API layer
Fast contract and data validation using Playwright without a browser, covering CRUD, filtering, response structure, and mutation correctness.
Case study
This project demonstrates how I structure layered automation in practice: broad fast feedback at lower layers, selective UI coverage where it earns its keep, and performance and mobile checks where they meaningfully reduce risk.
The goal is not maximum test count. The goal is maximum useful signal per test maintained, which is the difference between a healthy suite and a drag on delivery.
Context
Many automation suites fail for the same reasons: too much UI coverage, too little clarity on why a test exists, and no meaningful separation between fast feedback and slow confidence checks.
This project exists to show a different standard. It is a public, runnable example of how to combine frameworks and layers without losing the underlying strategy that keeps the suite maintainable.
The most mature automation strategy is usually not the broadest one. It is the one that places checks at the cheapest layer capable of giving trustworthy signal.
Architecture
Fast contract and data validation using Playwright without a browser, covering CRUD, filtering, response structure, and mutation correctness.
Browser tests target critical journeys, interaction patterns, and cases that only matter when exercised through a real interface.
Pure utility behavior is validated separately to keep business-logic feedback fast and avoid inflating higher-level suites with low-level checks.
k6 and Kaspresso show how the same separation-of-concerns thinking extends to latency budgets and Android coverage.
Patterns
Takeaways
This showcase is less about proving familiarity with tools and more about demonstrating judgement. The central point is that good automation architecture is a product of prioritisation, not just framework coverage.
Stack