Performance Test Design
Workload models, warm-up, think time, and the distribution the average hides.
4 to work through
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intermediate Multiple choice
A test must sustain 2000 requests per second against a service whose p50 is 120 ms, with 1 second of think time per virtual user between requests. Roughly how many virtual users does the generator need and what breaks first?
2 min answer -
advanced
A load test shows p99 latency of 120 ms at 2,000 requests per second. Production at the same rate shows 900 ms. Why?
2 min answer -
advanced
A team must load test at 10× normal traffic and a scaled-down environment tells them nothing. How is load testing in production done safely, and what does it find that nothing else does?
2 min answer -
advanced
What makes a performance test predictive of production behaviour, and what is the most common design flaw?
2 min answer
3 terms in this topic
Arrival Rate Model
Driving a load test by requests arriving per second regardless of how the system responds, rather than by a fixed number of virtual users.
conceptEmergent Failure
A failure that exists only above a particular absolute scale because it depends on a fixed threshold rather than a ratio - which is why scaled-down e…
practicePerformance Test Design
Constructing a load test whose result predicts production behaviour rather than merely producing numbers.
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.
Integration Test Boundaries
What sits inside a test's boundary, what is faked, and the confidence that follows.
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.
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.