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Infrastructure and containerization tools for hosting AI model environments.
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This repository serves as a curated collection of software packages for Kubernetes application deployment and package management. Its primary purpose is to provide a standardized set of predefined application configurations to ensure consistent software installations across different clusters. The project focuses on maintaining version compatibility and providing a reliable source of verified packages. This allows for a standardized cluster setup by simplifying the installation and versioning of software on a container orchestration platform.
Standardized Helm charts for Kubernetes package management.
This project is a Helm chart repository and Kubernetes application catalog providing standardized deployment templates for popular open-source software. It serves as a library of pre-configured packages designed to automate the installation and configuration of server-side applications on container clusters. The collection includes a suite of hardened container images built on minimal base layers to reduce the attack surface. These images undergo automated vulnerability scanning and triage within the release pipeline to identify and remediate security flaws before deployment. The project man
Official Helm charts for deploying applications on Kubernetes.
This project is a containerized deployment for running Stable Diffusion web interfaces. It provides a portable runtime for generative AI that manages dependencies and hardware acceleration to enable text-to-image generation and image-to-image transformations via a browser-based interface. The system uses hardware-specific image tags to support both GPU-accelerated synthesis and CPU-only execution. It ensures environment isolation across different operating systems while utilizing bind-mount data persistence to keep heavy model weights and generated outputs on the host machine. The deployment
Docker-based deployment for popular web-based model interfaces.
This project is an educational resource and engineering guide for building, deploying, and optimizing large language model applications and production pipelines. It serves as a blueprint for cloud AI infrastructure, providing a framework for orchestrating inference endpoints, data warehouses, and scalable production environments. The repository provides specific implementation patterns for retrieval augmented generation to ground model responses in external data. It includes a training workflow for crawling, structuring, and processing datasets to facilitate model fine-tuning, alongside an ev
Orchestrates end-to-end cloud infrastructure and containerization for scaling production AI environments.
This project provides a containerized environment for deploying Apache Airflow, enabling the orchestration of complex data pipelines and automated task scheduling. By packaging the orchestration platform into portable images, it ensures consistent execution across diverse infrastructure setups and simplifies the management of runtime dependencies. The platform facilitates distributed task execution by decoupling the scheduler from the execution layer, allowing for horizontal scaling of processing power across multiple worker nodes. It supports dynamic configuration through environment variabl
Community-standard Docker image for containerized installations.
Run the official Stable Diffusion releases in a Docker container with txt2img, img2img, depth2img, pix2pix, upscale4x, and inpaint.
Containerized setup for deploying image generation services.
Tutorial for scalable Kubernetes executor environments on GKE.
Kubernetes-focused deployment service and container definitions.
Lean Helm chart optimized for Kubernetes-native execution.
Lightweight installer for federated reference architectures.
Managed service platform for running orchestration on Kubernetes.
Chef cookbook for automated infrastructure configuration.
Comprehensive guide for running orchestration workloads on Kubernetes.
CloudFormation templates for deploying clusters on AWS.
Preconfigured Docker container optimized for Spark and Hadoop workloads.
Kubernetes custom controller for managing deployment lifecycles.