Module
Selfmanagement
selfmanagement_preset
Branches
Description

The self-management, self-monitoring and self-healing engine for services and applications.

Databases

Collection of in-memory database management systems and caching systems.

Databases

Collection of NoSQL database management systems.

Lamp

Classical web application environment with Linux, Apache, MySQL and PHP. PHP works as the mod_php Apache module.

Optional components: Memcached, Redis, Tarantool.

Lemp

Modern web application environment with Linux, Nginx, MySQL and PHP. It is similiar to the LAMP stack, where Apache is replaced with the lightweight yet powerful Nginx. PHP works in php-fpm mode.

Optional components: Memcached, Redis, Tarantool.

Nodejs

The software stack for Node.JS applications

Nginx
A pre-configured and ready-to-use Node.js 7 web stack with Nginx.
nodejs:7.9.0, min-nginx:1.11.2, selfmanagement_preset, development_preset, express_js_blank:1
Nginx
A pre-configured and ready-to-use Node.js 7 web stack with Nginx.
nodejs:7.9.0, min-nginx:1.11.2, selfmanagement_preset, development_preset, express_js_blank:1
Wordpress
The maximum performance one-click install solution for Wordpress 4, a free and open-source content management system (CMS), running on completely integrated, pre-configured and optimized LEMP stack with the freshest version of PHP 7.
wordpress:4.7.5, php:7.1.4, mariadb-mysqld:10.1.22, min-nginx:1.11.2, selfmanagement_preset, phpmyadmin:4.7.0
Lemp
A pre-configured and optimized for better performance LEMP environment for web-applications with the next generation of PHP version 7. It is similiar to the LAMP stack, where Apache is replaced with the lightweight yet powerful Nginx, and PHP works in `php-fpm` mode.
min-nginx:1.11.2, mariadb-mysqld:10.1.22, php:7.1.4, selfmanagement_preset, phpmyadmin:4.7.0, memcached:1.4.36, redis:3.2.8
Machine learning
A pre-configured and fully integrated software stack with PyTorch, an open source machine learning library, and Python 3.6. It provides a stable and tested execution environment for training, inference, or running as an API service. The stack can be easily integrated into continuous integration and deployment workflows. It is designed for short and long-running high-performance tasks and optimized for running on NVidia GPU.
pytorch:0.3.0, python:3.6.3, cuda:9.0.176, cudnn:7.0.5, cuda_only-nvidia_drivers:384.111, selfmanagement_preset, development_preset:1