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AWS Observability Handbook

AWS Observability Handbook

By : Phani Kumar Lingamallu, Fabio Oliveira
4.7 (7)
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AWS Observability Handbook

AWS Observability Handbook

4.7 (7)
By: Phani Kumar Lingamallu, Fabio 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)
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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

Implementing Distributed Tracing Using AWS X-Ray

AWS X-Ray is a versatile and powerful service that allows for detailed analysis and debugging of distributed applications. It can be used to investigate a wide range of applications running on various types of computing on AWS, including EC2 and Serverless. However, its real strength lies in its ability to seamlessly integrate and provide real-time visibility into each service’s performance in a microservices architecture. In the microservice architecture, a single request from a user can trigger a complex series of interactions between multiple services. AWS X-Ray helps you understand every aspect of the request-response cycle by tracing each step and allowing you to identify performance bottlenecks and errors, which help you address critical issues that might be impacting the user experience.

In a complex microservices architecture, diagnosing issues can be an incredibly challenging task. Without AWS X-Ray, it can be a time...

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