ObservabiliTrends

← Back to Articles

Better Logs in Production

Why Logging Matters

Logging is a fundamental aspect of observability. In production environments, effective logging is critical to diagnose problems, monitor system health, and gain insight into application behavior. However, without proper structure and practices, logs can become noisy, incomplete, or even useless.

Common Pitfalls in Production Logging

Principles of Better Logging

  1. Use structured logs: Log in JSON or a format easily consumed by logging systems like ELK, Loki, or Datadog.
  2. Include context: Always include trace IDs, span IDs, request URLs, user sessions, and environment tags.
  3. Log at the right level: Use error/warning for failures, info for key business events, and debug only in dev environments.
  4. Avoid sensitive data: Never log passwords, secrets, or personal data (PII).
  5. Be consistent: Define log schemas and naming conventions across all services.

Log Enrichment Techniques

Enriching logs means appending contextual metadata automatically. You can use log middleware or wrappers to add:

Centralized Logging and Querying

Centralized log aggregation is key to managing production logs. Tools like Elasticsearch, Loki, Datadog Logs, or CloudWatch Logs help you:

Conclusion

Production logs are your first line of defense when things go wrong. Investing in structured, enriched, and centralized logging practices dramatically improves your ability to detect, debug, and prevent incidents. Logs are not just artifacts—they are signals. Make them count.