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Top 23 Python Observability Projects
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MLflow
The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.
For example, this can be done using MLflow in Python:
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Project mention: volnux VS Prefect - a user suggested alternative | libhunt.com/r/volnux | 2025-11-19
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Project mention: I Merged 348 PRs. Here Are The 11 Bugs That Tested My Sanity. | dev.to | 2026-07-15
Fix: Include eks_* keys in _INVESTIGATED_EVIDENCE_KEYS for is_clearly_healthy (Fixes #582) #617
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Project mention: Semantic Observability: Engineering Reliability for Production RAG | dev.to | 2026-07-01
Injecting these into standard logs is a recipe for storage-cost disasters and PII leaks. Instead, we use OpenLLMetry, an open-source extension of OTel that introduces semantic conventions for AI. It auto-instruments calls to providers like OpenAI or Anthropic, capturing the input and output as attributes within a span.
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agent-starter-pack
Ship AI Agents to Google Cloud in minutes, not months. Production-ready templates with built-in CI/CD, evaluation, and observability.
Project mention: Building "Sweets Vault" - a multimodal Gemini Agent with physical hardware integration | dev.to | 2026-05-15To kick-start the agent development, I leveraged the agent-starter-pack templates. It provides a production-ready foundation with FastAPI, frontend UI integration, and built-in observability.
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mcp-context-forge
An AI Gateway, registry, and proxy that sits in front of any MCP, A2A, or REST/gRPC APIs, exposing a unified endpoint with centralized discovery, guardrails and management. Optimizes Agent & Tool calling, and supports plugins.
Project mention: Every AI toolchain is inventing its own safety layer. We shipped one that works across all of them. | dev.to | 2026-05-12Anthropic shipped Claude Code hooks — PreToolUse, PostToolUse, Notification, and friends. They run as subprocesses, get JSON on stdin, and decide whether the tool call proceeds. OpenAI ships tool guardrails in the Agents SDK — Python (and now TS) callables you attach to a tool, with tripwire booleans that abort the run. The MCP ecosystem is sprouting gateways and proxies for the same purpose: MCPX, IBM ContextForge, Microsoft's MCP Gateway, Lasso Security's MCP Gateway — all reasonable answers to the same wire-level question.
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robusta
Better Prometheus alerts for Kubernetes - smart grouping, AI enrichment, and automatic remediation
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Project mention: What is an AI SRE? Definition, Capabilities, and 2026 Buyer's Lens | dev.to | 2026-05-21
Infrastructure tool execution. The agent reads from kubectl, cloud SDKs, observability backends, and ticket systems. Some agents also write, with guardrails. HolmesGPT documents read-only access with RBAC respect. Aurora documents sandboxed execution into an isolated namespace. K8sGPT documents Kubernetes-only diagnostics with anonymisation before any AI backend call.
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kubetorch
Distribute and run AI workloads on Kubernetes magically in Python, like PyTorch for ML infra.
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That's where traces and evaluations come in — supported by a growing number of platforms: Langfuse, Arize Phoenix, MLflow, LangSmith, W&B Weave, Datadog, AWS AgentCore, Azure AI Foundry, Google Vertex AI
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If you’re interested in observability, infra tooling, or open-source projects: ⭐ Check it out :https://github.com/BlazeUp-AI/Observal ⭐ Try the platform :https://observal.io/ ⭐ Share feedback ⭐ Star the repo if you like the vision
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future-agi
Open-source, end-to-end platform for evaluating, observing, and improving LLM and AI agent applications. Tracing · Evals · Simulations · Datasets · Gateway · Guardrails. Self-hostable. Apache 2.0.
If you want a batteries-included solution rather than building all this from scratch, check out FutureAGI. It bundles tracing, evals, simulations, datasets management, a gateway, and guardrails into a single self-hostable platform under an Apache 2.0 license. It's the kind of thing I wish existed when I first started shipping LLM features.
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telescope
Web-based log viewer UI. Explore logs data stored in several sources: ClickHouse, Kubernetes or Docker (by iamtelescope)
Project mention: Show HN: FlyQL: query language to filter data or generate SQL | news.ycombinator.com | 2026-05-15Hey HN.
I want to share small library which i made.
While I developing my log viewer (https://github.com/iamtelescope/telescope) I needed a way for users to filter the data in my UI.
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kubeledger
System of Record for Kubernetes cost accounting: per-namespace CPU, memory and GPU usage, with the 30% non-allocatable overhead made visible. Connects to AI assistants via MCP (Claude, Gemini, Mistral, Cursor) for plain-language analysis. Formerly Kube-Opex-Analytics.
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PlayBooks
Runbook automation platform with deep observability integrations for SRE & On-Call Teams (by DrDroidLab)
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monocle
Monocle is a framework for tracing GenAI app code. This repo contains implementation of Monocle for GenAI apps written in Python. (by monocle2ai)
Project mention: How to Build Self-Healing AI Agents with Monocle, Okahu MCP and OpenCode | dev.to | 2026-04-08Monocle helps developers and platform engineers building or managing generative AI apps monitor these in prod by making it easy to instrument their code to capture traces that are compliant with open-source cloud-native observability ecosystem. It automatically captures traces from LLM SDKs like OpenAI, LangChain, and LlamaIndex without any manual span creation.
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grafana-ansible-collection
grafana.grafana Ansible collection provides modules and roles for managing various resources on Grafana Cloud and roles to manage and deploy Grafana Agent and Grafana
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Project mention: Show HN: CUDA Profiler for Production Inference | news.ycombinator.com | 2026-06-23
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
Python Observability discussion
Python Observability related posts
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Strands Agents + Langfuse Evaluations
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Show HN: Cost-xray – per-token cost attribution, by tool, skill, prompt and more
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LangChain overview for Node.js
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ForecastOps (Like LLMops, MLOps)
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Fable 5 burns tokens fast. I found an cost tracker for it
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Apache Burr: Build reliable AI agents and applications
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What is an AI SRE? Definition, Capabilities, and 2026 Buyer's Lens
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A note from our sponsor - SaaSHub
www.saashub.com | 21 Jul 2026
Index
What are some of the best open-source Observability projects in Python? This list will help you:
| # | Project | Stars |
|---|---|---|
| 1 | MLflow | 27,056 |
| 2 | Prefect | 23,401 |
| 3 | opensre | 8,590 |
| 4 | openllmetry | 7,306 |
| 5 | agent-starter-pack | 6,517 |
| 6 | logfire | 4,378 |
| 7 | mcp-context-forge | 4,100 |
| 8 | robusta | 3,055 |
| 9 | holmesgpt | 2,879 |
| 10 | tokencost | 1,995 |
| 11 | kubetorch | 1,220 |
| 12 | langsmith-sdk | 972 |
| 13 | Observal | 918 |
| 14 | future-agi | 710 |
| 15 | telescope | 707 |
| 16 | dd-trace-py | 647 |
| 17 | kubeledger | 484 |
| 18 | PlayBooks | 457 |
| 19 | uniplot | 456 |
| 20 | monosi | 329 |
| 21 | monocle | 302 |
| 22 | grafana-ansible-collection | 238 |
| 23 | graphsignal-profiler | 236 |
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