Building an Automated QA KPI Dashboard for Playwright & BDD Pipelines
Tracking test automation metrics manually often leads to outdated figures and missed engineering gaps. To solve this, automated reporting directly from your test suites—such as Playwright and Cucumber—provides clear visibility into health, execution speed, and coverage. Below is a breakdown of how to structure an Automation KPI Dashboard to streamline test metrics, track trends, and establish…
A comprehensive Automation KPI Dashboard has been established to monitor test automation metrics from Playwright and BDD pipelines. This streamlined reporting provides key visibility into health, execution speed, and coverage. The dashboard tracks several critical metrics:
1. Coverage & Execution
- Total Test Suite: 120 tests (94 automated, 26 manual)
- Latest Run (2026-05-29): 94 executed - 87 passed, 7 failed, 0 skipped
2. Flakiness Tracking
- 2 flaky tests identified in the last 10 runs
- Top offenders: UI timeout issues and data synchronization lag
3. Defect Detection & CI/CD Performance
- 3 defects opened, 1 closed (average resolution time: 2 days)
- Pipeline health: 98% success rate with 12-minute average build time
- Primary pipeline failure cause: Dependency resolution errors
The dashboard also includes trends over the last 6 test runs showing pass rates, failed rates, flaky rates, and execution durations. Key action items moving forward include expanding automated coverage past 90%, mitigating flakiness by refactoring explicit waits and isolation for identified scenarios, resolving dependency caching errors to achieve 100% CI/CD success, and optimizing execution suite duration below 25 minutes using parallel runs.
The dashboard's context can be automatically generated by parsing test execution JSON outputs from frameworks like Playwright or Cucumber BDD into CI/CD reporting artifacts after each major test cycle or sprint.
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