Integration Test Boundaries
What sits inside a test's boundary, what is faked, and the confidence that follows.
5 to work through
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intermediate
A team replaces every in-process fake with the real dependency in a container, and defect escape rate falls. What have they bought and when does the bill arrive?
2 min answer -
intermediate
For a service with a database, a message broker and two downstream HTTP dependencies, where do you draw the integration test boundary?
2 min answer -
intermediate
Where should the boundary of an integration test sit, and what is the common mistake?
2 min answer -
advanced
Nine teams share one integration environment where all 34 services run together. The 900-test suite takes three hours and a red run is usually somebody else's deploy rather than a defect. You have been asked to move to per-service tests with virtualised dependencies without interrupting the fortnightly release train. What is the sequence, and where can it go wrong?
3 min answer -
advanced
Where should integration tests draw their boundary - at the service, at the database, or at the external dependency?
2 min answer
2 terms in this topic
Integration Test Boundary
The deliberate choice of what a test includes and what it stubs, which determines both what the test can detect and what it costs.
conceptTest Double Boundary
The line inside a test between what is real and what is substituted, which determines exactly what the test can and cannot prove.
Neighbouring topics
Testing & Quality Architecture
General material on designing a testing strategy as an architectural concern.
Test Architecture Strategy
Choosing what to verify where, given the failure modes that actually occur.
Test Pyramid Shapes
Pyramid, trophy and honeycomb, and the system properties that justify each shape.
Contract Testing at Scale
Keeping dozens of services compatible without an environment that runs all of them.
Consumer-Driven Contracts
Consumers declaring what they rely on, and providers verifying against those declarations.
Test Data Management
Realistic data without copying production personal data into a weaker environment.
Synthetic Data
Generating data with the shape and edge cases of the real thing, and where it misleads.
Environment Parity
The differences between staging and production that decide which bugs survive to release.
Service Virtualisation
Standing in for a dependency you cannot call, and keeping the stand-in honest.
End-to-End Test Economics
Why broad end-to-end suites get slow, flaky and abandoned, and what to keep.
Non-Functional Test Strategy
Testing availability, latency, security and recovery rather than only behaviour.
Performance Test Design
Workload models, warm-up, think time, and the distribution the average hides.
Chaos as a Test
Fault injection with a hypothesis, a blast radius and an abort condition.
Security Testing in the Pipeline
SAST, DAST, dependency and secret scanning, and what to do with the findings.
Accessibility Testing
Automated checks, their ceiling, and the manual testing that has to sit above it.
Mutation Testing
Measuring whether tests would actually notice a defect, not just cover a line.
Flaky Test Management
Quarantine, detection, and the trust a suite loses once red stops meaning broken.
Testing in Production
Synthetic transactions, dark launches and shadow traffic, done deliberately and safely.
Quality Gates
Thresholds that block a release, who may override them, and how they decay.