Docker For Windows | Setting Up Docker On Windows

Docker For Windows | Setting Up Docker On Windows

7 / 11 Blog from Docker

If you’re looking for simple and painless software deployment, Docker is the right tool for you. It is the best containerization platform and in this blog on Docker for Windows we’ll specifically focus on how Docker works on Windows.

To get in-depth knowledge on Docker, you can enroll for live DevOps Certification Training by Edureka with 24/7 support and lifetime access.

I’ll be covering the following topics in this blog:

1. Why use Docker For Windows?
2. Docker for Windows prerequisites 
3. Components installed with Docker 
4. What is Docker?
5. Docker Terminologies
6. Hands-On

 

Why use Docker for Windows?

• Avoids the work on my machine but doesn’t work on production problem: This problem occurs due to the inconsistent environment throughout the software development workflow. With Docker you can run an application within a container which contains all the dependencies of the application and the container can be run throughout the software development cycle. This practice provides a consistent environment throughout the software development life cycle
• Improves productivity: By installing Docker on windows we’re running Docker natively. If you’ve been following Docker for a while, you know that Docker containers originally supported only Linux operating systems. But thanks to the recent release, Docker can now natively run on windows, which means that Linux support is not needed, instead the  Docker container will run on the windows kernel itself
• Supports native networking: Not only the Docker container, the entire Docker tool set is now compatible with windows. This includes the Docker CLI (client), Docker compose, data volumes and all the other building blocks for Dockerizied infrastructure are now compatible with windows. But how is this advantageous? Since all the Docker components are locally compatible with windows, they can now run with minimal computational overhead.

Docker For Windows Prerequisites

The following requirements need to be met before installing Docker on windows:

1. Check if you’re using Windows 10, either pro edition or enterprise edition, 64-bit system. Docker will not run on any other windows version. So if you’re running on an older windows version, you can install the Docker toolbox instead. 
2. Docker for windows requires a Type-1 hypervisor and in the case of windows, it’s called the Hyper-V. Hyper-V is basically a lightweight virtualization solution build on top of the hypervisor framework. So you don’t need a virtual box, you just have to enable the hypervisor.
3. And also you need to enable the virtualization in BIOS. Now when you install Docker for windows, by default of this is enabled. But in case you’re facing any issue during installation, please check if your Hyper-V and virtualization is enabled.

https://docs.microsoft.com/en-us/virtualization/hyper-v-on-windows/quick-start/enable-hyper-v

Enable-WindowsOptionalFeature -Online -FeatureName Microsoft-Hyper-V -All

Components Installed With Docker

 

1. Docker Engine: When we say Docker, we actually mean Docker engine. The Docker engine contains the Docker daemon, REST API for interacting with the Docker daemon and a command line interface client that communicates with the daemon. Docker daemon accepts Docker commands such as Docker run, Docker build, etc, from the Docker client.
2. Docker Compose: Docker compose is used to run multiple Docker containers at once by using a single command, which is docker-compose up.
3. Docker Machine: Docker machine is used to install Docker engine. It is basically what you install on your local system. The Docker machine has it’s own CLI client known as the Docker machine and a Docker engine client called Docker.
4. Kitematic: Kitematic is an open source project built to simplify the use of Docker on Windows. It helps to automate the installation of Docker and it provides a very interactive user interface for running Docker containers.

What Is Docker?

Docker is a containerization platform that runs applications within containers called Docker containers. Docker containers are light weighted when compared to virtual machines. When you install a Virtual machine on your system, it uses the guest operating system on top of your host operating system.  This obviously takes up a lot of resources like disk space, RAM, etc. On the other hand, Docker containers make use of the host operating system itself.

 

 

 In the above image, you can see that, there’s a host operating system on top of which the Docker engine is mounted. The Docker engine runs container #1 and container #2. Both of these containers have different applications and each application has its own libraries and packages installed within the container.

 

I hope you have a good idea about what Docker is if you still have doubts check out this blog to learn more!

Let’s discuss some Docker terminologies now:

• Docker Images

Docker images are read-only templates to build Docker images. Docker images are created from a file called Dockerfile. Within the Dockerfile, you define all the dependencies and packages that are needed by your application.

• Docker Containers

Every time you run a Docker image, it runs as a Docker container. Therefore, a Docker container is the run time instance of a Docker image.

• Docker’s Registry

Docker’s registry, known as DockerHub is used to store Docker images. These images can be pulled from the remote server and can be run locally. DockerHub allows you to have Public/Private repositories.

• Docker Swarm

Docker swarm is a technique to create and maintain a cluster of Docker engines. A cluster of Docker engines comprises of multiple Docker engines connected to each other, forming a network. This network of Docker engines is called a Docker swarm. A Docker manager initiates the whole swarm and the other Docker nodes have services running on them. The main goal of the Docker manager is to make sure that the applications or services are running effectively on these Docker nodes.

• Docker Compose

Docker compose is used to run multiple containers at once. Let’s say that you have 3 applications in 3 different containers and you want to execute them at once. This is where Docker compose comes in, you can run multiple applications in different containers at once, with a single command, which is docker-compose up.

 

Hands-On

We’ll begin our demo by installing Docker for windows. But before we do that, check if you’ve met the prerequisites.

One more thing to note is since Docker for Windows requires Microsoft’s Hyper-V and once it’s enabled, VirtualBox will no longer be able to run virtual machines. So you can’t run Docker for Windows and a VirtualBox on the same system, side by side.

 

Enough of theory, let’s get our hands dirty and create a simple Python web application by using Docker Compose. This application uses the Flask framework and maintains a hit counter on Redis.

Flask is a web development framework, written in Python and Redis is an in-memory storage component, used as a database. You don’t have to install Python or Redis, we’re simply going to use Docker images for Python and Redis.

In this demo we’re going to use Docker compose to run two services, namely:

1. Web service
2. Redis service.

What does the application do? It maintains a hit counter every time you access a web page. So each time you access the website the hit counter gets incremented. It’s simple logic, just increment the value of the hit counter when the web page is accessed.

For this demo, you’ll need to create four files:

1. Python file
2. Requirements.txt
3. Dockerfile
4. Docker compose file

Below is the Python file (webapp.py) that creates an application by using the Flask framework and it maintains a hit counter on Redis. 

 1.

import time
import redis
from flask
import Flask
app = Flask(__name__)
cache = redis.Redis(host = 'redis', port = 6379)
def get_hit_count():
  retries = 5
while True:
  try:
  return cache.incr('hits')
except redis.exceptions.ConnectionError as exc:
  if retries == 0:
  raise exc
retries -= 1
time.sleep(0.5)
@app.route('/')
def hello():
  count = get_hit_count()
return 'Hello World! I have been seen {} times.
'.format(count)
if __name__ == "__main__":
  app.run(host = "0.0.0.0", debug = True)

 

2.The requirements.txt file has the name of the two dependencies, i.e. Flask and Redis that we’ll be installing in the Dockerfile.

flask

redis

3.The Dockerfile is used to create Docker images. Here, I’m installing python and the requirements mentioned in the requirements.txt file.

How to name Dockerfiles

Don't change the name of the dockerfile if you want to use the autobuilder at hub.docker.com. Don't use an extension for docker files, leave it null. The filename should just be: (no extension at all)

Dockerfile

however, you can do like below too...

dev.Dockerfile, uat.Dockerfile, prod.Dockerfile etc.

On VS Code you can use <purpose>.Dockerfile and it works accordingly.

FROM python:3.4-alpine

ADD . /code

WORKDIR /code

RUN pip install -r requirements.txt

CMD ["python", "webapp.py"]

4.The Docker compose file or the YAML file contains two services:

1. Web service: Builds the Dockerfile in the current directory
2. Redis service: Pulls a Redis image from DockerHub

务必要注意这里的排版，缩进不能错

version: '3'
services:
  web:
    build:
      context: .
      dockerfile: sample.Dockerfile
    ports:
    - "5000:5000"
  redis:
    image: "redis:alpine"

 

You can now run these two services or containers by using the following command:

docker-compose up

To view the output you can use Kitematic. To open Kitematic, right click on the whale icon on the status bar.

四个文件的文件名

Directory: Docker\Sample

Mode LastWriteTime Length Name
---- ------------- ------ ----
-a--- 6/12/2020 6:16 PM 93 docker-compose.yml
-a--- 6/12/2020 5:59 PM 12 requirements.txt
-a--- 6/12/2020 6:11 PM 0 sample.Dockerfile
-a--- 6/12/2020 5:58 PM 496 webapp.py

 

PS C:\workspace\Edenred\Docker\Sample> docker-compose up
Building web
Step 1/5 : FROM python:3.4-alpine
3.4-alpine: Pulling from library/python
8e402f1a9c57: Pull complete cda9ba2397ef: Pull complete aafecf9bbbfd: Pull complete bc2e7e266629: Pull complete e1977129b756: Pull complete Digest: sha256:c210b660e2ea553a7afa23b41a6ed112f85dbce25cbcb567c75dfe05342a4c4b
Status: Downloaded newer image for python:3.4-alpine
---> c06adcf62f6e
Step 2/5 : ADD . /code
---> cf62e95b597f
Step 3/5 : WORKDIR /code
---> Running in 530d310c94db
Removing intermediate container 530d310c94db
---> d84245ac6307
Step 4/5 : RUN pip install -r requirements.txt
---> Running in 2c9f33c97898
DEPRECATION: Python 3.4 support has been deprecated. pip 19.1 will be the last one supporting it. Please upgrade your Python as Python 3.4 won't be maintained after March 2019 (cf PEP 429).

Step 5/5 : CMD ["python", "webapp.py"]
---> Running in ab484f9d5462

 

新版本里面Kitematic已经改名叫做Dashboard了

redis服务started，但是web服务没有start,查看日志

 

日志显示错误是，

File "webapp.py", line 7

retries = 5

^

IndentationError: expected an indented block

看起来是python脚本有问题。

https://stackoverflow.com/questions/10238770/indentationerror-expected-an-indented-block/38032036#38032036

发现是python脚本的格式化有问题，用下面的链接进行格式化

https://codebeautify.org/python-formatter-beautifier   尝试格式化了，还是报错，看来需要简单学习一下python的语法