AI Observer is a self-hosted observability backend that monitors local AI coding assistants like Claude Code and Codex CLI. It tracks metrics such as token usage, API latency, and error rates through a real-time dashboard, keeping all data local without third-party services. Users can import historical session data and export telemetry in various formats.

Learn how to build a fully functional Generative AI chatbot using Docker Model Runner, integrating observability tools like Prometheus, Grafana, and Jaeger for real-time monitoring. This guide addresses common challenges in AI development and provides a step-by-step process to create a local chatbot with a modern interface and comprehensive performance metrics.

The article provides a comprehensive guide on mastering Docker logs, detailing how to efficiently manage and analyze logs generated by Docker containers. It covers various logging drivers, commands for viewing logs, and best practices for log management to enhance troubleshooting and monitoring processes.

The article describes the GitHub repository for the "monitoring-stack," a Docker Compose setup designed for monitoring planar applications using OpenTelemetry. It includes components like Grafana, Prometheus, and Loki for visualizing metrics and logs, and provides instructions for setting up and accessing the stack.