Database Observability
Database is often the bottleneck. Track queries, pools, and patterns.
Query Span Attributes
| Attribute | Example | Required |
|---|
db.system | postgresql, mysql | Yes |
db.operation | SELECT, INSERT | Yes |
db.name | orders_db | Yes |
db.sql.table | users | Recommended |
db.statement | SELECT * FROM users WHERE id = ? | Parameterized only! |
Connection Pool Metrics (USE)
| Metric | Type | Description |
|---|
db.connections.active | Gauge | In use |
db.connections.idle | Gauge | Available |
db.connections.max | Gauge | Pool limit |
db.connections.wait_count | Counter | Had to wait |
db.connections.wait_duration | Histogram | Wait time |
Issues to Detect
| Issue | Detection | Fix |
|---|
| N+1 queries | >10 identical queries per request | Use eager loading |
| Slow queries | Duration > p95 threshold | Add indexes, optimize |
| Pool exhaustion | wait_count increasing | Increase pool, fix leaks |
Query Wrapper Pattern
Before: Start span (db.system, db.operation, db.sql.table), start timer
After: Record duration, set db.rows_affected, record errors, end span
Pool Monitor Pattern
Every 10s: Record active, idle, wait_count, wait_duration from pool stats
Anti-Patterns
- Full SQL with values → PII risk, use parameterized only
- No pool metrics → Can't detect saturation
- Missing slow query alerts → Problems go unnoticed
References
references/methodology/use-methodology.mdreferences/platforms/{platform}/database.md
