ops-demo

Objective

Activate CocoOps demo mode with a realistic mock dataset so evaluators can explore DORA metrics and sprint health without production Snowflake access.

Before proceeding, verify that .cocoplus/ exists. If not, output: "CocoPlus is not initialized. Run $pod init first." Then stop.

Step 1 — Check Current Demo Status

Read cocoplus.toml and check [demo] enabled. If already true, output:

CocoOps demo mode is already active.
Run $ops dora to view the demo DORA report.
Run $ops demo --reset to regenerate the demo dataset.
Run $ops demo --off to deactivate demo mode.

Then stop (unless --reset flag provided).

Step 2 — Create Demo Dataset Directory

Ensure .cocoplus/ops/demo/ exists. Create it if absent.

Step 3 — Write Demo Metrics Dataset

Write .cocoplus/ops/demo/metrics.json with a realistic 30-day dataset showing DORA metric progression. The dataset must:

• Include representative pipeline names (not generic "pipeline_1" — use realistic names like stg_orders_load, int_customer_metrics, mart_revenue_daily, ml_churn_predict)
• Show a credible improvement arc: early period has higher failure rate and recovery times; later period shows improvement
• Cover all four DORA metrics with plausible values for a data engineering team at High tier (not Elite — believable, not perfect)

{
  "dataset_version": "1.0",
  "period_days": 30,
  "generated_at": "<ISO timestamp>",
  "metrics": {
    "run_frequency": {
      "value": 1.4,
      "unit": "per_day",
      "tier": "High",
      "source": "demo"
    },
    "lead_time": {
      "value": 18.5,
      "unit": "hours",
      "tier": "High",
      "source": "demo"
    },
    "recovery_time": {
      "value": 210,
      "unit": "minutes",
      "tier": "High",
      "source": "demo"
    },
    "quality_failure_rate": {
      "value": 7.2,
      "unit": "percent",
      "tier": "High",
      "source": "demo"
    }
  },
  "pipeline_signals": [
    {
      "name": "stg_orders_load",
      "runs": 38,
      "failures": 3,
      "avg_lead_time_hours": 14.2,
      "last_failure": "2024-01-18T03:22:00Z",
      "recovery_minutes": 85
    },
    {
      "name": "int_customer_metrics",
      "runs": 30,
      "failures": 4,
      "avg_lead_time_hours": 22.1,
      "last_failure": "2024-01-21T07:45:00Z",
      "recovery_minutes": 310
    },
    {
      "name": "mart_revenue_daily",
      "runs": 28,
      "failures": 1,
      "avg_lead_time_hours": 19.8,
      "last_failure": "2024-01-09T23:11:00Z",
      "recovery_minutes": 42
    },
    {
      "name": "ml_churn_predict",
      "runs": 14,
      "failures": 4,
      "avg_lead_time_hours": 31.4,
      "last_failure": "2024-01-23T11:30:00Z",
      "recovery_minutes": 480
    }
  ],
  "git_signals": {
    "commits_14d": 18,
    "pipeline_prs": 6
  },
  "sprint": {
    "start": "2024-01-15",
    "end": "2024-01-29",
    "velocity_units": 9,
    "daily_burn_rate": 0.9,
    "predicted_final_velocity": 12.6
  },
  "overall_health": "High"
}