Cloud Logging
Definition
Google Cloud's centralized logging service that collects, stores, and analyzes logs from all your applications and infrastructure.
Use Cases
- Spotify: Centralized troubleshooting and operational visibility for microservices running on Google Cloud — Teams aggregate service and infrastructure logs into Cloud Logging, use structured logging (JSON) with consistent fields (service, version, trace/span IDs), and create log-based metrics and alerts for error rates and latency signals. Logs are routed to longer-term analytics destinations when needed. (Faster incident triage and improved reliability through consistent, searchable logs and automated alerting tied to production symptoms.)
- The Home Depot: Monitoring and debugging cloud-native applications and data pipelines on Google Cloud — Application and platform logs are collected centrally in Cloud Logging, with filters and saved queries for common failure modes. Log-based metrics are used to detect spikes in errors, and exports are configured for deeper analysis and compliance retention where required. (Reduced mean time to detect and resolve issues by giving engineers a single place to search and correlate logs across services.)
Provider Equivalents
- AWS: Amazon CloudWatch Logs
- Azure: Azure Monitor Logs (Log Analytics workspace)
- GCP: Cloud Logging
- OCI: OCI Logging
Frequently Asked Questions
- What's the difference between Cloud Logging and Cloud Monitoring?
- Cloud Logging stores and lets you search raw log entries (events like errors, requests, and audit records). Cloud Monitoring focuses on metrics (numbers over time like CPU usage, request latency, and error rate) and dashboards/alerts. In practice, you often use both: logs for detailed investigation, metrics for trends and alerting. Cloud Logging can also create log-based metrics that feed Monitoring.
- When should I use Cloud Logging?
- Use Cloud Logging when you need a centralized place to collect and search logs from Google Cloud services (like Cloud Run, GKE, Compute Engine, Cloud Functions) and your applications. It’s especially useful for debugging production issues, investigating security/audit events, building alerts from log patterns (for example, repeated 500 errors), and exporting logs to BigQuery or Cloud Storage for long-term analysis or compliance.
- How much does Cloud Logging cost?
- Cost depends mainly on the volume of logs ingested and how long you retain them. Common cost drivers include: (1) ingestion/bytes written, (2) retention beyond included/default periods, and (3) exporting logs to other services (which may have their own storage/query costs, such as BigQuery or Cloud Storage). To control cost, reduce noisy logs, use exclusion filters, choose appropriate retention, and route only necessary logs to premium destinations.
Category: monitoring
Difficulty: intermediate
Related Terms
See Also