Testing a microservices system requires different strategies at different levels. The testing pyramid principle applies, but the types of tests at each level differ from a monolithic application.
Consumer-driven contract tests
Consumer-driven contract testing (Pact framework) allows services to be tested independently by verifying that the interactions between a consumer and a provider match agreed contracts. The consumer writes tests that define what it expects from the provider; these are converted to a Pact contract file. The provider verifies that it satisfies all consumer contracts. This enables independent deployment: if the provider satisfies all contracts, consumers can safely upgrade.
Integration tests with Testcontainers
Testcontainers launches real Docker containers (databases, message queues, caches) for integration tests, providing realistic test environments without mocking. A test that needs PostgreSQL gets a real PostgreSQL container spun up before the test and torn down after. The Testcontainers library is available for .NET, Java, Go, and Node.js. The cost is test time (container startup); the benefit is tests that catch integration bugs that mocks would not.
Component tests over end-to-end
End-to-end tests that spin up the full microservices stack are slow, flaky, and expensive to maintain. Component tests (testing a single service with all its external dependencies replaced by test doubles or Testcontainers instances) provide similar coverage at lower cost and higher reliability. The portfolio: many unit tests, many component tests, few contract tests, minimal end-to-end tests covering only the most critical user journeys.
Test data management in microservices
Test data management in a microservices system is complex: each service owns its data, and data seeding for integration tests must respect the ownership boundaries. The patterns: test-specific seed data loaded via service APIs (not directly to the database, which violates service data ownership), event replay for eventual consistency tests, and database cleanup after each test using transaction rollback or truncation scripts. Shared test data across tests creates order dependencies and flakiness.