Effortless Relational Scalability with Amazon Aurora Serverless v2

Amazon Aurora Serverless is an on-demand auto scaling configuration for Amazon Aurora. With Aurora Serverless, you can scale your database capacity up or down based on your application’s need.

The lab demonstrates how Aurora Serverless v2 scales in response to changes in application demand. You will use an Aurora Serverless v2 PostgreSQL-Compatible Edition cluster to run a generated workload using pgbench. You will then monitor the database performance using Amazon CloudWatch metrics in the Amazon Relational Database Service (Amazon RDS) console, Amazon RDS Performance Insights tool, and CloudWatch dashboard.

Level

Intermediate

Duration

Course Objectives

In this course, you will learn how to:

• Configure Aurora Serverless v2 for PostgreSQL.
• Use custom pgbench scripts to simulate workload activity.
• Monitor key CloudWatch metrics using dashboard.
• Use Performance Insights to monitor the query performance.

Intended Audience

This course is intended for:

Data Engineers responsible for developing, constructing, testing and maintaining architectures.

Prerequisites

We recommend that attendees of this course have the following prerequisites:

• A working knowledge of Amazon RDS, AWS Cloud9, CloudWatch, and Performance Insights
• An understanding of database concepts, including database structures, data types, and structured query language (SQL)

Course Outline

Task 1: Inspect the environment

Task 2: Create an Aurora Serverless v2 cluster

Task 3: Configure load testing scripts in AWS Cloud9

Task 4: Create a database activity for a regular workload

Task 5: Create a dashboard for monitoring database metrics

Task 6: Create a database activity for variable read-only workloads