AI agent that generates, runs, and maintains API tests using Gemini — produces OpenAPI documentation from real traffic, detects regressions across every commit, and flags contract violations before they reach production. Built on Vertex AI and Cloud Build.
We implement an end-to-end API testing and documentation agent on Google Cloud — using Gemini to generate and maintain test suites, observe traffic for documentation accuracy, and detect regressions and contract violations in CI. Test quality improves automatically as your APIs evolve.
Test suites fall out of sync with API changes, accumulate false positives, and give teams false confidence — until a production incident reveals the gap.
OpenAPI specs are manually maintained and lag behind actual API behaviour by weeks or months, causing integration failures for internal and external consumers.
In microservices architectures, upstream API changes silently break downstream consumers — discovered only when services fail in production rather than in the CI pipeline.
Gemini analyses your API spec or observes actual traffic and generates comprehensive test suites — positive, negative, boundary, and security tests — in your framework of choice.
Generates and updates OpenAPI documentation by observing real API behaviour — enriched with Gemini-written natural language descriptions for each endpoint and parameter.
Detects schema changes, status code regressions, and latency degradation across every commit — with Gemini-narrated reports explaining exactly what broke and which consumers are affected.
Consumer-driven contract tests (Pact) ensure upstream changes don't silently break downstream services — run automatically in CI before any merge.
When API behaviour changes, the agent updates test assertions automatically and opens a PR with a summary of what changed and why the tests were updated.
The agent supports OpenAPI 2.0 and 3.x (Swagger), gRPC proto files, and GraphQL schemas as input specifications. Generated tests are output as executable code in pytest, Jest/Supertest, Postman collections, k6 for load testing, or Pact for contract tests. For organisations without an existing spec, the agent can infer an OpenAPI spec by observing Apigee or Cloud Endpoints traffic.
Gemini analyses the API specification to identify: all endpoint paths and HTTP methods; all required and optional parameters with their types and constraints; all defined response schemas and status codes; authentication requirements; and example request/response pairs. It generates test cases covering the happy path, boundary values, invalid inputs, missing required fields, type mismatches, and authentication bypass attempts. For APIs without complete specs, it supplements with traffic-observed patterns.
The agent observes actual API traffic through Apigee or Cloud Endpoints and compares observed request/response shapes against the OpenAPI spec. When it detects divergence — a field present in responses but missing from the spec, a new endpoint receiving traffic, a changed response schema — it generates a spec update PR with Gemini-written changelog notes and a plain-language summary of what changed. Documentation is deployed as a static Redoc or Swagger UI site updated on every spec change.
The test agent integrates with Cloud Build, GitHub Actions, and GitLab CI as a pipeline step. On every PR, it runs the complete test suite against a staging deployment, reports pass/fail status with Gemini-narrated summaries, and blocks merges when contract violations or regressions are detected. Test results and API health metrics are stored in BigQuery and visualised in a Looker Studio quality dashboard.
Gemini generates and maintains your API tests, keeps your OpenAPI docs accurate, and catches contract violations before they reach production. Deployed in 3 weeks.