control-theory/gonzo

What it solves

Log analysis is often a fragmented process involving switching between raw text streams, complex dashboards, and external AI tools. Gonzo provides a unified, real-time terminal user interface (TUI) that combines live log streaming, visual analytics, and AI-powered debugging in a single tool.

How it works

Gonzo processes log streams from various sources—including stdin, files, Kubernetes clusters, and OpenTelemetry (OTLP) gRPC/HTTP receivers—and parses them into a structured format. It uses a k9s-inspired 2x2 grid layout to display real-time charts, severity distributions, and log entries. For deeper analysis, it includes an embedded React-based web dashboard (Dstl8.Lite) and integrates with LLMs (like GPT-4, Claude, or local models via Ollama/LM Studio) to provide root cause suggestions and anomaly detection.

Who it’s for

DevOps engineers, SREs, and developers who need to monitor and debug distributed systems, Kubernetes clusters, or cloud-native applications in real-time without leaving the terminal.

Highlights

• Multi-source streaming: Supports Kubernetes native integration, OTLP, and standard file/stdin inputs.
• AI-powered insights: Integrates with multiple LLM providers to identify recurring issues and suggest root causes.
• Interactive TUI: Features Vim-style navigation, regex filtering, and a fullscreen log viewer.
• Embedded Web GUI: A built-in browser dashboard for severity heatmaps and pattern analysis via Drain3.
• Customizable parsing: Allows users to define custom log formats via YAML configuration.