Case Study · QA Engineering & DevOps

From zero QA process to full automation —
then 10× faster with Playwright.

A fast-growing product company had the team and the clients but none of the engineering process. No CI/CD, no structured QA, no automation — just a fast-moving codebase that relied on manual testing and developer judgment before every release. We built the entire QA discipline from scratch, then led the migration from thousands of Selenium tests to Playwright — cutting execution time by 90% and unifying the dev and QA tech stack into a single shared codebase.

DomainQA Engineering & DevOps
EngagementProcess Consulting & Engineering
ClientConfidential
BeforeNo process
Code written
Manual testing (sometimes)
Deploy to prod
🤞 Hope for the best
→
AfterFull CI/CD
⎇Feature branch + PR
⚙Build + static analysis
✓Unit + API tests
✓Playwright E2E suite
→Deploy to staging
✓Smoke + sign-off
🚀Deploy to production
0→∞
QA process built from nothing

CI/CD, version control, Jira, release management, and a full automation framework — all from a standing start

÷10
Test execution time

Full regression suite cut to one-tenth of the original Selenium runtime through Playwright's native parallelism

1
Shared tech stack

Dev and QA now write in the same language — TypeScript — on the same codebase. No translation layer between teams

↑
Release cadence

Automated regression and sign-off cycle collapsed from days to hours, enabling rapid, confident releases

Phase 1

Building QA from nothing

CI/CD pipeline, version control process, Jira-based project management, release management, and a full Java + Selenium + BDD automation framework — built from the ground up for a team that had none of it.

JavaSeleniumCucumber BDDREST AssuredGitHub ActionsJira
→
Phase 2

Selenium → Playwright

Thousands of Java Selenium tests migrated to TypeScript Playwright. Execution time cut to one-tenth. Dev and QA unified on a single language and codebase. Flaky tests eliminated.

PlaywrightTypeScriptNode.jsAllure ReportsTrace Viewer
Phase 1

Building QA discipline from a standing start.

The team was talented and fast-moving — but without process, speed creates instability. Every deliverable in Phase 1 was chosen to reduce risk while preserving the team's ability to ship quickly.

Process & Tooling
  • Jira set up for feature tracking, bug management, sprint planning, and release notes
  • Git branching strategy defined — feature branches, PR reviews, protected main
  • Environments defined: dev, QA, staging, production with promotion gates between each
  • Release management process with versioned tags, changelogs, and sign-off checklists
CI/CD Pipeline
  • Build pipeline triggered on every PR — compile, unit tests, static analysis
  • Automated test suite execution on merge to main and staging branches
  • Deployment pipeline to staging on green build, production on manual approval
  • Slack and email notifications for build failures, test failures, and deployments
Test Automation Framework
  • Java + Selenium + Cucumber BDD framework built from scratch
  • Feature files written in Gherkin — business-readable, dev/QA/product aligned
  • Page Object Model pattern for UI tests — maintainable, no selector duplication
  • REST Assured for API automation — contract tests, integration tests, regression suite
Test Coverage
  • Core user journeys automated end-to-end across all major flows
  • API layer tested independently — response schemas, status codes, data integrity
  • Regression suite scoped to cover every release without manual re-testing
  • Smoke suite for post-deployment verification — runs in under 10 minutes
Phase 2 · The Case for Playwright

Why Selenium had to go.

The Selenium suite worked — but it was brittle, slow, and written in a language that the application developers could not read. Playwright solved all three problems simultaneously.

Selenium + Java
Playwright + TypeScript
Auto-wait — no more flaky tests
Explicit and implicit waits scattered throughout the codebase. Race conditions between page loads and element readiness caused intermittent failures that were hard to diagnose and impossible to reliably reproduce.
Playwright waits for elements to be actionable before interacting — visible, stable, enabled, not obscured. Flaky waits were eliminated wholesale. The test suite became deterministic.
Execution speed — 10× faster
Full regression suite took hours to run. Each test spun up a browser session sequentially. Parallelism was possible but complex to configure and required additional infrastructure.
Native parallelism across workers. Tests run concurrently by default. The same regression suite that took hours in Selenium runs in a fraction of the time. CI feedback loops tightened from hours to minutes.
Unified tech stack
Tests written in Java. Application written in JavaScript/TypeScript. Two separate codebases, two languages, two sets of tooling. Developers could not easily read or debug QA test failures. QA could not contribute to unit tests.
Tests written in TypeScript — same language as the application. Developers can open a failing test, read it, and debug it without context-switching. QA engineers contribute directly to the application's test infrastructure.
Network interception & API mocking
No native ability to intercept or mock network requests. Integration with the real API was required for every test, making test data setup complex and tests slow to stabilise.
Built-in network interception. Tests can mock specific API responses, simulate errors, test loading states, and control data independently of the backend — making tests faster and more targeted.
Multi-browser & device coverage
Required separate WebDriver binaries per browser. Browser version management was a recurring maintenance overhead. Mobile testing required separate frameworks.
Single installation covers Chromium, Firefox, and WebKit. Device emulation built in. Mobile viewports, touch events, and geolocation all configurable per test with no additional setup.
Execution Time

Same tests. One-tenth the time.

Selenium regression suite
~4 hours
Sequential execution · Java WebDriver · Manual wait management
Playwright regression suite
~24 minutes
Native parallelism · Auto-wait · TypeScript · No flakiness overhead
90%reduction in CI regression time — from hours to minutes on every merge
Unified Tech Stack

One language. Two teams. No translation layer.

Before the migration, there was an invisible wall between development and QA. The application was written in JavaScript and TypeScript. The tests were written in Java. A developer looking at a failing QA test had to context-switch into a completely different language, toolchain, and set of idioms just to understand what the test was asserting.

The result was a predictable pattern: QA investigated all test failures, developers waited for QA to triage, and the feedback loop stretched. QA was a bottleneck — not by fault, but by structure.

With Playwright and TypeScript, the test code lives in the same ecosystem as the application code. A developer can open a failing test, understand it immediately, and fix it or flag it in minutes. QA engineers who understand the application framework can contribute to developer unit tests. The boundary between the two disciplines became permeable — and the whole team became more effective because of it.

Developers
Application codeUnit testsE2E test debugging ✓
TypeScript
Shared language
QA Engineers
E2E testsAPI testsUnit test contributions ✓
Before — two separate languages
Dev: JavaScript/TS⟵ wall ⟶QA: Java
Migration Approach

Thousands of tests. No big bang.

Migrating a large test suite all at once is a recipe for a regression gap. We migrated in parallel — keeping Selenium live until Playwright proved parity, area by area.

01

Audit and prioritise the Selenium suite

Before migrating a single test, we audited the full Selenium suite — categorising tests by stability, execution frequency, business criticality, and maintenance cost. High-value, frequently-run tests were migrated first. Tests that were already flaky in Selenium were redesigned during migration rather than ported as-is.

02

Framework scaffold in TypeScript

A new Playwright framework was scaffolded in TypeScript with the same structural patterns the QA team already understood — Page Object Model, test data factories, environment configuration. The familiar structure meant the team could contribute from day one without learning a completely new paradigm.

03

Parallel run period

For a defined period, both suites ran in CI. Playwright results were compared against Selenium results on each build. Discrepancies were investigated and resolved. When a Playwright test consistently passed where the Selenium equivalent was flaky, the Selenium test was retired rather than investigated.

04

Developer onboarding

Once the Playwright suite reached parity, the application developers were onboarded onto the test codebase. They could now read failing tests, add assertions to existing tests, and write new tests for features as they built them. The handoff from QA to dev for test ownership happened gradually, not in a single event.

05

Selenium decommission

Selenium was decommissioned section by section as Playwright coverage reached parity for each area. The CI pipeline was updated to remove Selenium steps incrementally. By the end, the old Java framework was removed entirely and the build time dropped dramatically.

Technologies

The full stack across both phases

Phase 1 · Selenium stack
Java
Test automation language — Phase 1
Selenium
Browser automation framework — Phase 1
Cucumber (BDD)
Gherkin feature files, business-readable test specs
REST Assured
API automation — contract and integration tests
TestNG / JUnit
Test runner, assertion library, report generation
Maven
Build and dependency management for Java test suite
Phase 2 · Playwright stack
Playwright
Browser automation — fast, reliable, natively parallel
TypeScript
Test language — shared with the application codebase
Node.js
Runtime for Playwright test execution
Allure Reports
Rich test reporting with screenshots and traces
Playwright Trace Viewer
Step-by-step debugging of test failures
msw / network mock
Network interception for isolated component tests
Process & CI/CD tooling
Jira
Feature tracking, bug management, sprint boards
GitHub Actions
CI/CD pipeline — build, test, deploy
Git
Branching strategy, PR reviews, protected branches
Slack webhooks
Build and deployment notifications
SonarQube
Static code analysis and code quality gates
Docker
Containerised test environments for consistent execution
Work with us

Shipping fast but testing slow?

Whether you need to build a QA function from scratch, modernise an existing Selenium suite, or establish CI/CD discipline — we have done it at scale and can do it for your team.