Modern columnar data format for ML and LLMs implemented in Rust. Convert from parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, Du…

External Secrets Operator reads information from a third-party service like AWS Secrets Manager and automatically injects the values as Kubernetes Secrets.

An extremely fast Python package installer and resolver, written in Rust.

Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b

📝 Design doc template & examples for machine learning systems (requirements, methodology, implementation, etc.)

Docker image for MLflow.

DSPy: The framework for programming—not prompting—foundation models

Static site generator for architecture models created with Structurizr DSL

Kedro Plugin to support running workflows on GCP Vertex AI Pipelines

A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems"

FastAPI framework, high performance, easy to learn, fast to code, ready for production

Guide on how to use Poetry for your projects

An open-source data logging library for machine learning models and data pipelines. 📚 Provides visibility into data quality & model performance over time. 🛡️ Supports privacy-preserving data collec…

Containers for machine learning

A set of tools to keep your pinned Python dependencies fresh.

Apache Maven Daemon

A curated list to learn about distributed systems

Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing

Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.

AWS Service registry for resilient mid-tier load balancing and failover.

An inference server for your machine learning models, including support for multiple frameworks, multi-model serving and more

Standardized Serverless ML Inference Platform on Kubernetes

A lightweight, clean and simple JSON implementation in Scala

Production infrastructure for machine learning at scale

A low-latency prediction-serving system

Design patterns implemented in Java