Docker
From charlesreid1
Docker is a way of deploying apps on servers. It packages apps into side-by-side containers. These are similar in spirit to virtual machines, but different because containers are not (or, don't have to be) fully bundled operating systems. The container system makes sure everything runs the same everywhere.
It's like Homebrew or Aptitude for apps.
References
Docker's documentation is excellent: https://docs.docker.com/
Docker from the command line: https://docs.docker.com/engine/reference/commandline/cli/
Docker to run memcached (Digital Ocean guide): https://www.digitalocean.com/community/tutorials/docker-explained-how-to-create-docker-containers-running-memcached
Note that many Docker issues on Github contain a wealth of useful debugging strategies and commands for checking the state of networks, ports, etc. Example: https://github.com/docker/docker/issues/13914
Potential security issues with Docker containers: https://blog.docker.com/2013/08/containers-docker-how-secure-are-they/
Flags
docker notes on the virtual microservice container platform
Installing the docker platform: Docker/Installing Docker Hello World: Docker/Hello World
Creating Docker Containers: Getting docker containers from docker hub: Docker/Dockerhub Creating docker containers with dockerfiles: Docker/Dockerfiles Managing Dockerfiles using git: Docker/Dockerfiles/Git Setting up Python virtualenv in container: Docker/Virtualenv
Running docker containers: Docker/Basics Dealing with volumes in Docker images: Docker/Volumes Removing Docker images: Docker/Removing Images Rsync Docker Container: Docker/Rsync
Networking with Docker Containers:
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docker pods pods are groups of docker containers that travel together
Docker pods are collections of Docker containers that are intended to run in concert for various applications.
Wireless Sensor Data Acquisition Pod The wireless sensor data acquisition pod deploys containers This pod uses the following technologies: Stunnel · Rsync · Apache · MongoDB · Python · Jupyter (numerical Python stack)
Deep Learning Pod This pod utilizes the following technologies: Python · Sklearn · Jupyter (numerical Python stack) · Keras · TensorFlow
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