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

Collecting Metrics and Traces Using OpenTelemetry

Regardless of whether you are a seasoned veteran or a beginner on your observability journey, since you are following this book and doing your homework, you already have all the pieces in place now: you can now collect metrics, traces, and logs from your application on AWS, whether using Elastic Compute Cloud (EC2) instances, containers, or Lambda functions.

But let’s take a step back to see the big picture. To collect metrics for an EC2 environment, you need to install an agent on your virtual machine, a sidecar on your containerized application, or a Lambda layer on your serverless application. To collect application-specific metrics, you need to use a library as a dependency and write code to collect it and all the essential context around it. The same can be said about traces. You need to retrieve the trace ID in your code entry point, send it in every cascaded call, again using a library or component, and make changes...