Hi 👋🏽

today we want to explore Amazon RDS, the fully managed database service that simplifies the process of...

• setting up
• operating and
• scaling relational databases

in the cloud. 🌤

Whether you're a seasoned database administrator or just getting started with cloud computing, this newsletter is packed with insights and best practices for getting the most out of Amazon RDS.

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Let's get started with RDS 🚀

RDS

Infographic

First, let's check out our overview with our one-page infographic for RDS:

Now we dive in and learn not only the fundamentals but how to optimize your database infrastructure with Amazon RDS.

The topics we'll cover in detail:

• Introduction
• Supported Database Engines
• Database States
• Resiliency via Multi-AZ
• Read Replicas
• Automated Backups
• Encryption
• Auto-Scaling
• Pricing

Let's go! 🚀

Introduction

Amazon Relational Database Service (RDS) is the fully-managed SQL database offered by AWS.

Instead of setting up, running and operating your own virtual machine that runs a database engine on top, you can set up a managed SQL cluster with a few clicks.

You don't need to manage the infrastructure or operating system.

You set up your database, receive a connection string, and you are good to go.

Database Engines

RDS comes with different engines for different requirements:

• Amazon Aurora: A fully managed DB engine compatible with different engines like MySQL and PostgreSQL for high availability and low latency.
• MySQL: An open-source database with flexible and scalable architecture and support for multiple platforms.
• MariaDB: Open-source DB engine derived from MySQL, offering advanced features and improvements.
• PostgreSQL: One of the most famous and loved open-source database engine known for advanced features, extensibility, and strong support for ACID (Atomicity, Consistency, Isolation, and Durability) transactions.
• Oracle: A commercial database engine that's widely used across companies for large-scale applications.
• Microsoft SQL Server: a relational database engine with advanced features, high availability, and scalability, and strong integration with Microsoft products.

One thing to be aware of these engines is the exact version AWS supports. The engine itself is an official release of the engine. But AWS often supports certain versions of this engine.

For example, in RDS you can use Postgres 14.3-R1. The latest minor version is 14.4. If you need a certain version check this before migrating the whole workload to RDS.

Database States

Your RDS database can be in different states within its lifecycle. Among them are:

• creating: the database will be created
• available: the database is ready to receive requests
• upgrading: database upgrades to a new version
• backing-up: a background process is backing-up your data
• modifying: user modifications are in progress
• stopped: the database is stopped
• storage-full: the storage is full
• maintenance: RDS is doing maintenance work on your database. You defined the maintenance window
• failed: your DB failed and RDS can't recover it
• deleting: the database will be deleted

There are many more states to discover.

Resiliency via Multi-AZ

One famous sentence by Werner Vogels, the CTO of Amazon, to always remember

Even with managed infrastructure in the cloud, servers will fail and outages will occur.

That's why it's important to have proper resiliency by being prepared for an availability zone outage.

In RDS this is configurable. Choose the option Multi-AZ DB Instance during the generation of the database. This makes your database available in multiple AZs.

RDS will then create a primary and secondary database which will be synchronized constantly.

If the primary database goes offline, AWS will automatically failover to your secondary database with read & write access.

Read Replicas

When your traffic grows over time, a read-replica is a good choice to increase the performance for read operations.

Let's say you have an application where most users are in the US. Your application will live in us-east-1. All users from other countries like Europe will experience a longer latency. This is not ideal.

To increase the performance you can create a read replicate in eu-central-1. This enables a much shorter latency to the database for reading workloads. Writing will still happen in us-east-1.

Automated Backups

With backups, you can restore your database back to a certain point in time.

In case you introduced a bug, deleted entries on accident, or any other incident occurred that resulted in corrupted or lost data.

Amazon RDS supports automated backups. These will constantly create snapshots of your data.

You can configure your backup in the RDS console. You configure a backup window which is a time when a backup takes place.

The backup window is optional. If skipped, RDS will fall back to default times for each region.

💡 The backup process will increase the load on your database while it is created. It’s a good practice to configure backup windows for times when your application is not at peak load, e.g. at night times instead of during business hours.

Encryption

You can encrypt your data within RDS. If you activate encryption your data will be encrypted at rest. That means your data is encrypted on the actual hardware.

It is encrypted with the industry standard of AES-256.

RDS activates this by default for every database creation.

Auto-Scaling

Scaling up and down your application is what makes RDS powerful. This can either happen at predictable peak times or at unpredictable events.

• Upscaling - means your database requires more resources like CPU or storage.
• Downscaling - means that your database needs fewer resources to save costs.

Instead of having one database instance, you would have two or three for example. Adding read replicas is one of the most straightforward ways of horizontal scaling. This was already discussed in the read replica chapter. The main point is: If your application only needs to scale for reading reasons add read replicas. You will find that this happens often.

Auto Scaling allows you to scale up and down automatically, based on a policy. A policy can be based on a metric like free storage. For example, if there is only 10% free storage, scale up.

💡 Auto-scaling is only possible for storage not for the actual instance class.

You can scale the instance class with a manual solution. For example, you could use EventBridge & Lambda to scale it up. But there are also downtimes involved so be careful about that.

Pricing

RDS is priced on the Instance Class & how long the instance runs. As RDS is not serverless, your instance will run 24/7 and you'll be charged 24/7.

You can check out the pricing calculator to get an accurate estimate of your database.

Final Words

Amazon RDS is a great choice for running a relational database due to its fully managed nature, which simplifies the process of setting up, operating, and scaling a database in the cloud.

With support for popular database engines like MySQL, PostgreSQL, Oracle, and Microsoft SQL Server, RDS offers a range of advanced features, high availability, and automatic scaling, making it an ideal choice for demanding applications that require fast and reliable performance.

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We hope you enjoyed this issue and you've learned something new.

Don't forget to get your hands on to get some personal experience with this great service! 🏗

Have a great week & hear you soon 👋

Sandro & Tobi

If you want to learn more about RDS, check out some of our recent blogs post that cover deep insights into the cost structure and scaling. 📚