June 2019
Intermediate to advanced
117 pages
2h 28m
English
Content preview from Microservices for Java Developers, 2nd Edition
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Chapter 7. Distributed Tracing with OpenTracing
In the previous chapters, we built a couple of microservices that connect to a backend. To access these two microservices, we also built an API Gateway. With just a few microservices, it’s easy to understand the topology and what calls what inside our cluster. However, in a real-world scenario the network of services will likely be far more complex, and therefore it will be much more complex to monitor the number of requests, the response time, and the path of a particular invocation. A simple invocation can traverse several microservices, and any particular issue will be hard to detect if we don’t have the ability to trace those invocations.
One things that we need to keep in mind is that distributed tracing should be technology-agnostic, because a Java microservice might invoke a .NET microservice that will call a Python microservice, and they should all accept and propagate the tracing information.
In 2010, Google published a paper about the project Dapper, which was designed to provide a solution for distributed tracing. This paper influenced several open source implementations, like Zipkin and Appdash. In 2015 the OpenTracing project was started, and in 2016 it became a hosted project of the Cloud Native Computing Foundation (CNCF).
OpenTracing is comprised of a set of standard APIs and a vendor-neutral framework for instrumentation. It supports the following platforms: Go, JavaScript, Java, Python, Ruby, PHP, Objective-C, ...
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