Every task Bugzy performs runs inside an isolated, ephemeral Cloud Run container. This page covers the execution infrastructure — what’s inside each container, the step-by-step test pipeline, and where test artifacts are stored.
Execution flow
Trigger (dashboard / webhook / cron / Slack message)
→ API route (Next.js on Vercel)
→ Task queue (Supabase)
→ Cloud Run Job (isolated container)
→ Claude Code agent (Anthropic)
→ MCP servers + Playwright browser
→ Results committed to Git
→ Dashboard updated in real time
Container properties
| Property | Detail |
|---|
| Runtime | Docker container on Google Cloud Run Jobs |
| Browser | Pre-installed Chromium via Playwright (version-pinned) |
| Credentials | Encrypted at rest with Cloud KMS, decrypted at job start |
| Workspace | Ephemeral — cloned from Git, destroyed after execution |
| MCP servers | Configured per project integrations (Slack, Jira, GitHub, etc.) |
| AI backbone | Claude Code (Anthropic SDK) |
Containers are single-use. No state persists between executions — every run starts from a clean Git clone with fresh credentials.
The 15-step test execution pipeline
When you trigger a test run, Bugzy executes a 15-step pipeline:
Run Tests Overview
Load task configuration and read tests/CLAUDE.md for project-specific test instructions.
Security Notice
Enforce security boundaries — the agent operates within defined permissions.
Parse Arguments
Extract test selection criteria: file pattern, tag (@smoke), specific file path, or “all”.
Read Test Strategy
Load test-execution-strategy.md for context on test tiers and priorities.
Clarification Protocol
If the request is ambiguous, confirm with the team before proceeding.
Identify Tests
Resolve the selector to specific test files and confirm the selection.
Run Tests
Execute selected Playwright tests inside the container with Chromium. Generate JSON reports.
Normalize Results
Convert raw test output into a standardized format.
Parse Results
Extract pass/fail status, error messages, screenshots, and traces from JSON reports.
Triage Failures
Classify each failure as a product bug (real application issue) or a test issue (broken selector, timing problem, flaky assertion). Uses the knowledge base for accuracy.
Fix Test Issues
The test-engineer subagent auto-fixes test issues — broken selectors, timing problems, stale references. Retries up to 3 times.
Log Product Bugs
File product bugs in your connected issue tracker (Jira, Azure DevOps, Asana, Linear) with screenshots and reproduction steps.
Handle Special Cases
Address edge cases — missing test files, invalid test cases, browser automation failures.
Update Knowledge Base
Record learnings in knowledge-base.md for future triage accuracy.
Notify Team
Post a summary to Slack, Microsoft Teams, or email with pass/fail counts, bug links, and fix details.
Where test artifacts live
All test artifacts are committed to your project’s Git repository:
| Artifact | Location | Format |
|---|
| Test plan | test-plan.md | Markdown |
| Manual test cases | test-cases/TC-XXX.md | Markdown |
| Automated tests | tests/specs/*.spec.ts | Playwright TypeScript |
| Test configuration | tests/CLAUDE.md | Markdown |
| Knowledge base | knowledge-base.md | Markdown |
| Disputed findings | disputed-findings.md | Markdown |
| Execution results | Dashboard + manifest.json | JSON |
