Zipkin is a distributed tracing system designed to help identify and resolve latency issues within service architectures. It facilitates the collection and lookup of timing data across distributed transactions.
Users can directly access trace information using a trace ID from log files or query data based on attributes like service name, operation, tags, and duration. The system provides summarized data, including the percentage of time spent in a service and operation success/failure status.
Key features include:
- Trace Visualization: Allows users to view detailed timing data for individual requests.
- Dependency Diagram: Presents a visual representation of how traced requests flow through different applications, aiding in the identification of error paths or calls to deprecated services.
- Flexible Data Reporting: Supports various methods for reporting trace data, including HTTP, Kafka, Apache ActiveMQ, gRPC, and RabbitMQ.
- Pluggable Storage Backends: Data can be stored in-memory or persistently using supported backends like Apache Cassandra or Elasticsearch.
To utilize Zipkin, applications must be instrumented, typically through a tracer or instrumentation library. The project offers quickstart guides, documentation on tracers, instrumentation, server extensions, and a vibrant community for support.
