Popular GitHub Repositories for Eks

DoEKS is a tool to build, deploy and scale Data & ML Platforms on Amazon EKS

Collection of best practices, reference architectures, model training examples and utilities to train large models on AWS.

A fully automated CI/CD pipeline that builds, tests, and deploys a Node.js application on Amazon EKS using GitHub Actions, Terraform, and Kubernetes.

Create, List, Update, Delete Amazon EKS clusters. Deploy and manage software on EKS. Run distributed model training and inference examples.

This repository aims to showcase how to finetune a FM model in Amazon EKS cluster using, JupyterHub to provision notebooks and craft both serving and training scripts, RayOperator to manage Ray Clusters and Karpenter to manage Node Scaling.

This Guidance demonstrates how to deploy a machine learning inference architecture on Amazon Elastic Kubernetes Service (Amazon EKS). It addresses the basic implementation requirements as well as ways you can pack thousands of unique PyTorch deep learning (DL) models into a scalable architecture and evaluate performance

Stable Diffusion is a popular Open Source project for generating images using Gen AI. Building a scalable and cost efficient inference solution is a common challenge. This project shows how to use AWS serverless and container services to build an end-to-end scalable, secure and price effecient asynchronous image generation architecture.

TwinGraph is a Python framework for distributed container orchestration using Kubernetes clusters, Docker Compose/Swarm or cloud resources on AWS (AWS Lambda, AWS Batch, Amazon EKS). Applications include high-throughput simulations, simulation-driven optimization, Digital Twins and machine learning.

OWASP EKS Goat is a deliberately vulnerable EKS cluster environment to explore AWS cloud-native security through hands-on attack and defense labs with walkthrough.

Helm Chart for deploying Spark history server in Amazon EKS for S3 Spark Event Logs

Federated Learning Infra Architecture on Kubernetes(EKS)

Open Infrastructure & Cloud Native Days Korea 2019 - Workshop

Collection of bet practices, reference architectures, examples, and utilities for foundation model development and deployment on AWS.

AWS Summit 2024 Jakarta --- ObservabilityAI: Memanfaatkan Amazon Bedrock Untuk Memantau Kinerja RESTful API Golang

Development and deployment on AWS of a question-answer LLM model using Llama2 with 7B parameters and RAG with LangChain

'Roiergasias' kubernetes operator is meant to address a fundamental requirement of any data science / machine learning project running their pipelines on Kubernetes - which is to quickly provision a declarative data pipeline (on demand) for their various project needs using simple kubectl commands. Basically, implementing the concept of No Ops. The fundamental principle is to utilise best of docker, kubernetes and programming language features to run a workflow with minimal workflow definition syntax. It is a Go based workflow running on command line or Kubernetes with the help of a custom operator for a quick and automated data pipeline for your machine learning projects (a flavor of MLOps).

A EKS-based ML deployment solution

Airflow DAGs repository synced for the MLOps plattform of the repository mlops-eks-mlplatform

Agentic Github Issues Retrieval on Kubernetes

Terraform frame to deploy a MLOps plattform on AWS EKS using Airflow, MLflow, and Jupyterhub.