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

Overview of Amazon DevOps Guru

Amazon DevOps Guru is an easy-to-use service with no configuration or no prior ML experience requirements for delivering anomaly detection and observability insights. It helps with continuously analyzing the streams of metrics and logs from disparate data sources and understanding the application’s behavior in an automated way by leveraging ML. Amazon DevOps Guru helps in accelerating the resolution of issues quickly by providing ML-powered insights and recommendations. It also helps reduce alarm fatigue by automatically correlating and grouping related anomalies. It is easy to scale and maintain with minimum or no intervention when new AWS resources are added.

DevOps Guru Insights, a component of the DevOps Guru service, automates the process of setting alarms and thresholds and provides clear, actionable guidance to aid developers and operations teams in quickly identifying and addressing the underlying cause of an issue.

The DevOps Guru...