Book Image

AWS Certified DevOps Engineer - Professional Certification and Beyond

By : Adam Book
Book Image

AWS Certified DevOps Engineer - Professional Certification and Beyond

By: Adam Book

Overview of this book

The AWS Certified DevOps Engineer certification is one of the highest AWS credentials, vastly recognized in cloud computing or software development industries. This book is an extensive guide to helping you strengthen your DevOps skills as you work with your AWS workloads on a day-to-day basis. You'll begin by learning how to create and deploy a workload using the AWS code suite of tools, and then move on to adding monitoring and fault tolerance to your workload. You'll explore enterprise scenarios that'll help you to understand various AWS tools and services. This book is packed with detailed explanations of essential concepts to help you get to grips with the domains needed to pass the DevOps professional exam. As you advance, you'll delve into AWS with the help of hands-on examples and practice questions to gain a holistic understanding of the services covered in the AWS DevOps professional exam. Throughout the book, you'll find real-world scenarios that you can easily incorporate in your daily activities when working with AWS, making you a valuable asset for any organization. By the end of this AWS certification book, you'll have gained the knowledge needed to pass the AWS Certified DevOps Engineer exam, and be able to implement different techniques for delivering each service in real-world scenarios.
Table of Contents (31 chapters)
Section 1: Establishing the Fundamentals
Section 2: Developing, Deploying, and Using Infrastructure as Code
Section 3: Monitoring and Logging Your Environment and Workloads
Section 4: Enabling Highly Available Workloads, Fault Tolerance, and Implementing Standards and Policies
Section 5: Exam Tips and Tricks

Searching and grouping logs with managed Elasticsearch

Many people associate Elasticsearch with ELK; however, the two have differences. ELK stands for Elasticsearch, Logstash, and Kibana. In this configuration, Elasticsearch serves as the storage, Logstash serves as the log parser, and Kibana serves as the visualization frontend of the system where users interact with the system:

Figure 17.8 – A comparison of the ELK stack versus Amazon's managed Elasticsearch service

With Amazon's managed Elasticsearch service, there is no Logstash installed by default; however, there are other options to get the logs that you generate into your Elasticsearch cluster.

Use cases for managed Elasticsearch

There are several use cases for using the managed Elasticsearch product from AWS. Let's examine them next.

Store and search logs for application monitoring

You can stream logs that have been placed into AWS CloudWatch Logs into Amazon&apos...