | 0 count | Adjustable |
ml.c7i.large for processing job usage ml.c7i.large for processing job usage general | 0 count | Adjustable |
ml.g5.4xlarge for processing job usage ml.g5.4xlarge for processing job usage general | 0 count | Adjustable |
ml.inf1.2xlarge for notebook instance usage ml.inf1.2xlarge for notebook instance usage capacity | 0 count | Adjustable |
Rate of CreateNotebookInstance requests Rate of CreateNotebookInstance requests throughput | 1 count | Fixed |
ml.r6i.4xlarge for notebook instance usage ml.r6i.4xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.c4.2xlarge for notebook instance usage ml.c4.2xlarge for notebook instance usage capacity | 1 count | Adjustable |
ml.eia2.medium for endpoint usage ml.eia2.medium for endpoint usage networking | 0 count | Adjustable |
ml.c7i.xlarge for processing job usage ml.c7i.xlarge for processing job usage general | 0 count | Adjustable |
ml.p5.4xlarge for cluster usage ml.p5.4xlarge for cluster usage capacity | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.m5.2xlarge instance Studio KernelGateway Apps running on ml.m5.2xlarge instance networking | 1 count | Adjustable |
Studio CodeEditor Apps running on ml.m5d.4xlarge instances Studio CodeEditor Apps running on ml.m5d.4xlarge instances capacity | 0 count | Adjustable |
RSessionGateway Apps running on ml.t3.large instance RSessionGateway Apps running on ml.t3.large instance networking | 0 count | Adjustable |
ml.c7i.large for spot training job usage ml.c7i.large for spot training job usage general | 0 count | Adjustable |
Maximum number of instances per training job Maximum number of instances per training job capacity | 20 count | Adjustable |
ml.c5.large for endpoint usage ml.c5.large for endpoint usage networking | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.r5.2xlarge instance Studio KernelGateway Apps running on ml.r5.2xlarge instance networking | 1 count | Adjustable |
ml.m7i.12xlarge for training warm pool usage ml.m7i.12xlarge for training warm pool usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.g6.8xlarge instances Studio JupyterLab Apps running on ml.g6.8xlarge instances capacity | 0 count | Adjustable |
ml.m7i.8xlarge for cluster spot instance usage ml.m7i.8xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r7i.4xlarge instances Studio CodeEditor Apps running on ml.r7i.4xlarge instances capacity | 0 count | Adjustable |
ml.m5.xlarge for processing job usage ml.m5.xlarge for processing job usage general | 0 count | Adjustable |
ml.g4dn.xlarge for notebook instance usage ml.g4dn.xlarge for notebook instance usage capacity | 0 count | Adjustable |
Studio KernelGateway Apps running on ml.g5.xlarge instance Studio KernelGateway Apps running on ml.g5.xlarge instance networking | 0 count | Adjustable |
ml.r5.24xlarge for notebook instance usage ml.r5.24xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.c5n.4xlarge for training job usage ml.c5n.4xlarge for training job usage general | 0 count | Adjustable |
ml.c5n.4xlarge for spot training job usage ml.c5n.4xlarge for spot training job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.r6i.32xlarge instances Studio CodeEditor Apps running on ml.r6i.32xlarge instances capacity | 0 count | Adjustable |
Maximum number of Studio spaces allowed per account Maximum number of Studio spaces allowed per account general | 6 count | Adjustable |
ml.r7i.xlarge for training job usage ml.r7i.xlarge for training job usage general | 0 count | Adjustable |
Studio CodeEditor Apps running on ml.g6e.24xlarge instances Studio CodeEditor Apps running on ml.g6e.24xlarge instances capacity | 0 count | Adjustable |
ml.g5.48xlarge for cluster usage ml.g5.48xlarge for cluster usage capacity | 0 count | Adjustable |
ml.g6e.16xlarge for cluster usage ml.g6e.16xlarge for cluster usage capacity | 0 count | Adjustable |
ml.g5.48xlarge for training warm pool usage ml.g5.48xlarge for training warm pool usage general | 0 count | Adjustable |
ml.c8g.medium for endpoint usage ml.c8g.medium for endpoint usage networking | 0 count | Adjustable |
ml.r7i.24xlarge for cluster usage ml.r7i.24xlarge for cluster usage capacity | 0 count | Adjustable |
ml.c5.4xlarge for cluster spot instance usage ml.c5.4xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c6id.large instances Studio JupyterLab Apps running on ml.c6id.large instances capacity | 1 count | Adjustable |
Studio CodeEditor Apps running on ml.c6i.2xlarge instances Studio CodeEditor Apps running on ml.c6i.2xlarge instances capacity | 1 count | Adjustable |
Studio JupyterLab Apps running on ml.g5.8xlarge instances Studio JupyterLab Apps running on ml.g5.8xlarge instances capacity | 0 count | Adjustable |
Rate of ListNotebookInstanceLifecycleConfigs requests Rate of ListNotebookInstanceLifecycleConfigs requests throughput | 2 count | Fixed |
ml.c7i.2xlarge for spot training job usage ml.c7i.2xlarge for spot training job usage general | 0 count | Adjustable |
ml.r6i.16xlarge for cluster spot instance usage ml.r6i.16xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.c5.24xlarge for cluster usage ml.c5.24xlarge for cluster usage capacity | 0 count | Adjustable |
ml.c6i.24xlarge for transform job usage ml.c6i.24xlarge for transform job usage general | 0 count | Adjustable |
ml.g5.16xlarge for cluster spot instance usage ml.g5.16xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.c5n.4xlarge for training warm pool usage ml.c5n.4xlarge for training warm pool usage general | 0 count | Adjustable |
ml.p6e-gb200.36xlarge for cluster usage ml.p6e-gb200.36xlarge for cluster usage capacity | 0 count | Adjustable |
ml.m7i.8xlarge for spot training job usage ml.m7i.8xlarge for spot training job usage general | 0 count | Adjustable |
ml.m5.12xlarge for cluster spot instance usage ml.m5.12xlarge for cluster spot instance usage capacity | 0 count | Adjustable |
ml.m6i.32xlarge for training job usage ml.m6i.32xlarge for training job usage general | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c6i.large instances Studio JupyterLab Apps running on ml.c6i.large instances capacity | 1 count | Adjustable |
ml.r7i.24xlarge for training job usage ml.r7i.24xlarge for training job usage general | 0 count | Adjustable |
ml.r6id.8xlarge for notebook instance usage ml.r6id.8xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.g6.4xlarge for notebook instance usage ml.g6.4xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.c5.18xlarge for cluster usage ml.c5.18xlarge for cluster usage capacity | 0 count | Adjustable |
Studio JupyterLab Apps running on ml.c5.large instances Studio JupyterLab Apps running on ml.c5.large instances capacity | 1 count | Adjustable |
ml.c7i.4xlarge for notebook instance usage ml.c7i.4xlarge for notebook instance usage capacity | 0 count | Adjustable |
Rate of DeleteEndpointConfig requests Rate of DeleteEndpointConfig requests throughput | 1 count | Fixed |
ml.g5.48xlarge for notebook instance usage ml.g5.48xlarge for notebook instance usage capacity | 0 count | Adjustable |
ml.r6i.24xlarge for cluster usage ml.r6i.24xlarge for cluster usage capacity | 0 count | Adjustable |
How to Request a Quota Increase
- 1Open the AWS Service Quotas console.
- 2Select Amazon SageMaker from the service list.
- 3Find the quota and click "Request increase".
- 4Enter the desired value and submit. Most increases are approved within a few hours.
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