Cortex | Awesome Repository

Cortex is a Kubernetes-based machine learning infrastructure platform designed for deploying, scaling, and managing models and workloads. It functions as a serverless inference engine and GPU cluster orchestrator, providing the tools necessary to execute real-time, asynchronous, and batch model predictions.

The platform utilizes declarative infrastructure-as-code for provisioning model clusters and environments. It optimizes operational costs by elastically scaling CPU and GPU resources through the use of spot instances.

The system covers a broad set of operational capabilities, including workload orchestration, private cloud network isolation with integrated identity management, and observability pipelines that stream logs and performance metrics to external monitoring tools.

Features

Production Serving Infrastructure - Deploys and serves machine learning models in production environments with scalable infrastructure and automated settings.
Serverless Inference Engines - Provides a serverless inference engine that automatically scales real-time, asynchronous, and batch model predictions.
GPU Resource Scaling - Dynamically adjusts GPU compute capacity using spot instances to balance performance and operational costs.

Features

Production Serving Infrastructure - Deploys and serves machine learning models in production environments with scalable infrastructure and automated settings.
Serverless Inference Engines - Provides a serverless inference engine that automatically scales real-time, asynchronous, and batch model predictions.
GPU Resource Scaling - Dynamically adjusts GPU compute capacity using spot instances to balance performance and operational costs.