Zipkin is a distributed tracing system that collects and analyzes timing data crucial for troubleshooting latency issues in service architectures. This comprehensive tool offers both data collection and lookup functionalities. By inputting a trace ID in a log file, users can quickly jump to the relevant data.

Alternatively, queries can be made based on attributes like service, operation name, tags, and duration. Zipkin also provides summarized information, such as the percentage of time spent in a service and the success rate of operations. Additionally, the Zipkin UI offers a Dependency diagram, which displays the number of traced requests passing through each application.

This visualization aids in identifying aggregate behavior, including error paths and deprecated service calls. Applications must be instrumented to report trace data to Zipkin, typically through the configuration of a tracer or instrumentation library. Reporting options include HTTP, Kafka, Apache ActiveMQ, gRPC, and RabbitMQ.

The UI data can be stored in-memory or persistently using supported backends like Apache Cassandra or Elasticsearch. Try Zipkin today by checking out their Quickstart guide or explore the various tracer and instrumentation library options for your platform. Join the Zipkin Gitter chat channel to engage with the community and access the open-source code on GitHub