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
RabbitMQ's flexibility is also its testing challenge. You have exchanges, queues, bindings, routing keys, headers, and TTLs — all of which can be misconfigured in ways that swallow messages silently. A unit test that mocks the AmqpTemplate tells you nothing about whether your topology is correct. This post covers
CI/CD
Microservices CI/CD testing is a different problem from monolith testing. In a monolith, you run all the tests against all the code. In microservices, each service has its own repository, its own pipeline, and its own deploy cadence — but it depends on other services it doesn't control.
Chaos Engineering
Your microservices work in staging. They fall over in production. Chaos engineering is the practice of intentionally injecting failures to find weaknesses before users do. This guide covers two tools — Netflix Chaos Monkey (for instance/pod termination) and LitmusChaos (for Kubernetes-native chaos) — with a focus on meaningful experiments, not
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
Pact
Pact contract testing solves one of the hardest problems in microservices: how do you know that your services will work together without running a full integration test suite? This guide covers Pact from the ground up — what it is, how consumer-driven contracts work, and how to integrate Pact into
Pact
Consumer-driven contract testing with Pact is well-documented at the basics level: consumer writes expectations, provider verifies them.
Approval Testing
Microservice architectures distribute the blast radius of API changes across multiple teams and deployment pipelines.
Testing
Service meshes like Istio and Linkerd add a powerful layer of infrastructure between your microservices: traffic management, mTLS encryption, observability, and resilience features. But they also add complexity to testing. A service that works fine in unit tests may behave unexpectedly when running behind a mesh proxy. This guide covers
Testing
Microservices testing is fundamentally different from testing monolithic applications.
Testing
When a test fails in a distributed system, the error message tells you what happened but not where.
Testing
When teams develop microservices independently, the biggest risk is one team changing an API that another team depends on.