Summary

In this chapter, we've looked at what observability is, and the challenges it can solve as regards the use of cloud-native applications. By exploring the different mechanisms available to generate telemetry and improve the observability of applications, we were also able to gain an understanding of how the observability landscape has evolved, as well as where some challenges remain.

Exploring the history behind the OpenTelemetry project gave us an understanding of the origin of the project and its goals. We then familiarized ourselves with the components forming tracing, metrics, logging signals, and pipelines to give us the terminology and building blocks needed to start producing telemetry using OpenTelemetry. This learning will allow us to tackle the first challenge of observability – producing high-quality telemetry. Understanding resources and context propagation will help us correlate events across services and signals to allow us to tackle the second challenge – connecting the data to better understand systems.

Let's now take a closer look at how this all works together in practice. In the next chapter, we will dive deeper into the concepts of distributed tracing, metrics, logs, and semantic conventions by launching a grocery store application instrumented with OpenTelemetry. We will then explore the telemetry generated by this distributed system.