What this book covers
Chapter 1, Observability 101, will go through the fundamentals of observability and discuss its building blocks and concepts. It provides you with the required terminology and introduces the vocabulary and concepts that you need to know relating to observability in a modern distributed application environment.
Chapter 2, Overview of the Observability Landscape on AWS, will help you understand the basic, foundational services and infrastructure-, application-, and machine learning-based tools available in AWS in terms of cloud-native observability and managed open source observability solutions.
Chapter 3, Gathering Operational Data and Alerting Using Amazon CloudWatch, helps you navigate the fundamentals of CloudWatch metrics, CloudWatch Logs, CloudWatch alarms, and CloudWatch dashboards. It provides hands-on experience in the installation of a unified agent and ingesting metrics and logs from EC2 instances and provides an overview of how to visualize them on a unified dashboard. It also introduces the requirement of the EventBridge service and event rules and how they would be used for fault monitoring.
Chapter 4, Implementing Distributed Tracing Using AWS X-Ray, will take you through what the requirement for distributed tracing is in modern applications and the fundamentals of the services offered by AWS relating to performance monitoring and distributed tracing.
Chapter 5, Insights into Operational Data with CloudWatch, will deep-dive into CloudWatch metrics and CloudWatch dashboards. We will see how to do more with less using CloudWatch Log Insights, CloudWatch Contributor Insights, and CloudWatch Application Insights, deriving operational intelligence automatically from log data and metrics and allowing for faster troubleshooting during operations.
Chapter 6, Observability for Containerized Applications on AWS, enables you to understand the setup of end-to-end containerized applications running on ECS and EKS to achieve observability.
Chapter 7, Observability for Serverless Applications on AWS, gives an overview of Lambda Insights and explores the data generated from it. You will understand how to gather metrics, logs, and traces from the serverless Lambda application and how they can be visualized as a unified dashboard for end-to-end operational visibility.
Chapter 8, End User Experience Monitoring on AWS, will take you through the importance of user experience monitoring. It provides an overview of how synthetic canaries can be implemented in understanding the user experience for a web application. We will provide an overview of how to collect metrics to capture real user behavior while interacting with a web application.
Chapter 9, Collecting Metrics and Traces Using OpenTelemetry, will discuss the existing SDKs, APIs, and AWS services that support organizations looking for ways to implement observability but using the open source ecosystem. It shows how AWS services can easily integrate with existing practices, helping to reduce much of the heavy lifting of deploying and managing those open source tools done by your own infrastructure team.
Chapter 10, Deploying and Configuring an Amazon Managed Service for Prometheus, enables you to understand the foundation of Amazon Managed Grafana and Prometheus and guides you in setting up the services, ingesting metrics, logs, and traces from the cloud-native observability services, and setting up advanced dashboards for operational visibility. It also discusses how to set up Prometheus monitoring for containerized workloads on AWS.
Chapter 11, Deploying the Elasticsearch, Logstash, and Kibana Stack Using Amazon OpenSearch Service, enables you to understand the foundation of Amazon OSS and guides you on how to set up the services and ingest logs and traces from your application workloads and set up dashboards for operational visibility.
Chapter 12, Augmenting the Human Operator with Amazon DevOps Guru, looks at AWS DevOps Guru, which is a service powered by machine learning that automatically extracts the relevant metrics about workloads and detects anomalies before they impact end users. In this chapter, you will learn how to use it to enrich the already deployed set of tools and use it as an advisor to detect issues and recommend remediations.
Chapter 13, Observability Best Practices at Scale, covers some patterns and recommendations on how to scale the observability of applications in complex organizations for workloads distributed in multiple accounts and regions.
Chapter 14, Be Well-Architected for Operational Excellence, looks at the AWS Well-Architected Framework, which provides guidelines on how to apply best practices of the design, delivery, and operations of AWS environments. Its Operational Excellence pillar and Management and Governance Lens include guidance on how to run workloads effectively and continuously improve operations. In this chapter, we discuss some of those principles and how they are interconnected with observability best practices.
Chapter 15, The Role of Observability in the Cloud Adoption Framework, looks at the Cloud Adoption Framework (CAF), which helps customers and users to digitally transform their businesses by leveraging the AWS experience and best practices. Among the CAF pillars are Management, Governance, and Operations. This chapter will discuss the role of observability in an organization’s transformation journey.
