Apache Zipkin
Apache Zipkin is a distributed tracing system that helps gather timing data needed to troubleshoot latency problems in service architectures. It manages both the collection and lookup of tracing data through a collector and query service. Zipkin provides a REST API, web UI, and multiple storage backends (Cassandra, Elasticsearch, MySQL). It supports the B3 propagation format and is compatible with OpenZipkin instrumentation libraries. Originally created at Twitter, it is now maintained as an open-source project.
Limited machine-readable signal and partial portal coverage — documentation a human can read, but little a machine or agent can consume without scraping.
API Evangelist profiles Apache Zipkin the way a machine reads it — 26 machine-readable artifacts across 4 APIs, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.
Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — Apache Zipkin scores 44.2/100 (thin), with a separate agent-readiness read of 39/100 (agent aware). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.
Kin Score
This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.
Kin Score
How this is scored →scored 2026-07-27 · rubric v0.5
How we profile Apache Zipkin
Each block below is one kind of artifact we hold for Apache Zipkin. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.
APIs 4
Each API is captured as its own OpenAPI definition — every operation, parameter, and response. This is the single most useful machine-readable description of what an API does, and it's what lets us score, lint, mock, and generate against it without asking the provider for anything.
Individual APIs this provider publishes, each with its own machine-readable definition.
Apache Zipkin autocomplete API
Tag key/value autocompletion
Apache Zipkin services API
Service discovery and dependency links
Apache Zipkin spans API
Ingest spans and query span names
Apache Zipkin traces API
Query trace data
Open Collections 1
Open, tool-agnostic collections carry the same runnable value as Postman without locking you to one client — the portable, forkable form of the same exercise.
Open, tool-agnostic API collections (OpenAPI-derived and Bruno).
Zipkin API
OPEN COLLECTIONPricing Plans 1
Pricing is part of the interface. Machine-readable plans tell you what a tier costs and includes before you commit — one of the six things the Kin Score reads for commercial clarity.
Published pricing tiers and plan structures.
Rate Limits 1
Rate limits are the difference between a demo that works and a production integration that doesn't fall over. Publishing them is an operational-transparency signal — and a hard requirement for any agent that plans its own throughput.
Documented rate limits and quota policies.
Apache Zipkin Rate Limits
RATE LIMITSFinOps 1
Cost, billing, and metering signals let a buyer model the financial operations of an API before it's live. We profile them for the same reason we profile pricing: the money is part of the contract.
Cost, billing, and metering signals for API financial operations.
Apache Zipkin Finops
FINOPSFeatures 6
The notable capabilities this provider advertises, captured as structured features so they can be searched and compared instead of read one landing page at a time.
Notable capabilities this provider offers.
Distributed Trace Collection
Collect timing and metadata for distributed service calls with B3 propagation headers.
Trace Query and Visualization
Web UI and REST API for searching and visualizing distributed traces with latency analysis.
Service Dependency Graph
Automatic service call graph generation from collected trace data.
Multiple Storage Backends
Cassandra, Elasticsearch, and MySQL storage backends for different scale requirements.
OpenTelemetry Compatible
Accepts OTLP/Zipkin spans from OpenTelemetry instrumented services.
B3 Propagation
Standard B3 trace propagation headers for distributed context passing across services.
Security Posture 1
Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Agentic Access 1
An x-agentic-access contract marks which operations are safe for an agent to run on its own and which need a human in the loop. It is the difference between an API an agent can use and one it can use safely.
Recommended x-agentic-access execution contracts for AI agents.
Use Cases 4
What developers actually build with this provider — captured so the catalogue answers 'what is this for', not just 'what does this expose'.
What developers build with this provider.
Microservices Latency Troubleshooting
Identify bottlenecks and slow service calls in distributed architectures.
Service Dependency Mapping
Automatically discover and visualize service-to-service call graphs.
Performance Regression Detection
Compare trace data before and after deployments to detect performance regressions.
Root Cause Analysis
Follow distributed call chains to identify the root cause of errors and failures.
Integrations 6
Pre-built integrations with other platforms tell you where this provider already fits in a stack.
Pre-built integrations with other platforms and tools.
Spring Cloud Sleuth
Spring Boot auto-instrumentation for trace propagation and Zipkin reporting.
Brave
Java instrumentation library (Brave) for adding Zipkin tracing to Java applications.
Elasticsearch
Elasticsearch storage backend for scalable trace data storage and search.
Apache Cassandra
Cassandra storage backend for high-volume trace data.
OpenTelemetry
OpenTelemetry Zipkin exporter for reporting OTLP traces to Zipkin.
Kafka
Kafka collector for ingesting spans from high-throughput microservice architectures.
Resources
Every other property we hold for Apache Zipkin — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.
Get Started 2
Portal, sign-up, and the first successful call
Documentation 1
Reference material describing how the API behaves
Agent Surfaces 1
MCP servers, agent skills, and machine-readable catalogs
Build 3
SDKs, sample code, and the tooling you integrate with
Access & Security 1
Authentication, authorization, and security posture
Operate 2
Status, limits, changes, and where to get help
Commercial 1
Pricing, plans, and the legal terms of use
← All providers · Data indexed from github.com/api-evangelist/apache-zipkin · machine-readable index on apis.io