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Cloud-Native Observability with OpenTelemetry

Cloud-Native Observability with OpenTelemetry

By : Boten
4.8 (8)
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Cloud-Native Observability with OpenTelemetry

Cloud-Native Observability with OpenTelemetry

4.8 (8)
By: 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)
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1
Section 1: The Basics
3
Chapter 2: OpenTelemetry Signals – Traces, Metrics, and Logs
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5
Section 2: Instrumenting an Application
10
Section 3: Using Telemetry Data

Traces

Distributed tracing is the foundation behind the tracing signal of OpenTelemetry. A distributed trace is a series of event data generated at various points throughout a system tied together via a unique identifier. This identifier is propagated across all components responsible for any operation required to complete the request, allowing each operation to associate the event data to the originating request. The following diagram gives us a simplified example of what a single request may look like when ordering groceries through an app:

Figure 2.5 – Example request through a simplified ordering system

Each trace represents a unique request through a system that can be either synchronous or asynchronous. Synchronous requests occur in sequence with each unit of work completed before continuing. An example of a synchronous request may be of a client application making a call to a server and waiting or blocking until a response is returned before...

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