Open Source Observability Projects
Discover 41 open source Observability repositories from GitHub, each with an analysis of what it does, key features, use cases and alternatives. Observability projects here are most often combined with LLM, Monitoring and Python. Last updated October 4, 2026.
41 repositories · updated October 4, 2026
mcp-server-cloudflare: Connect AI Clients to Cloudflare Services
A collection of domain-specific Model Context Protocol servers that let compatible AI clients inspect and work with Cloudflare services through guided tools. Use them when you want product-focused interactions rather than broad API access through code execution.
dagger: Automate Software Delivery Across Environments
Dagger is a Go-based automation engine for building, testing, and shipping software with reusable, programmable workflows. It suits teams that want the same containerized delivery tasks to run locally, in CI, or in the cloud.
dagster: Orchestrate Data Assets and Pipelines
Dagster is a Python platform for building and operating data pipelines as assets, with orchestration, lineage, and observability in one system. It suits data teams that need to develop, test, and maintain workflows from local work through production.
tianji: Combine Website Analytics and Service Monitoring
Tianji combines website analytics, uptime monitoring, and server status reporting in one self-hostable application. It suits teams that want a shared view of site traffic and service health without running separate tools.
turboseek: Build an AI Search Engine with Web Sources
TurboSeek is a TypeScript web app that answers questions using web search results and language models. It is suited to developers who want to explore or adapt a Perplexity-style search experience, with external API credentials required to run it.
style-observer: Detect Changes to CSS Properties
Style Observer is a JavaScript library that detects changes to CSS properties on connected elements, including custom properties and elements in Shadow DOM. Use it when application logic needs to respond to style changes without polling.
hertzbeat: Monitor Systems, Metrics, Logs, and Alerts
Apache HertzBeat is a self-hosted observability platform for collecting metrics and logs, managing alerts, and publishing service status pages. It suits teams seeking agentless monitoring with configurable collection and optional collector clusters.
karpor: Explore and Understand Kubernetes Clusters
Karpor is a Kubernetes visualization tool for searching resources and gaining operational insight across clusters. It helps platform and developer teams inspect compliance, resource relationships, and Kubernetes events, with AI-assisted capabilities.
greptimedb: Store and Query Metrics, Logs, and Traces
GreptimeDB is a Rust observability database that stores metrics, logs, and traces on object storage. It suits teams seeking a shared backend for telemetry, with SQL and PromQL queries and support for common ingestion protocols.
opik: Trace, Evaluate, and Monitor LLM Applications
Opik is a platform for tracing and evaluating LLM applications, RAG systems, and AI agents. Teams can use it to inspect workflows, run evaluations, and monitor deployments, either self-hosted or through Comet Cloud.
loguru: Simplify Logging in Python
Loguru is a Python logging library designed to make useful logging easy to add without the standard logging setup boilerplate. It suits scripts and applications that need configurable outputs, structured context, and clearer exception traces.
prometheus/prometheus: Monitor Systems with Time-Series Metrics
Prometheus collects and stores metrics from configured targets, lets teams query them with PromQL, and evaluates rules to surface issues or trigger alerts. It suits operators who want an autonomous monitoring system with flexible service discovery and metric labeling.