gcloud-usage

# GCP Observability Best Practices

## Structured Logging

### JSON Log Format

Use structured JSON logging for better queryability:

```json
{
  "severity": "ERROR",
  "message": "Payment failed",
  "httpRequest": { "requestMethod": "POST", "requestUrl": "/api/payment" },
  "labels": { "user_id": "123", "transaction_id": "abc" },
  "timestamp": "2025-01-15T10:30:00Z"
}
```

### Severity Levels

Use appropriate severity for filtering:

- **DEBUG:** Detailed diagnostic info
- **INFO:** Normal operations, milestones
- **NOTICE:** Normal but significant events
- **WARNING:** Potential issues, degraded performance
- **ERROR:** Failures that don't stop the service
- **CRITICAL:** Failures requiring immediate action
- **ALERT:** Person must take action immediately
- **EMERGENCY:** System is unusable

## Log Filtering Queries

### Common Filters

```
# By severity
severity >= WARNING

# By resource
resource.type="cloud_run_revision"
resource.labels.service_name="my-service"

# By time
timestamp >= "2025-01-15T00:00:00Z"

# By text content
textPayload =~ "error.*timeout"

# By JSON field
jsonPayload.user_id = "123"

# Combined
severity >= ERROR AND resource.labels.service_name="api"
```

### Advanced Queries

```
# Regex matching
textPayload =~ "status=[45][0-9]{2}"

# Substring search
textPayload : "connection refused"

# Multiple values
severity = (ERROR OR CRITICAL)
```

## Metrics vs Logs vs Traces

### When to Use Each

**Metrics:** Aggregated numeric data over time

- Request counts, latency percentiles
- Resource utilization (CPU, memory)
- Business KPIs (orders/minute)

**Logs:** Detailed event records

- Error details and stack traces
- Audit trails
- Debugging specific requests

**Traces:** Request flow across services

- Latency breakdown by service
- Identifying bottlenecks
- Distributed system debugging

## Alert Policy Design

### Alert Best Practices

- **Avoid alert fatigue:** Only alert on actionable issues
- **Use multi-condition alerts:** Reduce noise fro