{
  "schema_version": 1,
  "chart_type": "distribution",
  "mark": "boxplot",
  "meta": {
    "title": "CI Build Duration by Pipeline",
    "quality_profile": "showcase"
  },
  "data": {
    "columns": [
      { "id": "pipeline", "type": "string",
        "values": ["unit", "unit", "unit", "unit", "unit", "unit", "unit", "unit", "unit", "unit",
                   "integration", "integration", "integration", "integration", "integration", "integration", "integration", "integration", "integration", "integration",
                   "e2e", "e2e", "e2e", "e2e", "e2e", "e2e", "e2e", "e2e", "e2e", "e2e"] },
      { "id": "seconds", "type": "number", "unit": "s", "label": "Duration",
        "values": [42, 45, 47, 48, 50, 51, 53, 55, 58, 71,
                   118, 124, 131, 136, 140, 145, 152, 158, 166, 210,
                   295, 312, 328, 341, 355, 370, 388, 402, 425, 610] }
    ]
  },
  "encoding": {
    "value": { "column": "seconds", "label": "Duration (s)" },
    "group": { "column": "pipeline" }
  },
  "cards": [
    { "title": "Takeaway", "items": ["End-to-end runs dominate total CI time and vary the most.", "Each pipeline has one slow outlier, suggesting a cold-cache run rather than a code regression."] }
  ]
}