Prow Job Extract Must-Gather

Prow Job Extract Must-Gather

This skill extracts and decompresses must-gather archives from Prow CI job artifacts, automatically handling nested tar and gzip archives, and generating an interactive HTML file browser.

When to Use This Skill

Use this skill when the user wants to:

• Extract must-gather archives from Prow CI job artifacts
• Avoid manually downloading and extracting nested archives
• Browse must-gather contents with an interactive HTML interface
• Search for specific files or file types in must-gather data
• Analyze OpenShift cluster state from CI test runs

Prerequisites

Before starting, verify these prerequisites:

1. gcloud CLI Installation

   • Check if installed: which gcloud
   • If not installed, provide instructions for the user's platform
   • Installation guide: https://cloud.google.com/sdk/docs/install

2. gcloud Authentication (Optional)

   • The test-platform-results bucket is publicly accessible
   • No authentication is required for read access
   • Skip authentication checks

Input Format

The user will provide:

1. Prow job URL - gcsweb URL containing test-platform-results/
   • Example: https://gcsweb-ci.apps.ci.l2s4.p1.openshiftapps.com/gcs/test-platform-results/logs/periodic-ci-openshift-release-master-ci-4.20-e2e-aws-ovn-techpreview/1965715986610917376/
   • URL may or may not have trailing slash

Implementation Steps

Step 1: Parse and Validate URL

1. Extract bucket path

   • Find test-platform-results/ in URL
   • Extract everything after it as the GCS bucket relative path
   • If not found, error: "URL must contain 'test-platform-results/'"

2. Extract build_id

   • Search for pattern /(\\d{10,})/ in the bucket path
   • build_id must be at least 10 consecutive decimal digits
   • Handle URLs with or without trailing slash
   • If not found, error: "Could not find build ID (10+ digits) in URL"

3. Extract prowjob name

   • Find the path segment immediately preceding build_id
   • Example: In .../periodic-ci-openshift-release-master-ci-4.20-e2e-aws-ovn-techpreview/1965715986610917376/
   • Prowjob name: periodic-ci-openshift-release-master-ci-4.20-e2e-aws-ovn-techpreview

4. Construct GCS paths

   • Bucket: test-platform-results
   • Base GCS path: gs://test-platform-results/{bucket-path}/
   • Ensure path ends with /

Step 2: Create Working Directory

1. Check for existing extraction first

   • Check if .work/prow-job-extract-must-gather/{build_id}/logs/ directory exists and has content
   • If it exists with content:
     • Use AskUserQuestion tool to ask:
       • Question: "Must-gather already extracted for build {build_id}. Would you like to use the existing extraction or re-extract?"
       • Options:
         • "Use existing" - Skip to HTML report generation (Step 6)
         • "Re-extract" - Continue to clean and re-download
     • If user chooses "Re-extract":
       • Remove all existing content: rm -rf .work/prow-job-extract-must-gather/{build_id}/logs/
       • Also remove tmp directory: rm -rf .work/prow-job-extract-must-gather/{build_id}/tmp/
       • This ensures clean state before downloading new content
     • If user chooses "Use existing":
       • Skip directly to Step 6 (Generate HTML Report)

2. Create directory structure

   mkdir -p .work/prow-job-extract-must-gather/{build_id}/logs
   mkdir -p .work/prow-job-extract-must-gather/{build_id}/tmp
   

   • Use .work/prow-job-extract-must-gather/ as the base directory (already in .gitignore)
   • Use build_id as subdirectory name
   • Create logs/ subdirectory for extraction
   • Create tmp/ subdirectory for temporary files
   • Working directory: .work/prow-job-extract-must-gather/{build_id}/

Step 3: Download and Validate prowjob.json

1. Download prowjob.json

   gcloud storage cp gs://test-platform-results/{bucket-path}/prowjob.json .work/prow-job-extract-must-gather/{build_id}/tmp/prowjob.json --no-user-output-enabled
   

2. Parse and validate

   • Read .work/prow-job-extract-must-gather/{build_id}/tmp/prowjob.json
   • Search for pattern: --target=([a-zA-Z0-9-]+)
   • If not found:
     • Display: "This is not a ci-operator job. The prowjob cannot be analyzed by this skill."
     • Explain: ci-operator jobs have a --target argument specifying the test target
     • Exit skill

3. Extract target name

   • Capture the target value (e.g., e2e-aws-ovn-techpreview)
   • Store for constructing must-gather path

Step 4: Download Must-Gather Archive

1. Construct must-gather path

   • GCS path: gs://test-platform-results/{bucket-path}/artifacts/{target}/gather-must-gather/artifacts/must-gather.tar
   • Local path: .work/prow-job-extract-must-gather/{build_id}/tmp/must-gather.tar

2. Download must-gather.tar

   gcloud storage cp gs://test-platform-results/{bucket-path}/artifacts/{target}/gather-must-gather/artifacts/must-gather.tar .work/prow-job-extract-must-gather/{build_id}/tmp/must-gather.tar --no-user-output-enabled
   

   • Use --no-user-output-enabled to suppress progress output
   • If file not found, error: "No must-gather archive found. Job may not have completed or gather-must-gather may not have run."

Step 5: Extract and Process Archives

IMPORTANT: Use the provided Python script extract_archives.py from the skill directory.

Usage:

python3 plugins/prow-job/skills/prow-job-extract-must-gather/extract_archives.py \
  .work/prow-job-extract-must-gather/{build_id}/tmp/must-gather.tar \
  .work/prow-job-extract-must-gather/{build_id}/logs

What the script does:

1. Extract must-gather.tar

   • Extract to {build_id}/logs/ directory
   • Uses Python's tarfile module for reliable extraction

2. Rename long subdirectory to "content/"

   • Find subdirectory containing "-ci-" in the name
   • Example: registry-build09-ci-openshift-org-ci-op-m8t77165-stable-sha256-d1ae126eed86a47fdbc8db0ad176bf078a5edebdbb0df180d73f02e5f03779e0/
   • Rename to: content/
   • Preserves all files and subdirectories

3. Recursively process nested archives

   • Walk entire directory tree
   • Find and process archives:

   For .tar.gz and .tgz files:

   # Extract in place
   with tarfile.open(archive_path, 'r:gz') as tar:
       tar.extractall(path=parent_dir)
   # Remove original archive
   os.remove(archive_path)
   

   For .gz files (no tar):

   # Gunzip in place
   with gzip.open(gz_path, 'rb') as f_in:
       with open(output_path, 'wb') as f_out:
           shutil.copyfileobj(f_in, f_out)
   # Remove original archive
   os.remove(gz_path)
   

4. Progress reporting

   • Print status for each extracted archive
   • Count total files and archives processed
   • Report final statistics

5. Error handling

   • Skip corrupted archives with warning
   • Continue processing other files
   • Report all errors at the end

Step 6: Generate HTML File Browser

IMPORTANT: Use the provided Python script generate_html_report.py from the skill directory.

Usage:

python3 plugins/prow-job/skills/prow-job-extract-must-gather/generate_html_report.py \
  .work/prow-job-extract-must-gather/{build_id}/logs \
  "{prowjob_name}" \
  "{build_id}" \
  "{target}" \
  "{gcsweb_url}"

Output: The script generates .work/prow-job-extract-must-gather/{build_id}/must-gather-browser.html

What the script does:

1. Scan directory tree

   • Recursively walk {build_id}/logs/ directory
   • Collect all files with metadata:
     • Relative path from logs/
     • File size (human-readable: KB, MB, GB)
     • File extension
     • Directory depth
     • Last modified time

2. Classify files

   • Detect file types based on extension:
     • Logs: .log, .txt
     • YAML: .yaml, .yml
     • JSON: .json
     • XML: .xml
     • Certificates: .crt, .pem, .key
     • Binaries: .tar, .gz, .tgz, .tar.gz
     • Other
   • Count files by type for statistics

3. Generate HTML structure

   Header Section:

   <div class="header">
     <h1>Must-Gather File Browser</h1>
     <div class="metadata">
       <p><strong>Prow Job:</strong> {prowjob-name}</p>
       <p><strong>Build ID:</strong> {build_id}</p>
       <p><strong>gcsweb URL:</strong> <a href="{original-url}">{original-url}</a></p>
       <p><strong>Target:</strong> {target}</p>
       <p><strong>Total Files:</strong> {count}</p>
       <p><strong>Total Size:</strong> {human-readable-size}</p>
     </div>
   </div>
   

   Filter Controls:

   <div class="filters">
     <div class="filter-group">
       <label class="filter-label">File Type (multi-select)</label>
       <div class="filter-buttons">
         <button class="filter-btn" data-filter="type" data-value="log">Logs ({count})</button>
         <button class="filter-btn" data-filter="type" data-value="yaml">YAML ({count})</button>
         <button class="filter-btn" data-filter="type" data-value="json">JSON ({count})</button>
         <!-- etc -->
       </div>
     </div>
     <div class="filter-group">
       <label class="filter-label">Filter by Regex Pattern</label>
       <input type="text" class="search-box" id="pattern" placeholder="Enter regex pattern (e.g., .*etcd.*, .*\\.log$)">
     </div>
     <div class="filter-group">
       <label class="filter-label">Search by Name</label>
       <input type="text" class="search-box" id="search" placeholder="Search file names...">
     </div>
   </div>
   

   File List:

   <div class="file-list">
     <div class="file-item" data-type="{type}" data-path="{path}">
       <div class="file-icon">{icon}</div>
       <div class="file-info">
         <div class="file-name">
           <a href="{relative-path}" target="_blank">{filename}</a>
         </div>
         <div class="file-meta">
           <span class="file-path">{directory-path}</span>
           <span class="file-size">{size}</span>
           <span class="file-type badge badge-{type}">{type}</span>
         </div>
       </div>
     </div>
   </div>
   

   CSS Styling:

   • Use same dark theme as analyze-resource skill
   • Modern, clean design with good contrast
   • Responsive layout
   • File type color coding
   • Monospace fonts for paths
   • Hover effects on file items

   JavaScript Interactivity:

   // Multi-select file type filters
   document.querySelectorAll('.filter-btn').forEach(btn => {
     btn.addEventListener('click', function() {
       // Toggle active state
       // Apply filters
     });
   });
   
   // Regex pattern filter
   document.getElementById('pattern').addEventListener('input', function() {
     const pattern = this.value;
     if (pattern) {
       const regex = new RegExp(pattern);
       // Filter files matching regex
     }
   });
   
   // Name search filter
   document.getElementById('search').addEventListener('input', function() {
     const query = this.value.toLowerCase();
     // Filter files by name substring
   });
   
   // Combine all active filters
   function applyFilters() {
     // Show/hide files based on all active filters
   }
   

4. Statistics Section:

   <div class="stats">
     <div class="stat">
       <div class="stat-value">{total-files}</div>
       <div class="stat-label">Total Files</div>
     </div>
     <div class="stat">
       <div class="stat-value">{total-size}</div>
       <div class="stat-label">Total Size</div>
     </div>
     <div class="stat">
       <div class="stat-value">{log-count}</div>
       <div class="stat-label">Log Files</div>
     </div>
     <div class="stat">
       <div class="stat-value">{yaml-count}</div>
       <div class="stat-label">YAML Files</div>
     </div>
     <!-- etc -->
   </div>
   

5. Write HTML to file

   • Script automatically writes to .work/prow-job-extract-must-gather/{build_id}/must-gather-browser.html
   • Includes proper HTML5 structure
   • All CSS and JavaScript are inline for portability

Step 7: Present Results to User

1. Display summary

   Must-Gather Extraction Complete
   
   Prow Job: {prowjob-name}
   Build ID: {build_id}
   Target: {target}
   
   Extraction Statistics:
   - Total files: {file-count}
   - Total size: {human-readable-size}
   - Archives extracted: {archive-count}
   - Log files: {log-count}
   - YAML files: {yaml-count}
   - JSON files: {json-count}
   
   Extracted to: .work/prow-job-extract-must-gather/{build_id}/logs/
   
   File browser generated: .work/prow-job-extract-must-gather/{build_id}/must-gather-browser.html
   
   Open in browser to browse and search extracted files.
   

2. Open report in browser

   • Detect platform and automatically open the HTML report in the default browser
   • Linux: xdg-open .work/prow-job-extract-must-gather/{build_id}/must-gather-browser.html
   • macOS: open .work/prow-job-extract-must-gather/{build_id}/must-gather-browser.html
   • Windows: start .work/prow-job-extract-must-gather/{build_id}/must-gather-browser.html
   • On Linux (most common for this environment), use xdg-open

3. Offer next steps

   • Ask if user wants to search for specific files
   • Explain that extracted files are available in .work/prow-job-extract-must-gather/{build_id}/logs/
   • Mention that extraction is cached for faster subsequent browsing

Error Handling

Handle these error scenarios gracefully:

1. Invalid URL format

   • Error: "URL must contain 'test-platform-results/' substring"
   • Provide example of valid URL

2. Build ID not found

   • Error: "Could not find build ID (10+ decimal digits) in URL path"
   • Explain requirement and show URL parsing

3. gcloud not installed

   • Detect with: which gcloud
   • Provide installation instructions for user's platform
   • Link: https://cloud.google.com/sdk/docs/install

4. prowjob.json not found

   • Suggest verifying URL and checking if job completed
   • Provide gcsweb URL for manual verification

5. Not a ci-operator job

   • Error: "This is not a ci-operator job. No --target found in prowjob.json."
   • Explain: Only ci-operator jobs can be analyzed by this skill

6. must-gather.tar not found

   • Warn: "Must-gather archive not found at expected path"
   • Suggest: Job may not have completed or gather-must-gather may not have run
   • Provide full GCS path that was checked

7. Corrupted archive

   • Warn: "Could not extract {archive-path}: {error}"
   • Continue processing other archives
   • Report all errors in final summary

8. No "-ci-" subdirectory found

   • Warn: "Could not find expected subdirectory to rename to 'content/'"
   • Continue with extraction anyway
   • Files will be in original directory structure

Performance Considerations

1. Avoid re-extracting

   • Check if .work/prow-job-extract-must-gather/{build_id}/logs/ already has content
   • Ask user before re-extracting

2. Efficient downloads

   • Use gcloud storage cp with --no-user-output-enabled to suppress verbose output

3. Memory efficiency

   • Process archives incrementally
   • Don't load entire files into memory
   • Use streaming extraction

4. Progress indicators

   • Show "Downloading must-gather archive..." before gcloud command
   • Show "Extracting must-gather.tar..." before extraction
   • Show "Processing nested archives..." during recursive extraction
   • Show "Generating HTML file browser..." before report generation

Examples

Example 1: Extract must-gather from periodic job

User: "Extract must-gather from this Prow job: https://gcsweb-ci.apps.ci.l2s4.p1.openshiftapps.com/gcs/test-platform-results/logs/periodic-ci-openshift-release-master-ci-4.20-e2e-aws-ovn-techpreview/1965715986610917376"

Output:
- Downloads must-gather.tar to: .work/prow-job-extract-must-gather/1965715986610917376/tmp/
- Extracts to: .work/prow-job-extract-must-gather/1965715986610917376/logs/
- Renames long subdirectory to: content/
- Processes 247 nested archives (.tar.gz, .tgz, .gz)
- Creates: .work/prow-job-extract-must-gather/1965715986610917376/must-gather-browser.html
- Opens browser with interactive file list (3,421 files, 234 MB)

Tips

• Always verify gcloud prerequisites before starting (gcloud CLI must be installed)
• Authentication is NOT required - the bucket is publicly accessible
• Use .work/prow-job-extract-must-gather/{build_id}/ directory structure for organization
• All work files are in .work/ which is already in .gitignore
• The Python scripts handle all extraction and HTML generation - use them!
• Cache extracted files in .work/prow-job-extract-must-gather/{build_id}/ to avoid re-extraction
• The HTML file browser supports regex patterns for powerful file filtering
• Extracted files can be opened directly from the HTML browser (links are relative)

Important Notes

1. Archive Processing:

   • The script automatically handles nested archives
   • Original compressed files are removed after successful extraction
   • Corrupted archives are skipped with warnings

2. Directory Renaming:

   • The long subdirectory name (containing "-ci-") is renamed to "content/" for brevity
   • Files within "content/" are NOT altered
   • This makes paths more readable in the HTML browser

3. File Type Detection:

   • File types are detected based on extension
   • Common types are color-coded in the HTML browser
   • All file types can be filtered

4. Regex Pattern Filtering:

   • Users can enter regex patterns in the filter input
   • Patterns match against full file paths
   • Invalid regex patterns are ignored gracefully

5. Working with Scripts:

   • All scripts are in plugins/prow-job/skills/prow-job-extract-must-gather/
   • extract_archives.py - Extracts and processes archives
   • generate_html_report.py - Generates interactive HTML file browser