Question 1

What are logging best practices?

Accepted Answer

Logging best practices: Log levels: ERROR - failures, exceptions, immediate attention, WARN - potential problems, monitor closely, INFO - important events, normal tracking, DEBUG - detailed diagnostics, development only, TRACE - very detailed, debugging specific issues. Structure: Use structured logging (JSON), include timestamps, include request/session ID, include relevant context, consistent message format. Content: Log errors with stack trace and context, log business events for tracking, log performance metrics for optimization, log security events for audit. Avoid: Logging sensitive data (passwords, tokens), excessive debug logging in production, unstructured messages, missing context, logging in loops. Best practices = appropriate level, structured format, context included. Don't over-log, don't log secrets. Make logs searchable and useful.

Question 2

What should I log in applications?

Accepted Answer

What to log in applications: Errors and exceptions: All errors with stack trace, error context (inputs, state), error severity, error timestamps. Business events: User actions (login, logout), transactions, state changes, important milestones. Performance metrics: Request processing time, resource usage, cache hits/misses, queue depths. Security events: Authentication attempts, authorization failures, suspicious activity, admin actions. Request/response: Request IDs, request parameters (sanitized), response status, response time. State changes: Configuration changes, data modifications, system events. What to log = errors, events, metrics, security. Include context for diagnosis. Balance detail with volume. Never log secrets. Make logs actionable.

Question 3

How do I choose log levels?

Accepted Answer

Log level selection: ERROR level: Application failures, exceptions thrown, critical errors, system crashes, immediate attention required. WARN level: Potential problems, deprecated usage, near-error conditions, resource nearing limits, unusual patterns. INFO level: Important business events, user actions, transaction completions, configuration changes, normal milestones. DEBUG level: Detailed diagnostic info, internal state, flow tracing, only during development/debugging. TRACE level: Very detailed tracing, entering/exiting methods, variable values, specific debugging sessions. Production: ERROR and WARN always, INFO for key events, DEBUG/TRACE disabled or selective. Development: DEBUG/TRACE enabled for troubleshooting. Level selection = match severity. Error for problems. Info for events. Debug for details. Adjust by environment. Don't use wrong level.

Question 4

How do I avoid logging sensitive data?

Accepted Answer

Sensitive data logging prevention: What's sensitive: Passwords, API keys, tokens, credit card numbers, personal data (PII), authentication credentials, encryption keys, medical records. Prevention methods: Mask/replace sensitive fields before logging, use log sanitization libraries, configure exclusion filters, audit log statements for sensitive data, use placeholder values for credentials, separate audit logs for compliance needs. Implementation: Create log sanitization layer, standard field masking patterns, developer training on sensitive data, code review for log statements, automated scanning for secrets in logs. Compliance: GDPR, HIPAA, PCI-DSS requirements, log retention policies, audit trail without secrets. Prevention = conscious effort. Sanitize before logging. Review log statements. Train developers. Automated checks. Security and compliance critical.

Question 5

How do I set up log aggregation?

Accepted Answer

Log aggregation setup: Purpose: Centralize logs from multiple sources, enable search and analysis, provide unified view, support monitoring and alerting. Tools: ELK Stack (Elasticsearch, Logstash, Kibana), Splunk, CloudWatch Logs, Datadog, Grafana Loki, Fluentd/Fluent Bit. Setup steps: Choose aggregation platform, configure log shipping from applications, set up log parsing/format, configure indexes for search, set up dashboards, configure alerts for critical logs. Architecture: Application logs → Log shipper → Aggregation platform → Search/visualization. Considerations: Log volume and cost, retention policy, search performance, security/access control. Aggregation = centralize and analyze. Choose appropriate tool. Configure shipping. Set up dashboards. Define alerts. Manage volume and cost.

Logging Best Practices Guide

Log Levels

Best Practices

What to Log

Pitfalls to Avoid

Logging Checklist