Hey everyone,
Today I want to explain you a bit about Docker Volumes, when/where to use them and their benefits.
Remember that in the Docker Introduction I said a Docker container is stateless? For the contained data that is mostly true.
There are two differences:
- Docker Volumes
- External Connections
A completely stateless container would of course be useless for us. We couldn´t store e.g. no Grocery list or Appointments.
And we couldn´t store files like pictures from the Wedding.
So the idea is to have the docker container that is stateless but add a Volume if you want to store files and configure external connections
to e.g. issue an order.
Depending on the type of data (Grocery List Entry or Wedding Pictures) we want to store them differently. The Grocery Entry belongs to a database,
the Picture into a volume.
Both can be configured through the Stack Configuration, the external Connection to e.g. a database is normally a simple Environment Variable with the url,
while the volume is a mounted filesystem.
An example Stack configuration for a single service can look like this:
version: '3' services: myservice: image: image deploy: resources: limits: memory: 256M reservations: memory: 32M environment: - MYSQL_URL=mysql://$username:$password@$hostname:$port/$path ports: - $port
I will explain a stack configuration file in another post, so we focus only on the environment key.
Under it is an Environment Variable MYSQL_URL that can be read inside the container. So your API can read MYSQL_URL and connect to that address.
This way you can use the same docker container and just configure it locally for testing to your computer while in the production environment it points to e.g. an Amazon RDS MySQL Instance.
The Volume is somewhat different:
version: '3' services: myservice: image: image deploy: resources: limits: memory: 256M reservations: memory: 32M environment: - MYSQL_URL=mysql://$username:$password@$hostname:$port/$path ports: - $port volumes: - $volume_name:$mounted_path volumes: youtube_publish_data: external: true
As you can see we describe a volume under the volumes key. We give it a unique name, followed by the path inside the container where it should be mounted.
Additionally we add a root key volumes, under it the name of the volume and under that we set external to true, so that the data is outside of the docker container of the logic, but inside
a data container.
This means we have separated the logic from the data files. Depending on the driver it is limited to the local machine (the default we use is on the local machine).
Still this give us e.g. the possibility to have a generic downloading container that is started by a message. This container uses an external data volume for the downloaded data.
A second container processes the downloads. Therefore we need a config like this:
version: '3' services: myservice: image: image deploy: resources: limits: memory: 256M reservations: memory: 32M environment: - MYSQL_URL=mysql://$username:$password@$hostname:$port/$path ports: - $port volumes: - $volume_name:$mounted_path volumes: $volume_name: external: name: $Stackname_$volume_name
Now we can mount the same volume in two or more containers and access the data there. That is quite cool and saves us ressource for transfering the data back and forth.
Depending on your setup you might want to have it this way and just transfer out the final production file to e.g. Amazon S3 to save time and money on bandwith.
I hope that helped you to get a step further into distributed system architecture.
I´m myself a life-long student of it and every day I learn a new possibility that helps to simplify my projects.
So if you have another idea how to do things please contact me in the comments or via mail. I appreciate it.
Yours sincerely,
Frank
Sources:
(1) Docker Tip #12: A Much Better Development Experience With Volumes
(2) Using Docker Compose for NodeJS Development
(3) Understanding Volumes in Docker
(4) Docker and Continuous Integration: Code, Build, Test, Deploy
(5) Dive Into Docker – The Complete Docker Course for Developers