GCP Observability Best Practices

Structured Logging

JSON Log Format

Use structured JSON logging for better queryability:

{
  "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

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