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Daily Health Check Example

This example demonstrates how to run a daily health check on your production system.

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Scenario

You want to analyze the past 24 hours of production logs to get a system health report.

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Command

uv run main.py --time-range 24h --environment production

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Expected Output

The pipeline will:
  1. Discover production log sources
  2. Fetch logs from the last 24 hours
  3. Parse and normalize log entries
  4. Aggregate metrics
  5. Detect any anomalies
  6. Generate hypotheses (if anomalies found)
  7. Create a summary report
  8. Provide recommendations

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Sample Summary Output

# System Log Summary – Production
**Time Range**: Last 24 hours (2026-02-09 14:00 → 2026-02-10 14:00)
**Generated**: 2026-02-10 14:35:00 UTC

## Executive Summary
✅ **System healthy** - No critical anomalies detected
- Total Events: 12,034
- Error Rate: 0.9% (baseline: 0.9%)
- Most Active Service: auth-service

## Key Metrics
- **Total Events**: 12,034
- **Error Rate**: 0.9% (baseline: 0.9%)
- **Volume Change**: -5.1% vs baseline

## Service Breakdown

### auth-service
- Total: 5,234 events
- Errors: 123 (2.4%)
- P95 Latency: 1,200ms

### payment-service
- Total: 3,456 events
- Errors: 12 (0.3%)
- P95 Latency: 800ms

## Top Error Signatures
1. **AUTH_FAILED** - 89 occurrences (72.3%)
2. **RATE_LIMIT** - 34 occurrences (27.7%)

## Recommendations

✅ No immediate action required. System is operating within normal parameters.

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Automating Daily Checks

Add to your crontab for automated daily reports: 
# Run at 2 AM daily
0 2 * * * cd /path/to/live-log-insight && \
  uv run main.py --time-range 24h --environment production && \
  cat output/summary.md | mail -s "Daily Health Report" ops-team@example.com