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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.

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Execution flow

Triggers include clicking “Run Tests” in the dashboard, a GitHub push/PR webhook, a cron schedule, or a Slack message mentioning Bugzy. API routes validate the request, create an execution record in Supabase, and enqueue a task. Cloud Run Jobs pick up the task, decrypt credentials via Cloud KMS, clone the project repo, and launch the Claude Code agent with the appropriate task configuration. Claude Code executes a step-based task using MCP servers (Slack, Jira, GitHub, etc.) and Playwright for browser automation. Results — test reports, code fixes, bug filings — are committed back to the repo. Real-time updates flow from Supabase subscriptions and legacy notification channels to the dashboard, so you see execution progress as it happens.

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Container properties

Containers are single-use. No state persists between executions — every run starts from a clean Git clone with fresh credentials.

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The 15-step test execution pipeline

When you trigger a test run, Bugzy executes a 15-step pipeline:
1

Run Tests Overview

Load task configuration and read tests/CLAUDE.md for project-specific test instructions.
2

Security Notice

Enforce security boundaries — the agent operates within defined permissions.
3

Parse Arguments

Extract test selection criteria: file pattern, tag (@smoke), specific file path, or “all”.
4

Read Test Strategy

Load test-execution-strategy.md for context on test tiers and priorities.
5

Clarification Protocol

If the request is ambiguous, confirm with the team before proceeding.
6

Identify Tests

Resolve the selector to specific test files and confirm the selection.
7

Run Tests

Execute selected Playwright tests inside the container with Chromium. Generate JSON reports.
8

Normalize Results

Convert raw test output into a standardized format.
9

Parse Results

Extract pass/fail status, error messages, screenshots, and traces from JSON reports.
10

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.
11

Fix Test Issues

The test-engineer subagent auto-fixes test issues — broken selectors, timing problems, stale references. Retries up to 3 times.
12

Log Product Bugs

File product bugs in your connected issue tracker (Jira, Azure DevOps, Asana, Linear) with screenshots and reproduction steps.
13

Handle Special Cases

Address edge cases — missing test files, invalid test cases, browser automation failures.
14

Update Knowledge Base

Record learnings in knowledge-base.md for future triage accuracy.
15

Notify Team

Post a summary to Slack, Microsoft Teams, or email with pass/fail counts, bug links, and fix details.

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Where test artifacts live

All test artifacts are committed to your project’s Git repository: Because everything lives in Git, you get full version history, code review via PRs, and the ability to run tests locally with standard Playwright commands.