Chapter 5: Amazon Aurora

Amazon Aurora is a fully managed relational database offered by Amazon Web Services (AWS). It has many similarities to Amazon Relational Database Service (RDS), which we learned about in the previous chapter, but it also has many exclusive features. Aurora is a major topic within the AWS Certified Database – Specialty exam and as it features many of the same technologies as RDS it is highly recommended that you study Chapter 4, Relational Database Service, before this one.

In this chapter, we will learn about Amazon Aurora's architecture and how it differs from RDS, how we can achieve high availability and design Aurora to allow rapid disaster recovery, and we'll learn about some advanced options and features that only exist within Aurora.

This chapter includes a hands-on lab where we will deploy, configure, and explore an Aurora cluster, including how we can monitor it.

In this chapter, we're going to cover the following main...

Technical requirements

You will require an AWS account with root access; everything we will do in this chapter will be available as Free Tier, which means you can run all the example code without spending any money as long as your account has only been opened within the last 12 months. You will also require AWS Command-Line Interface (CLI) access. The AWS CLI Configuration Guide (https://docs.aws.amazon.com/cli/latest/userguide/cli-chap-configure.html) will explain the steps required, but I will summarize them here:

1. Open an AWS account if you have not already done so.
2. Download the AWS CLI latest version (AWS CLI version 2) from the following link: https://docs.aws.amazon.com/cli/latest/userguide/cli-chap-welcome.html.
3. Create an access key for your administration user: https://docs.aws.amazon.com/IAM/latest/UserGuide/getting-started_create-admin-group.html#getting-started_create-admin-group-cli.
4. Run the aws configure command to set up a profile for your user.
...

Overview of the Amazon Aurora service

Amazon Aurora is a managed database service. This means that AWS offers a wrapper around a relational database that handles many of the functions normally carried out by a Database Administrator (DBA). Where Aurora differs from RDS is that Aurora always speeds up the database functionality, and it can run up to five times faster than a non-Aurora version of the same database. Aurora manages such fast speeds by using a distributed storage system to avoid bandwidth and disk-read bottlenecks. Aurora has many benefits compared to RDS:

• Faster scaling: Aurora can almost instantly add additional read replicas whereas with RDS these can take some time to provision.
• Read replicas: Aurora supports up to 15 replicas compared to five on RDS.
• High durability: Aurora stores your data in six different locations across three Availability Zones (AZs) by default, so it has very high resilience as standard.
• Rapid disaster recovery: Aurora can...

Understanding Aurora clusters and replicas

Amazon Aurora has been designed to benefit from cloud technology and as a result, it can use cloud ideologies such as auto-scaling (both horizontal and vertical) and decoupling of different parts of the application to improve resilience in a deeper manner than RDS. Let's take a closer look at an Aurora cluster to see how it decouples the compute layer and the storage layer to offer high redundancy and fast scaling.

Aurora clusters

An Aurora cluster is made up of two different types of nodes:

• Database instance: This is the power of the database and is where the database application sits and the processing of the data happens.
• Cluster volume: This is the storage layer spanning three AZs to offer the six data storage locations.

The following diagram shows how an Aurora cluster is arranged:

Figure 5.1 – Amazon Aurora cluster topology

All of the data is stored within the cluster volumes...

Backing up and restoring Aurora

Ensuring your data is secure and can be restored rapidly is a critical part of any reliable and resilient database system. Aurora has multiple options for backup and recovery strategies.

Backing up an Aurora cluster

Amazon Aurora is backed up continually and automatically as well as a system backup taken daily. The continual backups are taken throughout the day and do not have an impact on the performance of the database; this is a major advantage of the cluster volumes Aurora uses. The daily backup is taken during the backup window defined and this can have a low impact on performance, so the backup window should be chosen during a non-peak time. The backups are held in S3 until the retention time is reached, when they are deleted. The retention time can be set between one and 35 days and the default is one day regardless of whether the database is provisioned by the console or awscli.

You can also make ad-hoc backups at any time. These are...

Using Aurora's Global Database and Serverless options

Aurora offers two advanced features that can make a huge difference for certain use cases. In particular, customers who have a worldwide customer base can use Global Database options to reduce the latency between the database and applications around the world, improving performance. Customers with unpredictable or intermittent workloads can benefit from Aurora Serverless, where they can use a database without having to define the compute. Let's start by looking at Aurora Global Database in more depth.

Aurora Global Database

Aurora Global Database allows you to create a cross-region Aurora cluster where you can send read requests all over the world. This allows you to have read replicas in the same regions as your applications and users to greatly reduce latency times and improve the performance of your applications.

Aurora Global Database can also offer rapid recovery from a region outage, as any of the secondary...

Understanding Aurora pricing

Aurora pricing is different between provisioned mode and Serverless. In provisioned mode, Aurora is priced in a similar way to RDS, where you decide how much resources (CPU and memory) you need, as well as how much storage. In Serverless, you are billed based on the Aurora Capacity Units (ACUs), which are priced as a combination of CPU and memory. In addition, you pay for any specific features you use such as global tables and Backtrack. In addition, you pay for read/write I/O usage in Aurora, which is included as standard in RDS.

To calculate your total Aurora costs, you will need to choose an instance size, database engine (MySQL or PostgreSQL), storage size, and I/O requirements. You can use the AWS Calculator to help you build your estimate. The following screenshot shows the figures you need to add to the Calculator for storage and I/O rates:

Figure 5.3 – AWS Calculator

The Calculator URL is https://calculator.aws...

Deploying an Aurora cluster

Now we have learned about Aurora and its features, let's deploy our own cluster to practice and to see how the topics we've covered in this chapter work together. We will be deploying an Aurora cluster using the MySQL engine in Serverless mode and we'll then add Global Database. We'll use both the console and awscli for these steps.

Provisioning an Aurora cluster

We'll start by provisioning an Aurora MySQL cluster. We'll be using the Ohio (us-east-1) region. It is important to switch off encryption for this cluster, otherwise we will get an error when creating a global database. In a production environment, we would create a custom KMS key to be used for our multi-region databases, but for now, we will turn off encryption:

1. Open the AWS console in an internet browser and log in using an account that has privileges to create and modify an RDS instance.
2. Navigate to Amazon RDS (remember Aurora is a specific type...

Summary

In this chapter, we have learned about Amazon Aurora. We have learned how Aurora differs from RDS, what database types are supported, how to deploy both a provisioned and Serverless Aurora cluster, and how to carry out some common maintenance and configuration tasks. We learned how to use both the AWS console and awscli to interact with our databases. These skills will enable us to work with Amazon Aurora databases confidently, as well as describe the use cases and benefits of Aurora compared to RDS.

During the AWS Certified Database – Specialty exam, your knowledge of Aurora will be tested heavily with questions around troubleshooting, service limits, Serverless and Global Database features, and migrating from RDS.

In the next chapter, we will be learning about AWS DynamoDB, which is a NoSQL database designed and fully managed by AWS. DynamoDB is very different from both RDS and Aurora as it supports unstructured data and does not rely on complex queries with...

Cheat sheet

This cheat sheet reminds you of the high-level topics and points covered in this chapter and should act as a revision guide and refresher:

• Amazon Aurora is a managed database service created by AWS that offers a database compatible with MySQL or PostgreSQL.
• An Aurora cluster features reader and writer instances with their own endpoints, allowing you to split your application workload between reads and writes.
• You do not define the storage capacity for Aurora as it can scale instantaneously and automatically. You also do not need to define any Input/Output Operations Per Second (IOPS) or throughput as you always get the maximum available with any Aurora instance or storage size.
• You can have up to 15 reader instances in any one cluster, but only one writer instance.
• Aurora automates many of the daily administrative functions typically carried out by a DBA. These include backups, log rotation, and patching of the operating system and database, and...

Review

To check your knowledge from this chapter, here are five questions that you should now be able to answer. Remember the exam techniques from Chapter 1, AWS Certified Database – Specialty Exam Overview, and remove the clearly incorrect answers first to help you:

1. You have an application that has an Amazon Aurora MySQL backend database. The customer wants to grant access to a reporting tool. How can you modify the existing database to give access to the reporting tool, which must be highly available without impacting the performance of the online application in the most cost-efficient way?
   1. Create a cross-region Multi-AZ deployment and create a read replica in the second region.
   2. Move the instance to Amazon EC2 and create and manage snapshots manually.
   3. Create a Multi-AZ Aurora read replica of the Aurora DB instance.
   4. Create a Single-AZ Aurora read replica of the Aurora DB instance. Create a second Single-AZ Aurora read replica from the replica.
2. You are managing a web...

Further reading

In this chapter, we have covered the most common Aurora topics. In the AWS Certified Database – Specialty exam, you will be expected to know and understand how other areas of AWS interact with Aurora, which we will cover in more depth in later chapters. However, for a deeper understanding of how the underlying storage and network configuration of Aurora works, refer to the book AWS: Security Best Practices on AWS (https://subscription.packtpub.com/book/virtualization_and_cloud/9781789134513/2/ch02lvl1sec19/aws-kms).