Book Image

AWS Certified Database – Specialty (DBS-C01) Certification Guide

By : Kate Gawron
5 (1)
Book Image

AWS Certified Database – Specialty (DBS-C01) Certification Guide

5 (1)
By: Kate Gawron

Overview of this book

The AWS Certified Database – Specialty certification is one of the most challenging AWS certifications. It validates your comprehensive understanding of databases, including the concepts of design, migration, deployment, access, maintenance, automation, monitoring, security, and troubleshooting. With this guide, you'll understand how to use various AWS databases, such as Aurora Serverless and Global Database, and even services such as Redshift and Neptune. You’ll start with an introduction to the AWS databases, and then delve into workload-specific database design. As you advance through the chapters, you'll learn about migrating and deploying the databases, along with database security techniques such as encryption, auditing, and access controls. This AWS book will also cover monitoring, troubleshooting, and disaster recovery techniques, before testing all the knowledge you've gained throughout the book with the help of mock tests. By the end of this book, you'll have covered everything you need to pass the DBS-C01 AWS certification exam and have a handy, on-the-job desk reference guide.
Table of Contents (24 chapters)
1
Part 1: Introduction to Databases on AWS
Free Chapter
2
Chapter 1: AWS Certified Database – Specialty Overview
5
Part 2: Workload-Specific Database Design
12
Part 3: Deployment and Migration and Database Security
16
Part 4: Monitoring and Optimization
20
Part 5: Assessment
21
Chapter 16: Exam Practice

Summary

In this chapter, we learned about three different tools that are commonly used with AWS to automate infrastructure creation and administration – that is, the AWS CLI, CloudFormation, and CDK. Then, we learned how to automate how to load and handle data from S3 using AWS Glue and Amazon Athena.

Regarding automation, we learned how to create a CloudFormation stack using YAML or JSON templates and how to launch those stacks using both the AWS Console and the AWS CLI. We learned how we can use parameters within our stacks to allow the same code to be reused to create a controlled and automated method to create databases.

We finished this chapter by learning how to create an ETL job using AWS Glue and how to use Amazon Athena to query the data that's held within S3 without having to import it into a database first.

In the next chapter, we are going to learn about database security. We came across a few different database security tools and features earlier in...