Testing
Micro-frontend teams ship independently. That's the whole point. But independent shipping only works if every team respects the interfaces their code exposes and consumes. Without enforcement, breaking changes slip through: a prop gets renamed, an event payload changes shape, a shared utility gets a new required parameter.
Testing
Most contract testing material focuses on REST APIs. But many modern systems communicate through message queues — Kafka, RabbitMQ, SNS/SQS, or custom event buses. The same integration problems that contract testing solves for HTTP — a producer changes a message schema and consumers silently break — exist in event-driven architectures, and
Contract Testing
Contract testing only protects you if it runs in CI/CD. A manually run Pact verification that isn't blocking deploys is just documentation. This guide shows how to wire contract testing into a real CI/CD pipeline: consumer tests publish pacts on every build, providers verify on every
Testing
Integration tests are slow, brittle, and expensive to maintain. You spin up multiple services, wire them together in a test environment, and hope that everything behaves the way it did last Tuesday. When a test fails, you spend twenty minutes figuring out whether the problem is in the consumer, the
Contract Testing
Consumer-driven contract testing is a testing approach where each consumer of an API defines what it expects from the provider, those expectations are captured as a contract, and the provider verifies it honors every consumer's contract before deploying. It prevents the most common microservices failure mode: API
Testing
Writing consumer Pact tests is the easy part. Provider verification is where teams run into real friction — database state, authentication middleware, third-party dependencies, and slow test setup all become problems at once. This post covers practical strategies for handling each of these. The Core Challenge: Provider State Every Pact
Testing
GraphQL presents a unique challenge for contract testing. REST APIs have stable URL paths and HTTP verbs — easy to record as contracts. GraphQL routes everything through a single endpoint (POST /graphql) with the operation in the request body. The schema is flexible and self-describing. So where does contract testing
Contract Testing
Pact and Spring Cloud Contract both implement consumer-driven contract testing but with a fundamental philosophical difference: in Pact, the consumer owns and writes the contract; in Spring Cloud Contract, the provider writes the contract and generates consumer stubs from it. This difference determines which tool fits your team'
Testing
Provider verification is the other half of the contract testing equation. Consumers write pacts that describe what they need. Providers verify those pacts against their real implementation. This guide covers the Python side of that workflow using pact-python and pytest. How Provider Verification Works When you run provider verification,
Contract Testing
Pact and OpenAPI both prevent API integration failures, but they solve different parts of the problem. OpenAPI defines the contract — the shape of requests and responses. Pact verifies that specific consumer interactions are honored by the provider. Used together, they cover each other's blind spots. This guide shows
Testing
HTTP contract testing is well understood. You define the request and response, Pact records them as a contract, and the provider verifies it. But microservices don't only communicate over HTTP — they publish and consume events through Kafka topics, SQS queues, and SNS topics. Those async channels need contracts
Contract Testing
Pact is a consumer-driven contract testing library that lets you define what a consumer (e.g., a frontend app or microservice) expects from a provider (e.g., an API), generate a contract file from those expectations, and verify the provider actually fulfills them — without spinning up both services at