This repository provides a comprehensive collection of Dockerfiles for a wide array of applications, targeting developers and system administrators who need to deploy and manage various services efficiently. It offers pre-built Docker images for big data, IoT, machine learning, monitoring, web services, and more, simplifying setup and ensuring consistent environments.

How It Works

The project maintains a vast catalog of Dockerfiles, each tailored for a specific application. These Dockerfiles leverage multi-stage builds and best practices to create optimized and secure container images. The collection is organized by functional categories, making it easy to find and utilize images for diverse use cases, from data processing pipelines to web application hosting.

Quick Start & Requirements

• Install: Clone the repository and build images using docker build -t <image-name> . from within each application's directory.
• Prerequisites: Docker is the primary requirement. Some images may have specific build-time dependencies noted within their respective Dockerfiles.
• Resources: Building images can be resource-intensive, depending on the application. Pre-built images are available on Docker Hub under vimagick and easypi (for ARM).

Highlighted Details

• Extensive coverage across numerous categories including Big Data, IoT, Machine Learning, Monitoring, Web, E-commerce, Security, Proxy, and VPN.
• Support for both x86 and ARM architectures for many applications.
• Active development and a broad range of third-party integrations.
• Includes auto-completion scripts for docker exec to simplify container interaction.

Maintenance & Community

The project is actively maintained, with a clear indication of community contributions and ongoing development. Issues and feature requests can be tracked via the GitHub issues page.

Licensing & Compatibility

The repository's licensing is not explicitly stated in the provided README. Users should verify licensing for individual Dockerfiles or the collection as a whole before commercial use or integration into closed-source projects.

Limitations & Caveats

The README does not specify licensing details, which could be a concern for commercial adoption. Some applications are marked with :skull:, indicating potential issues or deprecation.