Get Started, Part 3: Services
Estimated reading time: 7 minutesPrerequisites
Get Docker Compose. On Docker for Mac and Docker for Windows it’s pre-installed, so you’re good-to-go. On Linux systems you will need to install it directly. On pre Windows 10 systems without Hyper-V, use Docker Toolbox.
Read the orientation in Part 1.
Learn how to create containers in Part 2.
Make sure you have published the
friendlyhello
image you created by pushing it to a registry. We’ll use that shared image here.Be sure your image works as a deployed container. Run this command, slotting in your info for
username
,repo
, andtag
:docker run -p 80:80 username/repo:tag
, then visithttp://localhost/
.
Introduction
In part 3, we scale our application and enable load-balancing. To do this, we must go one level up in the hierarchy of a distributed application: the service.
- Stack
- Services (you are here)
- Container (covered in part 2)
Understanding services
In a distributed application, different pieces of the app are called “services.” For example, if you imagine a video sharing site, it probably includes a service for storing application data in a database, a service for video transcoding in the background after a user uploads something, a service for the front-end, and so on.
Services are really just “containers in production.” A service only runs one image, but it codifies the way that image runs—what ports it should use, how many replicas of the container should run so the service has the capacity it needs, and so on. Scaling a service changes the number of container instances running that piece of software, assigning more computing resources to the service in the process.
Luckily it’s very easy to define, run, and scale services with the Docker
platform – just write a docker-compose.yml
file.
Your first docker-compose.yml
File
A docker-compose.yml
file is a YAML file that defines how Docker containers
should behave in production.
docker-compose.yml
Save this file as docker-compose.yml
wherever you want. Be sure you have
pushed the image you created in Part
2 to a registry, and update this .yml
by replacing
username/repo:tag
with your image details.
version: "3"
services:
web:
# replace username/repo:tag with your name and image details
image: username/repository:tag
deploy:
replicas: 5
resources:
limits:
cpus: "0.1"
memory: 50M
restart_policy:
condition: on-failure
ports:
- "80:80"
networks:
- webnet
networks:
webnet:
This docker-compose.yml
file tells Docker to do the following:
Pull the image we uploaded in step 2 from the registry.
Run five instances of that image as a service called
web
, limiting each one to use, at most, 10% of the CPU (across all cores), and 50MB of RAM.Immediately restart containers if one fails.
Map port 80 on the host to
web
’s port 80.Instruct
web
’s containers to share port 80 via a load-balanced network calledwebnet
. (Internally, the containers themselves will publish toweb
’s port 80 at an ephemeral port.)Define the
webnet
network with the default settings (which is a load-balanced overlay network).
Wondering about Compose file versions, names, and commands?
Notice that set the Compose file to
version: "3"
. This essentially makes it swarm mode compatible. We can make use of the deploy key (only available on Compose file formats version 3.x and up) and its sub-options to load balance and optimize performance for each service (e.g.,web
). We can run the file with thedocker stack deploy
command (also only supported on Compose files version 3.x and up). You could usedocker-compose up
to run version 3 files with non swarm configurations, but we are focusing on a stack deployment since we are building up to a swarm example.You can name the Compose file anything you want to make it logically meaningful to you;
docker-compose.yml
is simply a standard name. We could just as easily have called this filedocker-stack.yml
or something more specific to our project.
Run your new load-balanced app
Before we can use the docker stack deploy
command we’ll first run:
docker swarm init
Note: We’ll get into the meaning of that command in part 4. If you don’t run
docker swarm init
you’ll get an error that “this node is not a swarm manager.”
Now let’s run it. You have to give your app a name. Here, it is set to
getstartedlab
:
docker stack deploy -c docker-compose.yml getstartedlab
See a list of the five containers you just launched:
docker stack ps getstartedlab
You can run curl http://localhost
several times in a row, or go to that URL in
your browser and hit refresh a few times. Either way, you’ll see the container
ID change, demonstrating the load-balancing; with each request, one of
the five replicas is chosen, in a round-robin fashion, to respond.
Note: At this stage, it may take up to 30 seconds for the containers to respond to HTTP requests. This is not indicative of Docker or swarm performance, but rather an unmet Redis dependency that we will address later in the tutorial.
Scale the app
You can scale the app by changing the replicas
value in docker-compose.yml
,
saving the change, and re-running the docker stack deploy
command:
docker stack deploy -c docker-compose.yml getstartedlab
Docker will do an in-place update, no need to tear the stack down first or kill any containers.
Now, re-run the docker stack ps
command to see the deployed instances reconfigured. For example, if you scaled up the replicas, there will be more
running containers.
Take down the app and the swarm
Take the app down with docker stack rm
:
docker stack rm getstartedlab
This removes the app, but our one-node swarm is still up and running (as shown
by docker node ls
). Take down the swarm with docker swarm leave --force
.
It’s as easy as that to stand up and scale your app with Docker. You’ve taken a huge step towards learning how to run containers in production. Up next, you will learn how to run this app as a bonafide swarm on a cluster of Docker machines.
Note: Compose files like this are used to define applications with Docker, and can be uploaded to cloud providers using Docker Cloud, or on any hardware or cloud provider you choose with Docker Enterprise Edition.
Recap and cheat sheet (optional)
Here’s a terminal recording of what was covered on this page:
To recap, while typing docker run
is simple enough, the true implementation
of a container in production is running it as a service. Services codify a
container’s behavior in a Compose file, and this file can be used to scale,
limit, and redeploy our app. Changes to the service can be applied in place, as
it runs, using the same command that launched the service:
docker stack deploy
.
Some commands to explore at this stage:
docker stack ls # List all running applications on this Docker host
docker stack deploy -c <composefile> <appname> # Run the specified Compose file
docker stack services <appname> # List the services associated with an app
docker stack ps <appname> # List the running containers associated with an app
docker stack rm <appname> # Tear down an application