Do I need to instrument my application code?

While the reporter works for test metrics alone, full trace correlation requires your backend services to be instrumented with OpenTelemetry to propagate the trace context.

What is trace-based testing in this context?

Trace-based testing allows you to use Tracetest to assert on backend spans triggered by your Playwright actions, ensuring that specific API calls or database operations occurred as expected.

How does this skill help debug flaky tests?

By correlating UI test failures with backend traces and logs, you can pinpoint exactly which service or database query failed, helping distinguish between flaky test code and environmental backend issues.

Does this work with cloud-based observability stacks?

Yes, it includes configurations for local setups as well as cloud-native environments like Railway using standard OTLP exporters and environment variables.

Playwright Test Observability

Name: Playwright Test Observability
Author: adaptationio

byadaptationio

分析と監視

Integrates Playwright end-to-end tests with OpenTelemetry and Grafana to provide full-stack trace correlation and performance metrics.

概要

The Playwright Test Observability skill bridges the gap between frontend testing and backend monitoring by connecting your test suite to an OpenTelemetry-compatible stack including Grafana, Prometheus, Loki, and Tempo. This enables developers to visualize the entire request lifecycle—from a browser click through the backend services to the database—within a single trace. It is particularly useful for debugging intermittent failures in distributed systems, monitoring test suite performance over time, and performing trace-based assertions to validate backend side-effects during UI interactions.

主な機能

0 GitHub stars
Automated alerting for test failure rates and performance regressions
Trace-based assertions using Tracetest for deeper backend validation
Pre-configured Grafana dashboards for pass rates, flakiness, and p95 duration
Full-stack trace correlation from browser interactions to database queries
Log aggregation combining test runner output with application logs

ユースケース

Validating backend database state and service calls after UI actions
Root cause analysis for failures in complex microservice architectures
Measuring and optimizing end-to-end performance bottlenecks

概要

主な機能

0 GitHub stars
Automated alerting for test failure rates and performance regressions
Trace-based assertions using Tracetest for deeper backend validation
Pre-configured Grafana dashboards for pass rates, flakiness, and p95 duration
Full-stack trace correlation from browser interactions to database queries
Log aggregation combining test runner output with application logs

ユースケース

Validating backend database state and service calls after UI actions
Root cause analysis for failures in complex microservice architectures
Measuring and optimizing end-to-end performance bottlenecks