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

Augmenting the Human Operator with Amazon DevOps Guru

Today’s applications are becoming increasingly distributed and complex. We learned in the previous chapters that we need the three pillars of Metrics, Logs, and Traces to achieve good observability. To visualize the data that’s been collected, we need dashboards that can correlate data and provide a drill-down view of the application, such as the CloudWatch service map. While this model is effective for less complex systems, as the volume and diversity of data increase, it becomes challenging to identify and troubleshoot issues manually. Developers or administrators may face difficulties in locating and resolving problems as they need to correlate information manually from multiple sources and tools. The constant alerts and notifications from different tools can also lead to alarm fatigue and difficulty in determining the most pressing issue. That’s where DevOps Guru steps in and comes to the rescue.

DevOps...