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

Metrics

Just as distributed traces do, metrics provide information about the state of a running system to developers and operators. The data collected via metrics can be aggregated over time to identify trends and patterns in applications graphed through various tools and visualizations. The term metrics has a broad range of applications as they can capture low-level system metrics such as CPU cycles, or higher-level details such as the number of blue sweaters sold today. These examples would be helpful to different groups in an organization.

Additionally, metrics are critical to monitoring the health of an application and deciding when an on-call engineer should be alerted. They form the basis of service level indicators (SLIs) (https://en.wikipedia.org/wiki/Service_level_indicator) that measure the performance of an application. These indicators are then used to set service level objectives (SLOs) (https://en.wikipedia.org/wiki/Service-level_objective) that organizations use to...