Fetch Test Runs

Fetch Test Runs

This skill fetches test runs from the Sippy API. It can return both failed and successful test runs, including JUnit output for AI-based analysis.

When to Use This Skill

Use this skill when you need to:

• Fetch test run data for a specific test across all jobs
• Get raw test failure outputs for AI-based similarity analysis
• Compare error messages across runs to determine if they share the same root cause
• Include successful runs in addition to failures (optional)
• Filter runs by job name substrings (e.g., only GCP techpreview jobs)
• Access JUnit test output for debugging and investigation

Prerequisites

1. Network Access: Must be able to reach the Sippy test runs API

   • No authentication required
   • Check: curl -s https://sippy.dptools.openshift.org/api/tests/v2/runs?test_id=test

2. Python 3: Python 3.6 or later

   • Check: python3 --version
   • Uses only standard library (no external dependencies)

3. Input Data: Requires test_id (job_run_ids are optional)

   • Get from fetch-regression-details skill output
   • test_id: Found in regression data (e.g., "openshift-tests:71c053c318c11cfc47717b9cf711c326")
   • job_run_ids: Optional - extracted from sample_failed_jobs[].failed_runs[].job_run_id

Implementation Steps

Step 1: Run the Python Script

# Path to the Python script
script_path="plugins/ci/skills/fetch-test-runs/fetch_test_runs.py"

# Fetch all test runs (failures only, by default)
python3 "$script_path" "$test_id" --format json

# Include successful runs as well
python3 "$script_path" "$test_id" --include-success --format json

# Filter to a specific Prow job (exact name works as substring of itself)
python3 "$script_path" "$test_id" --job-contains "periodic-ci-openshift-release-..." --format json

# Filter by multiple substrings (AND logic, case-insensitive, server-side)
python3 "$script_path" "$test_id" --job-contains gcp --job-contains techpreview --format json

# Filter to specific job run IDs (backward compatible with analyze-regression)
python3 "$script_path" "$test_id" "$job_run_ids" --format json

# Get human-readable summary
python3 "$script_path" "$test_id" --format summary

Arguments:

• test_id: Required test identifier (e.g., "openshift-tests:abc123")
• job_run_ids: Optional comma-separated list of Prow job run IDs to filter by

Options:

• --include-success: Include successful test runs (default: failures only)
• --job-contains <name>: Filter by job name substring (server-side, case-insensitive). Repeatable for AND logic — all substrings must appear in the job name. Full job names also work since they are substrings of themselves. E.g., --job-contains gcp --job-contains techpreview matches jobs containing both "gcp" and "techpreview".
• --start-days-ago <days>: Number of days to look back (default API is 7 days)
• --exclude-output: Strip the output field from each run to reduce response size. Use when you only need pass/fail status (e.g., regression start analysis). Significantly reduces JSON output size for large result sets.
• --output <path>: Write output to a file instead of stdout. Use when fetching large result sets (e.g., --include-success --start-days-ago 28) that may exceed stdout buffer limits. The script prints a summary line to stderr confirming the write.
• --format json|summary: Output format (default: json)

Step 2: Prepare Input Data (for analyze-regression)

When used with regression analysis, extract required data from regression details:

# Assuming you have regression_data from fetch-regression-details skill
test_id=$(echo "$regression_data" | jq -r '.test_id')

# Collect all job_run_ids from sample_failed_jobs
# This creates a comma-separated list of all failed job run IDs
job_run_ids=$(echo "$regression_data" | jq -r '
  .sample_failed_jobs
  | to_entries[]
  | .value.failed_runs[]
  | .job_run_id
' | tr '\n' ',' | sed 's/,$//')

echo "Test ID: $test_id"
echo "Job Run IDs: $job_run_ids"

Step 3: Parse the Output

The script outputs structured JSON data:

# Store JSON output for processing
output_data=$(python3 "$script_path" "$test_id" --format json)

# Check if fetch was successful
success=$(echo "$output_data" | jq -r '.success')

if [ "$success" = "true" ]; then
  # Extract runs array
  runs=$(echo "$output_data" | jq -r '.runs')

  # The runs array contains objects with: url, output, test_name, success
  # The AI command will analyze these runs for similarity
  echo "Fetched $(echo "$runs" | jq 'length') runs"
else
  # Handle error case
  error=$(echo "$output_data" | jq -r '.error')
  echo "Error: $error"
  echo "Test runs API may not be available"
fi

API Response Schema

The Sippy API returns a JSON array of test run objects:

[
  {
    "url": "https://prow.ci.openshift.org/view/gs/test-platform-results/logs/periodic-ci-openshift-release-master-ci-4.22-e2e-aws-ovn-techpreview/2016123858595090432",
    "output": "fail [k8s.io/kubernetes/test/e2e/apimachinery/discovery.go:145]: Fail to access: /apis/stable.e2e-validating-admission-policy-1181/: the server could not find the requested resource",
    "test_name": "[sig-api-machinery] Discovery should validate PreferredVersion for each APIGroup [Conformance]",
    "success": false,
    "failed_tests": 3
  },
  {
    "url": "https://prow.ci.openshift.org/view/gs/test-platform-results/logs/...",
    "output": "",
    "test_name": "[sig-api-machinery] Discovery should validate PreferredVersion for each APIGroup [Conformance]",
    "success": true,
    "failed_tests": 0
  }
]

Script Output Format

The script supports two output formats:

JSON Format (--format json)

Returns structured JSON with raw runs:

{
  "success": true,
  "test_id": "openshift-tests:71c053c318c11cfc47717b9cf711c326",
  "requested_job_runs": 0,
  "include_success": false,
  "job_name_filters": ["gcp", "techpreview"],
  "runs": [
    {
      "url": "https://prow.ci.openshift.org/...",
      "output": "fail [...]: error message",
      "test_name": "[sig-api-machinery] test name",
      "success": false,
      "failed_tests": 3
    }
  ],
  "api_url": "https://sippy.dptools.openshift.org/api/tests/v2/runs?test_id=...&prowjob_name=gcp&prowjob_name=techpreview"
}

Field Descriptions:

• success: Boolean indicating if the API call succeeded
• test_id: The test identifier that was queried
• requested_job_runs: Number of job run IDs requested (0 if none specified)
• include_success: Whether successful runs were requested
• job_name_filters: List of job name substrings used for server-side filtering (null if not specified)
• runs: Raw array of test run objects from Sippy API
  • url: Prow job URL for this specific run
  • output: The actual JUnit test failure output text (empty for successes)
  • test_name: Full test name
  • success: Boolean indicating if this run passed
  • failed_tests: Count of all tests that failed in this job run. If failed_tests > 10, this is a mass failure job — the test may be caught up in a larger issue (e.g., infrastructure failure, installer failure) that needs further investigation to root cause. When many runs show mass failures, the regression may not be caused by a change specific to this test.
• api_url: The API URL that was called

Error Response (when success is false):

{
  "success": false,
  "error": "Failed to connect to test runs API: Connection refused",
  "test_id": "openshift-tests:abc123",
  "requested_job_runs": 0,
  "include_success": false,
  "job_name_filters": null
}

Summary Format (--format summary)

Returns human-readable formatted output with sample runs:

Test Runs
============================================================

Test ID: openshift-tests:71c053c318c11cfc47717b9cf711c326
Job Contains: ['gcp', 'techpreview']
Include Successes: False
Runs Fetched: 18

Successes: 0, Failures: 18

Mass Failure Runs (>10 test failures in job): 4 of 18
  ⚠ These runs had many other test failures — this test may be caught up in a larger issue.

Sample Runs:

1. [FAIL] Job URL: https://prow.ci.openshift.org/view/gs/test-platform-results/logs/...
   Failed Tests in Job: 3
   Output: fail [k8s.io/kubernetes/test/e2e/apimachinery/discovery.go:145]: Fail to access...

2. [FAIL] [MASS FAILURE] Job URL: https://prow.ci.openshift.org/view/gs/test-platform-results/logs/...
   Failed Tests in Job: 47
   Output: fail [k8s.io/kubernetes/test/e2e/apimachinery/discovery.go:145]: Fail to access...

3. [PASS] Job URL: https://prow.ci.openshift.org/view/gs/test-platform-results/logs/...

... and 15 more runs

Error Handling

Case 1: API Not Available

python3 fetch_test_runs.py "openshift-tests:abc"

Output (JSON format):

{
  "success": false,
  "error": "Failed to connect to test runs API: Connection refused.",
  "test_id": "openshift-tests:abc",
  "requested_job_runs": 0,
  "include_success": false,
  "job_name_filters": null
}

Output (summary format):

Test Runs - FETCH FAILED
============================================================

Error: Failed to connect to test runs API: Connection refused.

The test runs API may not be available.

Case 2: No Runs Returned

If the API returns an empty array:

{
  "success": true,
  "test_id": "openshift-tests:abc",
  "requested_job_runs": 0,
  "include_success": false,
  "job_name_filters": null,
  "runs": []
}

Case 3: Invalid Arguments

python3 fetch_test_runs.py

Output:

Usage: fetch_test_runs.py <test_id> [job_run_ids] [options]

Arguments:
  test_id       Test identifier (e.g., 'openshift-tests:abc123')
  job_run_ids   Optional comma-separated list of Prow job run IDs

Options:
  --include-success    Include successful test runs (default: failures only)
  --job-contains       Filter by job name substring (repeatable for AND logic)
  --exclude-output     Strip output text from runs to reduce response size
  --output <path>      Write output to file instead of stdout
  --format json|summary   Output format (default: json)

Exit Codes:

• 0: Success
• 1: Error (invalid input, API error, network error, etc.)

Examples

Example 1: Fetch All Failures for a Test

script_path="plugins/ci/skills/fetch-test-runs/fetch_test_runs.py"
python3 "$script_path" "openshift-tests:bb3a7d828630760296ef203c5cacf708" --format json

Example 2: Fetch All Runs Including Successes

script_path="plugins/ci/skills/fetch-test-runs/fetch_test_runs.py"
python3 "$script_path" "openshift-tests:bb3a7d828630760296ef203c5cacf708" --include-success --format json

Example 3: Fetch Specific Job Runs (Backward Compatible)

Used by analyze-regression command:

# Assume regression_data is already fetched
test_id=$(echo "$regression_data" | jq -r '.test_id')
job_run_ids=$(echo "$regression_data" | jq -r '.sample_failed_jobs | to_entries[] | .value.failed_runs[] | .job_run_id' | tr '\n' ',' | sed 's/,$//')

# Fetch outputs for specific job runs
script_path="plugins/ci/skills/fetch-test-runs/fetch_test_runs.py"
output_data=$(python3 "$script_path" "$test_id" "$job_run_ids" --format json)

# Check success
if [ "$(echo "$output_data" | jq -r '.success')" = "true" ]; then
  echo "Successfully fetched runs"
fi

Example 4: Get Summary Report

python3 plugins/ci/skills/fetch-test-runs/fetch_test_runs.py \
  "openshift-tests:71c053c318c11cfc47717b9cf711c326" \
  --format summary

Example 5: Extract Output Messages for AI Analysis

# Fetch runs
output_data=$(python3 "$script_path" "$test_id" --format json)

# Extract all failure output messages
if [ "$(echo "$output_data" | jq -r '.success')" = "true" ]; then
  # Get all output texts from failed runs
  echo "$output_data" | jq -r '.runs[] | select(.success == false) | .output'

  # AI command will analyze these for:
  # - Similarity/consistency
  # - Common error patterns
  # - File references and API paths
  # - Root cause determination
fi

Example 6: Filter Runs by Job Name Substrings

Filter to runs from jobs matching multiple criteria (e.g., GCP + techpreview):

script_path="plugins/ci/skills/fetch-test-runs/fetch_test_runs.py"

# Get only GCP techpreview runs (both substrings must match, server-side)
python3 "$script_path" "openshift-tests:abc123" --include-success \
  --job-contains gcp --job-contains techpreview \
  --start-days-ago 28 --format json

# Get only metal upgrade runs
python3 "$script_path" "openshift-tests:abc123" \
  --job-contains metal --job-contains upgrade \
  --format summary

# Full job name also works (it's a substring of itself)
python3 "$script_path" "openshift-tests:abc123" \
  --job-contains "periodic-ci-openshift-release-master-nightly-4.22-e2e-gcp-ovn-techpreview" \
  --format json

Example 7: Determine Regression Start Date

Used by analyze-regression command to find when failures began:

script_path="plugins/ci/skills/fetch-test-runs/fetch_test_runs.py"

# Get the job with the most failures
most_failed_job="periodic-ci-openshift-release-master-nightly-4.22-e2e-metal-ipi-ovn"

# Fetch all runs (including successes) for this specific job, going back 28 days
job_history=$(python3 "$script_path" "$test_id" \
  --include-success \
  --job-contains "$most_failed_job" \
  --start-days-ago 28 \
  --format json)

# Analyze the run history
if [ "$(echo "$job_history" | jq -r '.success')" = "true" ]; then
  # Runs are returned newest to oldest
  # Iterate to find where failures started
  echo "$job_history" | jq -r '.runs[] | "\(.success) \(.url)"'

  # Look for transition from passing to failing
  # Find the first failure that's part of the current regression
fi

Notes

• The script uses only Python standard library - no external dependencies required
• Uses the production Sippy URL
• Handles API unavailability gracefully with clear error messages
• Returns raw outputs for AI-based interpretation and similarity analysis
• Job run IDs are optional - can fetch all runs for a test
• --include-success allows analyzing both passing and failing runs
• --job-contains filters results server-side using case-insensitive substring matching. Repeat for AND logic (all substrings must appear in the job name). Full job names work too since they are substrings of themselves.
• --start-days-ago allows looking back further than the default 7 days (e.g., --start-days-ago 28)
• Combine --include-success, --job-contains, and --start-days-ago to get full test history for regression analysis
• Backward compatible with analyze-regression command (accepts job_run_ids)
• Summary format shows first 5 runs only, to keep output manageable
• Runs are returned in order from most recent to least recent
• Each run includes a failed_tests count — the total number of tests that failed in that job. If failed_tests > 10, it indicates a mass failure job where many tests failed together, suggesting the test may be caught up in a larger issue (infrastructure failure, installer failure, etc.) rather than a regression specific to this test

See Also

• Related Skill: fetch-regression-details (provides test_id and job_run_ids)
• Related Command: /ci:analyze-regression (uses this skill for failure analysis)

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