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

This chapter allowed us to learn or review some concepts that will assist us when instrumenting applications using OpenTelemetry. We looked at the building blocks of distributed tracing, which will come in handy when we go through instrumenting our first application with OpenTelemetry in Chapter 4, Distributed Tracing – Tracing Code Execution. We also started analyzing tracing data using tools that developers and operators make use of every day.

We then switched to the metrics signal; first, looking at the minimal contents of a metric, then comparing different data types commonly used to produce metrics and their structures. Discussing exemplars gave us a brief introduction to how correlating metrics with traces can create a more complete picture of what is happening within a system by combining telemetry across signals.

Looking at log formats and searching through logs to find information about the demo application allowed us to get familiar with yet another tool...