An awesome & curated list of best LLMOps tools for developers
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Updated
Oct 16, 2026 - Shell
An awesome & curated list of best LLMOps tools for developers
Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.
deployKF builds machine learning platforms on Kubernetes. We combine the best of Kubeflow, Airflow†, and MLflow† into a complete platform.
Docker images for fastai
🕹️ Performance Comparison of MLOps Engines, Frameworks, and Languages on Mainstream AI Models.
MONAI Deploy aims to become the de-facto standard for developing, packaging, testing, deploying and running medical AI applications in clinical production.
Run GPU inference and training jobs on serverless infrastructure that scales with you.
obra/superpowers extended — 14→24 skills, 6 GadaaLabs engineering improvements, override infrastructure, one-command install
Chart for deploying ChromaDB in Kubernetes
🚀 The Ultimate Curated List of LLMOps Tools, Frameworks, and Resources - A comprehensive collection of the best tools for Large Language Model Operations
Hands-on GPU/HPC infrastructure operations: K8s GPU scheduling, HAMi sharing, Slurm, observability & vLLM inference. Learn it free on a laptop; validate on one cheap GPU.
Serving Next Generation Experimental Tracking for Machine Learning Operations
mlflow container setup for docker, docker compose and kubernetes including helm chart
Production-ready platform for deploying OpenAI-compatible LLM inference on Kubernetes. A one-command installer for enterprise generative AI on Intel® Xeon®, with vLLM and other serving engines, secure Keycloak authentication, and built-in observability - from bare metal to a scalable AI endpoint.
A curated collection of Docker Compose configurations for popular services like PostgreSQL, Kafka, Elasticsearch, Redis, RabbitMQ, MinIO, and more. Simplify your development and deployment workflows with ready-to-use setups.
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