Library › Book 1 › Reporting and Observability
Reporting and Observability
15.1🔒OverviewAI-driven tests fail differently than scripted tests: the execution path varies run to run, so "re-run it and watch" is not a debugging…
15.2🔒What to CapturePer test: the command log, screenshots per step, YAML snapshots per step (agent-readable semantic state), the current URL, timing and…
15.3🔒Command LoggingEvery playwright-cli command the agent executes should be logged:
15.4🔒Structured ReportsThe JSON report carries an environment block, a summary, and per-test detail:
15.5🔒Failure Analysis: The Six ArtifactsWhen a test fails, capture:
15.6🔒Traces: The Flight Recorder and the Audit TrailThe Playwright trace plays three roles at once:
15.7🔒Performance TrackingWrap each command in a timing function that logs duration and exit code, and record per-test durations into a time-series store. Alert when…
15.8🔒Integration with CI DashboardsJUnit XML remains the universal interchange format -- Jenkins, GitHub, GitLab all consume it:
15.9🔒Key Takeaways- Every failure should be diagnosable from artifacts alone; re-running a non-deterministic test is not a debugging strategy - The…
15.10🔒Q&ASelf-Assessment Quiz1. Why do AI-driven tests need richer failure artifacts than scripted tests? 2. What does "observability is largely a matter of copying the…
15.11🔒Exercises[Intermediate] Exercise 15.1: Implement a timing wrapper and run a small suite through it. Which command class is slowest -- the browser or…
15.12🔒Career Translation- Designed an observability system for AI-driven browser tests capturing six artifact types per failure, reducing mean time to diagnose…
15.13🔒Q&AInterview Depth CheckPrompt: An AI-driven test failed overnight in CI. What artifacts do you reach for, in what order?