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

Introducing a little chaos

In normal circumstances, the real world is unpredictable enough that intentionally introducing problems may seem unnecessary. Accidental configuration changes, sharks chewing through undersea cables, and power outages affecting data centers are just a few events that have caused large-scale issues across the world. In distributed systems, in particular, dependencies can cause failures that may be difficult to account for during normal development.

Putting applications through various stress, load, functional, and integration tests before they are deployed to production can help predict their behavior to a large extent. However, some circumstances may be hard to reproduce outside of a production environment. A practice known as chaos engineering (https://principlesofchaos.org) allows engineers to learn and explore the behavior of a system. This is done by intentionally introducing new conditions into the system through experiments. The goal of these experiments...