What are the best practices for logging in cloud-native environments?
Log recording in cloud-native environments is crucial for ensuring the observability of distributed systems, especially in scenarios involving microservices, dynamic container scheduling, and immutable infrastructure. It supports core operational requirements such as fault diagnosis, performance monitoring, compliance auditing, and security analysis.
The core of best practices includes:
1. Agentless log output: Applications should always output logs to standard output (stdout) and standard error (stderr) instead of writing to files, with unified collection by the infrastructure layer.
2. Sidecar or daemon-based collection: In Kubernetes, prefer using DaemonSets like Fluent Bit/Fluentd or configuring dedicated Sidecar containers for critical applications to handle log collection, avoiding intrusion into application logic.
3. Structured logging: Mandatorily output logs in structured formats such as JSON, including high-value metadata like timestamps, log levels, service names, and request IDs to facilitate efficient parsing and filtering.
4. Centralized storage and analysis: Must adopt centralized log storage and query engines such as Elasticsearch and Loki, combined with visualization tools like Kibana or Grafana for unified analysis.
5. Log normalization and grading: Define and enforce consistent specifications for log formats, field naming, and log levels.
Implementation steps and value: First, establish a log management platform (such as EFK/ELK Stack or PLG Stack). During development, applications output structured logs to standard streams according to specifications. In the deployment phase, configure log collectors (DaemonSet or Sidecar). At the platform layer, configure parsing rules, storage policies, visualization dashboards, and alert rules. This significantly improves troubleshooting efficiency, system transparency, and compliance, while reducing operational costs through automation. Special attention should be paid to log rotation, data lifecycle management (archiving/deletion), and cost control.