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kubeflow - Machine Learning Toolkit for Kubernetes

  •    Python

The Kubeflow project is dedicated to making machine learning on Kubernetes simple, portable and scalable. Our goal is not to recreate other services, but to provide a straightforward way to train, test, and deploy best-of-breed open-source predictive models to diverse infrastructures. Anywhere you are running Kubernetes, you should be able to run KubeFlow.This document details the steps needed to run the Kubeflow project in any environment in which Kubernetes runs.

CloudComputing - Sample programs for Cloud Computing course at UT Austin

  •    Python

This repository contains samples and examples demonstrating cloud resource provisioning and usage for Amazon AWS and Google Cloud Platform (GCP).

caastle - Full-stack microservices deployment for Google Kubernetes Engine and Amazon Elastic Container Service

  •    Python

CaaStle is a full-stack microservices deployment tool for Google Kubernetes Engine (GKE) and Amazon ECS. Platform of containerized applications/microservices includes application/web servers, container orchestration engine clusters, and application’s external resource dependencies such as managed database servers.