The three pillars of observability are logs, metrics, and tracing. Most teams are able to handle logs and metrics, while proper tracing can still be a challenge. On this podcast, we talk with Yuri Shkuro, the creator of Jaeger, author of the book Mastering Distributed Tracing, and a software engineer at Uber, about how the Jaeger tracing backend implements the OpenTracing API to handle distributed tracing.

Why listen to the podcast:

- Jaeger is an open-source tracing backend, developed at Uber. It also has a collection of libraries that implement the OpenTracing API.

- At a high level, Jaeger is very similar to Zipkin, but Jaeger has features not available in Zipkin, including adaptive sampling and advanced visualization tools in the UI.

- Tracing is less expensive than logging because data is sampled. It also gives you a complete view of the system. You can see a macro view of the transaction, and how it interacted with dozens of microservices, while still being able to drill down into the details of one service.

- If you have only a handful of services, you can probably get away with logging and metrics, but once the complexity increases to dozens, hundreds, or thousands of microservices, you must have tracing.

- Tracing does not work with a black box approach to the application. You can't simply use a service mesh then add a tracing framework. You need correlation between a single request and all the subsequent requests that it generates. A service mesh still relies on the underlying components handling that correlation.

More on this: Quick scan our curated show notes on InfoQ https://bit.ly/2ZlvMyR

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