Book Image

AWS Observability Handbook

By : Phani Kumar Lingamallu, Fabio Braga de Oliveira
Book Image

AWS Observability Handbook

By: Phani Kumar Lingamallu, Fabio Braga de Oliveira

Overview of this book

As modern application architecture grows increasingly complex, identifying potential points of failure and measuring end user satisfaction, in addition to monitoring application availability, is key. This book helps you explore AWS observability tools that provide end-to-end visibility, enabling quick identification of performance bottlenecks in distributed applications. You’ll gain a holistic view of monitoring and observability on AWS, starting from observability basics using Amazon CloudWatch and AWS X-Ray to advanced ML-powered tools such as AWS DevOps Guru. As you progress, you'll learn about AWS-managed open source services such as AWS Distro for OpenTelemetry (ADOT) and AWS managed Prometheus, Grafana, and the ELK Stack. You’ll implement observability in EC2 instances, containers, Kubernetes, and serverless apps and grasp UX monitoring. With a fair mix of concepts and examples, this book helps you gain hands-on experience in implementing end-to-end AWS observability in your applications and navigating and troubleshooting performance issues with the help of use cases. You'll also learn best practices and guidelines, such as how observability relates to the Well-Architected Framework. By the end of this AWS book, you’ll be able to implement observability and monitoring in your apps using AWS’ native and managed open source tools in real-world scenarios.
Table of Contents (22 chapters)
1
Part 1: Getting Started with Observability on AWS
6
Part 2: Automated and Machine Learning-Powered Observability on AWS
11
Part 3: Open Source Managed Services on AWS
15
Part 4: Scaled Observability and Beyond

Summary

In this chapter, we saw why AWS X-Ray is required in a distributed application and navigated the foundations of AWS X-Ray. We understood various components of the AWS X-ray console, such as the ServiceLens map, AWS X-Ray Analytics, and traces, and how to understand them. Further, we instrumented a Java application running on EC2 using AWS X-Ray and understood how to read the trace data and how annotations and metadata can support troubleshooting operational issues and filter out traces that are relevant to the problem.

At this point, you understand the value of having a distributed tracing tool in your observability toolbelt and how to apply it correctly to collect all the necessary data.

This is the last chapter of Part 1 of this book, where you gained a good first picture of observability’s more fundamental building blocks. Part 2 will introduce services that remove much of the manual work necessary to gather and show the relevant data and introduce innovative...