Displaying 1 to 20 from 178 results

dockerfiles - Various Dockerfiles I use on the desktop and on servers.

  •    Shell

This is a repo to hold various Dockerfiles for images I create.You may also want to checkout my dotfiles, specifically the aliases for all these files which are here: github.com/jessfraz/dotfiles/blob/master/.dockerfunc.

Portainer - Simple management UI for Docker

  •    Javascript

Portainer is a lightweight management UI which allows you to easily manage your different Docker environments (Docker hosts or Swarm clusters). Portainer is meant to be as simple to deploy as it is to use. It consists of a single container that can run on any Docker engine (can be deployed as Linux container or a Windows native container). It allows you to manage your Docker containers, images, volumes, networks and more ! It is compatible with the standalone Docker engine and with Docker Swarm mode.

CADL - Course materials/Homework materials for the FREE MOOC course on "Creative Applications of Deep Learning w/ Tensorflow" #CADL

  •    Jupyter

This repository contains lecture transcripts and homework assignments as Jupyter Notebooks for the first of three Kadenze Academy courses on Creative Applications of Deep Learning w/ Tensorflow. It also contains a python package containing all the code developed during all three courses. The first course makes heavy usage of Jupyter Notebook. This will be necessary for submitting the homeworks and interacting with the guided session notebooks I will provide for each assignment. Follow along this guide and we'll see how to obtain all of the necessary libraries that we'll be using. By the end of this, you'll have installed Jupyter Notebook, NumPy, SciPy, and Matplotlib. While many of these libraries aren't necessary for performing the Deep Learning which we'll get to in later lectures, they are incredibly useful for manipulating data on your computer, preparing data for learning, and exploring results.




uwsgi-nginx-flask-docker - Docker image with uWSGI and Nginx for Flask applications in Python running in a single container

  •    Shell

Docker image with uWSGI and Nginx for Flask web applications in Python 3.6, Python 3.5 and Python 2.7 running in a single container. Optionally using Alpine Linux. This Docker image allows you to create Flask web applications in Python that run with uWSGI and Nginx in a single container.

hadolint - Dockerfile linter, validate inline bash, written in Haskell

  •    Haskell

A smarter Dockerfile linter that helps you build best practice Docker images. The linter is parsing the Dockerfile into an AST and performs rules on top of the AST. It is standing on the shoulders of ShellCheck to lint the Bash code inside RUN instructions. You can run hadolint locally to lint your Dockerfile.

awesome-docker - :whale: A curated list of Docker resources and projects

  •    Javascript

A curated list of Docker resources and projects Inspired by @sindresorhus' awesome and improved by these amazing contributors. The creators and maintainers of this list do not receive any form of payment to accept a change made by any contributor. This page is not an official Docker product in any way. It is a list of links to projects and is maintained by volunteers. Everybody is welcome to contribute. The goal of this repo is to index open-source projects, not to advertise for profit.


habitus - A Build Flow Tool for Docker

  •    Go

Habitus adds workflows to Docker build. This means you can create a chain of builds to generate your final Docker image based on a workflow. This is particularly useful if your code is in compiled languages like Java or Go or if you need to use secrets like SSH keys during the build. Habitus is a standalone build flow tool for Docker. It’s a command line tool that builds Docker images based on their Dockerfile and a build.yml.

kafka-docker - Dockerfile for Apache Kafka

  •    Shell

Kafka Docker helps to run multiple Kafka brokers in Docker.

habitus - A Build Flow Tool for Docker

  •    Go

Habitus adds workflows to Docker build. This means you can create a chain of builds to generate your final Docker image based on a workflow. This is particularly useful if your code is in compiled languages like Java or Go or if you need to use secrets like SSH keys during the build.Habitus is a standalone build flow tool for Docker. It’s a command line tool that builds Docker images based on their Dockerfile and a build.yml.

dockerfiles-windows - Various Dockerfiles for Windows Containers

  •    Javascript

Various Dockerfiles for Windows. Most of these can be run as Windows Containers on Windows 10, Windows Server 2016, Windows Server 1709 and Windows Server 1803. Most of these Dockerfiles are automatically built on AppVeyor and pushed to Docker Hub. See the badges in each sub folder's README files.

vim - My Vim configuration more Python, Javascript, Vue

  •    Vim

You can use Docker to try it. Or use the GitLab registry, where the image is automatically built weekly and all dependent packages are updated.

Dockerfile.vim - Vim syntax file & snippets for Docker's Dockerfile

  •    Vim

Vim syntax file for Docker's Dockerfile and snippets for snipMate.See LICENSE file.

dockerfile-examples - Dockerfile examples

  •    Shell

NOTE: Images values in config.yaml needs to match directory name where Dockerfile is located. If you skip build part with env.sh script, images will be automatically pulled from docker index.

docklands - Minimalistic Java EE Related Dockerfiles

  •    Shell

Simplest viable dockerfiles for Java EE projects (aka microservices) aiming for build speed and productivity. Each folder represents a Dockerfile which can be build by executing the build.js command. Recent builds already exist in https://hub.docker.com/u/airhacks/. To run the image use the "airhacks" name e.g. docker run -d -p 8080:8080 --name payara-ping airhacks/payara-ping.

dockerfile_lint

  •    Javascript

A rule based 'linter' for Dockerfiles. The linter rules can be used to check file syntax as well as arbitrary semantic and best practice attributes determined by the rule file writer. The linter can also be used to check LABEL rules against docker images. Rule files are written in yaml. See the example rule file sample_rules.yaml in the root folder of the project. The rules are implememented using regular expressions, run on one instruction of the dockerfile at a time. The rule file has 4 sections, a profile section, a general section, a line rule section and a required instruction section.