🔍Zipkin

NEW

A distributed tracing system that collects and visualizes timing data to troubleshoot latency across microservices.

DESCRIPTION

Zipkin provides trace collection, storage, and a web UI to analyze request propagation and latency. It originated at Twitter and remains widely used for tracing in Java and polyglot stacks. Zipkin integrates with OpenTelemetry exporters and popular frameworks like Spring Cloud Sleuth. It supports various transports and storage options, making it flexible for on-premise or cloud deployments.

ALTERNATIVE DEFINITIONS

Zipkin

Zipkin is a distributed tracing system.

Direct, concise statement of purpose.

Source

OpenZipkin

Zipkin is a distributed tracing system that helps gather timing data needed to troubleshoot latency problems in microservice architectures.

Stresses latency troubleshooting and microservices focus.

Source

RELATED TERMS

Tracing OpenTelemetry OpenTracing Spring Cloud Sleuth Prometheus Microservices Service Mesh W3C Trace Context AWS X-Ray

COMPETING TERMS

Jaeger Grafana Tempo

RELATIONS

• Conforms to: OpenTelemetry OpenTracing

KNOWLEDGE AREAS

Observability & Telemetry Software Engineering Platform & Tooling Cloud

TARGET AUDIENCE

DevOps Engineer Software Developer Solution Architect MLOps Engineer Cloud Architect IT Manager

EXTERNAL SOURCES

• Wikipedia - Zipkin (software)
• Zipkin - Quickstart to run Zipkin
• OpenTelemetry - Zipkin exporters for OTEL
• Spring - Sleuth integration with Zipkin

TOP QUESTIONS

Why choose Zipkin for tracing?

Zipkin is lightweight, widely integrated, and easy to deploy. Its simplicity makes it attractive for teams starting with distributed tracing.

Category: Relevancy

How does Zipkin store traces?

Zipkin supports storage backends like Elasticsearch, Cassandra, and in-memory for development, balancing scale and simplicity.

Category: Requirements

How does Zipkin compare to Jaeger?

Both visualize distributed traces; Jaeger often emphasizes enterprise-scale backends and CNCF ecosystem, while Zipkin is praised for simplicity and Java ecosystem integration.

Category: Alternatives

How to instrument apps for Zipkin?

Use OpenTelemetry or framework-specific integrations to emit spans and set Zipkin exporters or collectors as the destination.

Category: How-to

What is a common Zipkin deployment pattern?

Run a collector and UI service, connect to a persistent store, and configure services to export spans over HTTP or Kafka.

Category: Example

What pitfalls occur with Zipkin tracing?

Missing propagation headers break trace continuity; inconsistent naming hinders analysis. Align on standard trace context and naming conventions.

Category: Mistakes

How does Zipkin handle sampling?

Sampling is typically configured at the client or instrumentation level, controlling which requests produce spans to manage overhead.

Category: Management

What risks come with high trace volume in Zipkin?

Unbounded spans can increase latency and storage costs. Planning retention and sampling avoids operational overload.

Category: Risks

Where to learn Zipkin basics?

Start with the Zipkin quickstart, then integrate a single service, validate headers, and expand to end-to-end traces.

Category: Learning