From Selenium to Playwright: A Safe and Scalable Migration Blueprint for Modern QA

For a decade, Selenium was the undisputed standard for UI test automation. It powered thousands of QA organizations, from scrappy startups to global enterprises. But what carried us through the 2010s has become the anchor of the 2020s. Scaling Selenium today feels like running a marathon in ankle weights: slow runtimes, brittle tests, dated infrastructure, and a lack of intelligence to meet the demands of cloud-native, AI-driven delivery pipelines.

If you’re reading this, you’re probably feeling the pain: a Selenium repo that’s too large to ignore but too fragile to scale. The good news? There is a way out. Playwright, with its modern architecture and first-class tooling, offers a chance to reboot your automation practice around speed, stability, and intelligence.

But the hard question remains: how do you migrate a large Selenium estate safely and efficiently; without disrupting your teams, risking production confidence, or stalling delivery?

This post lays out a practical migration playbook: from phased deprecation of Selenium, to setting up secure CI/CD, to layering on test intelligence and executive-level reporting. By the end, you’ll see how to go from brittle Selenium scripts to a button-click Playwright pipeline that even your VP of Product can trigger in Allure TestOps.

Why Migrate at All?

Let’s state the obvious: Selenium is not “bad.” It’s just a product of its era. Its design assumptions; remote drivers, XML-heavy configs, community plug-ins; reflected the browser ecosystem of 2011. Today’s demands look radically different:

• Parallelism by default → Playwright supports test sharding, multi-browser runs, and headless execution with minimal setup. Selenium often requires complex infra (grid, containers) to achieve the same.
• Modern APIs → Selenium scripts read like plumbing. Playwright offers concise, chainable APIs, automatic waits, and first-class selectors.
• CI/CD native → Selenium grew up in a world of Jenkins masters. Playwright was designed for GitHub Actions, AWS CodeBuild, and containerized runners.
• Intelligence ready → Selenium logs require parsing and stitching. Playwright integrates seamlessly with reporting tools like Allure, paving the way for analytics and AI-driven insights.

The migration isn’t just about faster tests. It’s about building a modern Quality Engineering scaffold that can scale with your company.

Phase 1: Scaffolding Playwright Without Breaking Selenium

A common mistake is to “big bang” the migration; rewriting hundreds or thousands of Selenium tests in one shot. That path leads to outages, confidence gaps, and frustrated teams. Instead, treat this as a scaffold project:

1. Stand up a new Playwright repo
   • Separate from the Selenium codebase to avoid dependency collisions.
   • Include a shared utilities layer (selectors, fixtures, API helpers).
   • Enforce deterministic ordering of tests to prepare for sharding.
2. Connect Playwright CI/CD early
   • GitHub Actions: simple to bootstrap, good for developer visibility.
   • AWS CodeBuild/ECS: required for HIPAA/SOC2 compliance, keeps secrets in AWS Secrets Manager.
   • Best practice: run tests inside hardened containers pulled from ECR.
3. Run smoke tests in parallel
   • Start with 10–15 UI smoke tests covering critical paths.
   • Execute daily on CI while Selenium still runs in parallel.
   • Compare pass/fail trends; executives can see “Playwright stability vs Selenium” from day one.
4. Implement reporting from the start
   • Allure TestOps as the central hub.
   • Pipe Playwright runs into Allure dashboards.
   • Tag tests by module, persona, risk, and environment.

Key principle: Selenium is still the production sentinel; Playwright is the “shadow pipeline.” This de-risks adoption.

Phase 2: Expanding Coverage and Building Confidence

Once Playwright smoke tests are stable, it’s time to scale coverage without breaking teams’ workflows.

1. Identify golden paths
   • Audit manual and Selenium suites.
   • Tag high-risk, high-value user flows (checkout, login, patient data access).
   • Prioritize these for Playwright migration.
2. Automate aggressively, retire cautiously
   • For each Selenium test migrated, keep the Selenium version active until Playwright runs green in CI for 2–3 weeks.
   • Mark Selenium versions as “deprecated” in your TCM.
   • Communicate status with developers so they trust the transition.
3. Unify manual and automation tagging
   • Even if you don’t migrate Zephyr/Xray yet, adopt a consistent risk-based schema:
     • P0 = must never break
     • P1 = high value, run daily
     • P2 = regression, run weekly
   • This schema lets you align manual regression and automation coverage for clarity.
4. Expand CI/CD footprint
   • Add regression jobs that run nightly in AWS.
   • Shard Playwright tests across multiple runners (pytest -n auto or shard_runner.py).
   • Store artifacts (videos, screenshots, JUnit XML) securely in S3.

Key principle: Don’t rip Selenium out overnight. Let Playwright earn trust while Selenium slowly shrinks.

Phase 3: Test Intelligence and Executive Dashboards

This is where many migrations fail: teams move the tests but never unlock analytics. Without intelligence, automation is just a cost center.

Here’s how to layer in intelligence:

1. Adopt Allure TestOps as the command center
   • Centralize results from both Selenium (legacy) and Playwright (modern).
   • Allow executives to view pass/fail trends by product line, release, or environment.
   • Provide drill-downs for engineers but high-level summaries for VPs.
2. Build risk-based dashboards
   • Example: “P0 coverage by module”
   • Show which high-risk flows have Playwright coverage and which still rely on Selenium/manual.
3. Enable on-demand test execution
   • Integrate Allure with CI/CD triggers (GitHub Actions workflows, AWS Lambda).
   • Allow Product or VP stakeholders to launch Playwright suites with a single click.
   • Example: “Run Checkout Tests in Staging” button in Allure.
4. Add AI-driven insights (optional, phase 3+)
   • Log clustering to group failures by root cause.
   • Flake triage dashboards.
   • Gap analysis: highlight user journeys not yet automated.

Key principle: Executives don’t care about tests; they care about confidence. Give them dashboards, not JUnit logs.

Security Considerations

Migrating test frameworks isn’t just about speed. If you’re in healthcare, fintech, or SaaS, compliance is non-negotiable. Best practices:

• Secrets management: Never hard-code credentials in GitHub Actions. Use AWS Secrets Manager or GitHub OIDC with IAM roles.
• Data masking: If tests hit real patient/customer data, mask or mock datasets in lower environments.
• Audit trails: Store test logs and results in immutable S3 buckets with lifecycle policies.
• Least privilege CI/CD: GitHub runners or AWS CodeBuild projects should have only the permissions they need; no shared IAM keys.

Key principle: Migration is a perfect moment to modernize your security posture.

Phase 4: Sunsetting Selenium

After 6–12 months, your Selenium suite should no longer be the backbone of confidence. The sunset plan looks like this:

1. Promote Playwright to primary
   • All P0 and P1 flows fully migrated.
   • Regression suite running nightly.
   • Executives reviewing Playwright dashboards.
2. Retire Selenium incrementally
   • Start by disabling Selenium jobs in CI (keep repo intact).
   • Archive test cases in TCM as “migrated.”
   • Keep a small “sentinel” set of Selenium tests for unusual edge cases (optional).
3. Decommission infrastructure
   • Tear down Selenium Grid clusters.
   • Remove stale Docker images and dependencies.
   • Lock repo to read-only.
4. Celebrate the migration
   • Publish metrics: “We cut runtime by 60%, reduced flakes by 80%, and empowered execs to run tests on demand.”
   • Socialize wins internally; migration is a culture change as much as a technical shift.

Key principle: Kill Selenium slowly but decisively. Don’t let it linger as a zombie repo.

The End State: Automation-First, Intelligence-Led

Imagine this:

• Every PR triggers Playwright smoke tests in GitHub Actions.
• Every nightly run executes a sharded Playwright regression in AWS.
• Allure dashboards show real-time risk coverage to engineering and product leaders.
• Your VP of Product can log into Allure, click “Run Staging Checkout Suite,” and see results in minutes.
• Manual tests, if still in Zephyr/Xray, are mapped by risk so execs see the full quality picture.

That’s the promise of an automation-first company in 2025. Not just faster tests, but intelligent, democratized quality engineering that serves every stakeholder; from developer to CEO.

Migration Best Practices Checklist

• ✅ Separate Playwright repo; don’t bolt onto Selenium.
• ✅ Run Playwright in parallel to Selenium for 2–3 months.
• ✅ Adopt Allure TestOps early for unified reporting.
• ✅ Use GitHub for fast feedback, AWS for compliance runs.
• ✅ Shard Playwright tests to scale efficiently.
• ✅ Implement strict secrets management and data masking.
• ✅ Use risk-based tagging across manual + automation.
• ✅ Retire Selenium slowly, keep a sentinel if needed.
• ✅ Enable one-click test execution for product stakeholders.
• ✅ Measure and broadcast wins.

Migration = Culture Reset

Migrating from Selenium to Playwright isn’t just a framework upgrade. It’s a cultural reset: from brittle scripts and opaque logs to a modern quality platform that powers decision-making across the company.

Do it right, and you won’t just replace Selenium. You’ll build a living scaffold for quality; a system that scales with your product, informs your executives, and empowers every team to move faster with confidence.

The journey is challenging, but the payoff is transformational. Don’t settle for Selenium’s ankle weights. Build the Playwright future.