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Website Debugging Guide: Addressing "HAP Rupture" Incidents

Context

The Ardens Project relies on robust digital infrastructure for its collaborative human-AI "braid" operations and for hosting critical tools like the Hybrid Attack Panel (HAP). Given the emergent and sometimes disruptive nature of these interactions, unexpected system ruptures and website bugs can occur. This guide provides a systematic approach to debugging websites, specifically tailored to incidents that may follow or be correlated with intense Ardens activity such as HAP deployments.

1. Don't Panic and Assess the Immediate Impact

  • Stay Calm: Panic can lead to mistakes. Approach the problem methodically.
  • Initial Assessment: Quickly understand the scope. Is the entire site down, or just a specific feature? Are users impacted globally or regionally?
  • Check Monitoring Systems: Review any existing monitoring alerts, dashboards, or logs for immediate indicators of the problem (e.g., server errors, increased latency, service unavailability).

2. Reproduce the Problem

  • Recreate Consistently: The first and most crucial step is to consistently reproduce the bug. If you can't reliably trigger it, it's much harder to fix.
  • Local Reproduction: If possible, try to reproduce the issue in a local development or staging environment. This allows for more intrusive debugging without affecting live users.
  • Gather Context: Note down precise steps to reproduce, user roles, browser, operating system, network conditions, and any specific inputs that lead to the rupture.

3. Locate the Bug: Server-Side vs. Client-Side

  • Browser Developer Tools: For client-side issues (frontend JavaScript errors, CSS rendering problems, network request failures visible in the browser):
    • Console Tab: Look for JavaScript errors, network errors, or custom log messages.
    • Network Tab: Check failed requests, unexpected responses, or slow loading assets.
    • Elements Tab: Inspect HTML/CSS for unexpected changes or rendering issues.
    • Sources Tab: Set breakpoints in JavaScript code to step through execution.
  • Server-Side Logs: For backend issues (application crashes, database errors, API failures, unexpected data processing):
    • Application Logs: Check logs generated by your web server (e.g., Apache, Nginx), application framework (e.g., Django, Flask, Node.js), and any microservices.
    • Database Logs: Look for query errors, connection issues, or performance bottlenecks.
    • System Logs: Review operating system logs for server-level problems (e.g., disk space, memory, CPU usage).
  • Distributed Tracing/APM: If available, use tools that provide end-to-end visibility across your application stack to trace requests and identify where failures occur.

4. Isolate the Issue

  • Divide and Conquer: Once you have a general idea of where the problem lies, narrow it down.
  • Comment Out Code: Systematically comment out sections of code to see if the bug disappears. This helps isolate the problematic lines or modules.
  • Breakpoints and Stepping: Use a debugger (browser dev tools for frontend, IDE debuggers for backend) to set breakpoints and step through your code line by line. Inspect variable values at each step to understand the program's flow and state.
  • Simplify Input: Try the simplest possible input that still triggers the bug.
  • Revert Changes: If the rupture occurred after recent deployments, consider reverting to a known stable version to quickly restore service and then debug the new changes in a controlled environment.

5. Formulate and Test a Hypothesis

  • Hypothesize the Cause: Based on your observations and isolation, form a theory about what's causing the problem.
  • Implement a Fix: Develop a potential solution based on your hypothesis.
  • Test Thoroughly: Apply the fix and re-test to ensure the bug is resolved and no new issues have been introduced (regression testing). Test all identified reproduction paths.

6. Document and Learn

  • Document the Incident: Record what happened, how it was debugged, the root cause, and the solution. This is invaluable for future incidents and knowledge sharing.
  • Post-Mortem Analysis: Conduct a post-mortem to understand why the rupture happened, how it could have been prevented, and what improvements can be made to systems, processes, or code.
  • Implement Preventative Measures: Based on the learning, implement changes to prevent recurrence (e.g., improved monitoring, better testing, code refactoring, infrastructure hardening).