Book Image

Cloud-Native Observability with OpenTelemetry

By : Alex Boten
Book Image

Cloud-Native Observability with OpenTelemetry

By: Alex Boten

Overview of this book

Cloud-Native Observability with OpenTelemetry is a guide to helping you look for answers to questions about your applications. This book teaches you how to produce telemetry from your applications using an open standard to retain control of data. OpenTelemetry provides the tools necessary for you to gain visibility into the performance of your services. It allows you to instrument your application code through vendor-neutral APIs, libraries and tools. By reading Cloud-Native Observability with OpenTelemetry, you’ll learn about the concepts and signals of OpenTelemetry - traces, metrics, and logs. You’ll practice producing telemetry for these signals by configuring and instrumenting a distributed cloud-native application using the OpenTelemetry API. The book also guides you through deploying the collector, as well as telemetry backends necessary to help you understand what to do with the data once it's emitted. You’ll look at various examples of how to identify application performance issues through telemetry. By analyzing telemetry, you’ll also be able to better understand how an observable application can improve the software development life cycle. By the end of this book, you’ll be well-versed with OpenTelemetry, be able to instrument services using the OpenTelemetry API to produce distributed traces, metrics and logs, and more.
Table of Contents (17 chapters)
1
Section 1: The Basics
3
Chapter 2: OpenTelemetry Signals – Traces, Metrics, and Logs
5
Section 2: Instrumenting an Application
10
Section 3: Using Telemetry Data

Summary

Learning to navigate telemetry data produced by systems comfortably takes time. Even with years of experience, the most knowledgeable engineers can still be puzzled by unexpected changes in observability data. The more time spent getting comfortable with the tools, the quicker it will be to get to the bottom of just what caused changes in behavior.

The tools and techniques described in this chapter can be used repeatedly to better understand exactly what a system is doing. With chaos engineering practices, we can improve the resilience of our systems by identifying areas that can be improved upon under controlled circumstances. By methodically experimenting and observing the results from our hypotheses, we can measure the improvements as we're making them.

Many tools are available for experimenting and simulating failures; learning how to use these tools can be a powerful addition to any engineer's toolset. As we worked our way through the vast amount of data...