# Python Sample: ETL Healthcheck Runner

```python
from datetime import datetime, timedelta
import pyodbc

WARNING_MINUTES = 30
CRITICAL_MINUTES = 60

connection = pyodbc.connect(
    "Driver={ODBC Driver 18 for SQL Server};"
    "Server=tcp:server.database.windows.net,1433;"
    "Database=etlops;"
    "Uid=user;"
    "Pwd=password;"
    "Encrypt=yes;TrustServerCertificate=no;"
)

query = """
SELECT PipelineName, MAX(CompletedAtUtc) AS LastRunUtc
FROM dbo.PipelineRunAudit
GROUP BY PipelineName;
"""

now_utc = datetime.utcnow()
with connection.cursor() as cursor:
    cursor.execute(query)
    for pipeline_name, last_run in cursor.fetchall():
        age_minutes = (now_utc - last_run).total_seconds() / 60.0
        if age_minutes >= CRITICAL_MINUTES:
            status = "CRITICAL"
        elif age_minutes >= WARNING_MINUTES:
            status = "WARNING"
        else:
            status = "HEALTHY"
        print(f"{pipeline_name}: {status} ({age_minutes:.0f} min since last run)")
```

Use this pattern to:
- Detect stalled ETL pipelines.
- Flag warning and critical thresholds.
- Feed alerts into email, Teams, or ticketing workflows.