AI DevOps

Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.

A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems", which is `dmls-book`

Build, Manage and Deploy AI/ML Systems

Open-source, low-code AutoML platform for Python. PyCaret 4.0: sklearn-native engine + React control plane.

Evidently is ​​an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.

Open-source observability for your GenAI or LLM application, based on OpenTelemetry

The Open Source Feature Store for AI/ML

Ship AI Agents to Google Cloud in minutes, not months. Production-ready templates with built-in CI/CD, evaluation, and observability.

An awesome & curated list of best LLMOps tools for developers

🧊 Open source LLM observability platform. One line of code to monitor, evaluate, and experiment. YC W23 🍓

Next-generation AI Agent Optimization Platform: Cozeloop addresses challenges in AI agent development by providing full-lifecycle management capabilities from development, debugging, and evaluation to monitoring.

Fastest enterprise AI gateway (50x faster than LiteLLM) with adaptive load balancer, cluster mode, guardrails, 1000+ models support & <100 µs overhead at 5k RPS.

ZenML 🙏: One AI Platform from Pipelines to Agents. https://zenml.io.

🐢 Open-Source Evaluation & Testing library for LLM Agents

SkillFoundry — a leading open-source project in the AI/LLM ecosystem.

StackQuadrant — a leading open-source project in the AI/LLM ecosystem.