Best of Monitoring — September 2025

1. 1
   Article

   Blueground Engineering·36w

   A Software Engineer’s Guide to Observability

   A comprehensive guide to observability for engineering teams, covering the three pillars (logging, tracing, metrics) and their practical applications. Explains why observability has become critical in the era of distributed systems and AI-generated code, where complexity is increasing while domain expertise is becoming more distributed. The guide focuses on understanding when and why to use different observability tools rather than just how to configure them.

   38
2. 2
   Article

   Noted·36w

   Komodo - Manage Docker Images & Containers Across Multiple Servers

   Komodo is an open-source web application that centralizes Docker container and server management across multiple servers. It provides monitoring, deployment automation, Docker Compose stack management, and scheduling capabilities through a unified interface. The platform includes server resource tracking, container lifecycle management, Git-based deployments, configuration management, and audit logging without subscription limitations.

   23
3. 3
   Article

   InfoWorld·35w

   Advanced debug logging techniques: A technical guide

   Debug logging is essential for maintaining high-performance applications across different architectures. Effective debug logging requires being selective about what to log, using structured formats like JSON, including contextual information such as correlation IDs, and implementing techniques like parameterized logging and rate limiting. Key practices include avoiding over-logging, never logging sensitive data, maintaining consistent formatting, and using centralized log management platforms. The guide covers specific tools for different languages (Winston for Node.js, structlog for Python, SLF4J for Java) and emphasizes the importance of correlation IDs for distributed tracing in microservice environments.

   20
4. 4
   Article

   OpenTelemetry·37w

   How to Name Your Metrics

   OpenTelemetry metrics should focus on what is being measured rather than who is measuring it. Service names, units, and deployment context belong in attributes, not metric names. This approach enables cross-service aggregation, reduces namespace clutter, and creates reusable dashboards. Clean metric names like 'transaction.count' with service.name attributes are more maintainable than traditional patterns like 'payment_service_transaction_total'.

   14
5. 5
   Article

   PostgreSQL·36w

   PostgreSQL: pgexporter 0.7

   pgexporter version 0.7.0 has been released with improvements to core metrics and new features. This Prometheus exporter for PostgreSQL includes extension support developed as part of a Google Summer of Code project. The tool helps monitor PostgreSQL databases by exporting metrics to Prometheus.

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