MLOps Tools Directory

Alibi Detect

Track your model to detect performance degradation, bias and data drift. Detect issues early and take action.

Apache Airflow

Apache Airflow is a platform created by the community to programmatically author, schedule and monitor workflows using Python DAGs.

Apache Beam

Automate the steps of your ML experiments. Schedule automatic pipeline runs to retrain the model on new data.

Apache Spark

Apache Spark is a data processing framework for large datasets and distributed computing.

Apache Zeppelin

Apache Zeppelin is a web-based notebook for interactive data analytics and collaborative documents with built-in Apache Spark integration for ML experimentation.

Argo Workflows

Argo Workflows is an open-source, container-native workflow engine for orchestrating parallel jobs on Kubernetes, particularly suited for MLOps pipeline orchestration.

BentoML

BentoML is an open platform that simplifies ML model deployment and enables you to serve your models at a production scale in minutes.

ClearML

ClearML is an end-to-end platform with an auto-magical suite of tools to streamline your ML workflow.

DagsHub

Keep track of important information about your experiments such as parameters, metrics and models.

DAGsHub

Platform for data scientists that combines GitHub-like repository management with integrated data versioning, experiment tracking, and model management. Built on top of Git and DVC with zero-configuration setup for MLOps workflows.

Dagster

Dagster is an orchestration platform for developing, producing, and observing data assets.

Dask

Optimize your code and distribute execution across multiple machines to improve performance.

Delta Lake

Delta Lake is an open-source storage framework that enables building Lakehouse architectures with ACID transactions and scalable metadata handling on data lakes.

Determined

Determined is an open-source deep learning training platform that makes building models fast and easy.

Dolt

Dolt is a SQL database that you can fork, clone, branch, merge, push and pull just like a Git repository - like Git and MySQL had a baby.

DVC

DVC is an open-source version control system for machine learning projects.

Evidently

Evidently is a tool for analyzing and tracking data and ML model quality throughout the model lifecycle.

FastAPI

FastAPI is a modern, high-performance web framework for building APIs with Python.

FastDS

A command-line wrapper that combines Git and DVC functionality to streamline data science workflows. Automates repetitive version control tasks and reduces errors in Git+DVC operations through simplified command interfaces.

Flyte

Flyte is a workflow automation platform for mission-critical data and machine learning processes at scale.

Git

Git is a free and open-source distributed version control system designed to handle everything from small to very large projects with speed and efficiency.

Git LFS

Git extension that replaces large files with text pointers while storing the actual files on a remote server. Enables version control of large assets while maintaining normal Git workflows and keeping repository sizes manageable.

Github

GitHub is the world's most widely adopted AI-powered developer platform that provides collaborative software development capabilities with specialized MLOps features.

Grafana

Grafana is an open-source tool for online system analytics & monitoring.

Guild AI

An open-source experiment tracking and optimization toolkit that automatically captures training runs, hyperparameters, and results without code modification. Provides systematic experiment management with built-in hyperparameter optimization and model comparison capabilities.

Horovod

Horovod is a distributed deep learning training framework developed by Uber for TensorFlow, Keras, PyTorch, and Apache MXNet that makes distributed training fast and easy.

Jenkins

A Java-based open-source automation server that provides robust CI/CD pipeline capabilities for MLOps workflows. Offers extensive plugin ecosystem, flexible pipeline configuration, and strong integration with containerization and cloud platforms for machine learning model deployment.

Jupyter

Jupyter Notebook is an open-source web application where you can create and share documents that contain live code, equations, visualizations, and text.

Kedro

Kedro is an open-source Python framework for creating reproducible, maintainable, and modular data science code.

Kestra

An open-source, infinitely-scalable orchestration platform that enables declarative workflow definition using YAML. Designed for event-driven and scheduled data workflows with rich plugin ecosystem and multi-language support for MLOps automation.

KServe

KServe is a Kubernetes-native platform for deploying both generative and predictive AI inference at scale, supporting OpenAI-compatible protocols and multi-framework deployment.

Kubeflow

Kubeflow makes deploying ML workflows on Kubernetes simple, portable and scalable.

lakeFS

Open-source data version control platform that transforms object storage into Git-like repositories. Enables atomic operations, branching, and versioning for data lakes with support for S3, GCS, Azure Blob, and other cloud storage systems.

Luigi

Luigi is a lightweight Python workflow scheduler built at Spotify that helps you build complex pipelines of batch jobs with dependency resolution and workflow management.

MLflow

MLflow is an open-source platform for managing the end-to-end machine learning lifecycle.

MLRun

Automate the steps of your ML experiments. Schedule automatic pipeline runs to retrain the model on new data.

ModelDB

Keep track of important information about your experiments such as parameters, metrics and models.

NannyML

NannyML is an open-source post-deployment data science library that detects silent model failures in production and estimates ML model performance without ground truth.

Neptune

Neptune is a flexible metadata store for MLOps that allows teams to log, store, display, organize, compare, and query model-building metadata.

Nextflow

A workflow framework for creating scalable, portable, and reproducible computational pipelines based on dataflow programming principles. Designed for bioinformatics and data-intensive applications with strong containerization and cloud deployment support.

Nuclio

A high-performance serverless computing platform designed for data-intensive and compute-intensive workloads. Provides 10-100x faster execution than traditional frameworks with built-in support for machine learning, real-time analytics, and event-driven architectures.

Orchest

A visual pipeline builder for data science workflows that enabled interactive development without DAGs. **Note: Project is no longer actively developed** - creators recommend Apache Airflow for robust workflow solutions.

Pachyderm

Pachyderm is a tool for data versioning and pipelines for MLOps.

Polyaxon

Polyaxon is a platform for building, training, and monitoring large-scale deep learning applications.

Polynote

Netflix's open-source polyglot notebook environment that supports multiple programming languages (Scala, Python, SQL) within single notebooks. Features IDE-like capabilities with autocomplete, parameter hints, and seamless Apache Spark integration for data science workflows.

Prefect

Prefect is an open-source workflow management system designed for modern infrastructure.

Prometheus

Prometheus is an open-source system monitoring and alerting toolkit.

Quilt

A data mesh platform that enables teams to manage large datasets like code packages, providing centralized data cataloging, automatic versioning, and collaborative data workflows. Designed for machine learning, biotech, and analytics teams requiring robust data lineage and reproducibility.

Ray

Automate the steps of your ML experiments. Schedule automatic pipeline runs to retrain the model on new data.

Seldon Core

Seldon Core 2 is a Kubernetes-native MLOps and LLMOps framework for deploying machine learning models and Large Language Model systems at scale.

Spyder

A powerful scientific Python development environment designed by and for scientists, engineers, and data analysts. Combines advanced code editing and debugging capabilities with interactive data exploration, visualization, and analysis tools from popular scientific libraries.

TensorBoard

TensorBoard is a visualization toolkit to optimize and debug ML models.

TensorFlow Serving

A flexible, high-performance serving system designed specifically for machine learning models in production environments. Provides efficient model version management, RESTful and gRPC APIs, and seamless integration with TensorFlow ecosystem for scalable ML inference.

TorchServe

A flexible and easy-to-use tool for serving and scaling PyTorch models in production environments. Supports both eager mode and TorchScript models with built-in multi-worker scaling, metrics collection, and seamless API access for high-performance inference.

Triton Inference Server

NVIDIA Triton Inference Server is an open-source AI inference serving platform that standardizes AI model deployment across different workloads with high-performance inference.

Weights & Biases

Weights & Biases is a tool to track and visualize your machine learning pipeline pieces, from datasets to production models.

ZenML

ZenML is a unified, extensible, open-source MLOps framework for creating portable, production-ready MLOps pipelines that work across different infrastructure platforms.