What exactly do we need to know about to manage docker effectively? What are the main pain points?
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The basics aren’t tough. You need to know the anatomy of a Dockerfile, and how to setup a docker-compose.yml to ease the headache of docker run. You also should know how to manage docker images, and us docker ps to find out what’s currently running. And get an interactive shell (docker exec -it imageid). You’ll also make friends with inspect. But what else?
1. Manage image bloat
Docker images can get quite large. Even as you try to pair them down they can grow. Why is this?
Turns out the architecture of docker means as you add more stuff, it creates more “layers”. So even as you delete files, the lower or earlier layers still contain your files.
One option, during a package install you can do this:
RUN apt-get update && apt-get install -y mypkg && rm -rf /var/lib/apt/lists/*
This will immediately cleanup the crap that apt-get built from, without it ever becoming permanent in that layer. Cool! As long as you use “&&” it is part of that same RUN command, and thus part of that same layer.
Another option is you can flatten a big image. Something like this should work:
$ docker export 0453814a47b3 | docker import — newimage
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2. Orchestrate
Running docker containers on dev is great, and it can be a fast and easy way to get things running. Plus it can work across dev environments well, so it solves a lot of problems.
But what about when you want to get those containers up into the cloud? That’s where orchestration comes in. At the moment you can use docker’s own swarm or choose fleet or mesos.
But the biggest players seem to be kubernetes & ECS. The former of course is what all the cool kids in town are using, and couple it with Helm package manager, it becomes very manageable system. Get your pods, services, volumes, replicasets & deployments ready to go!
On the other hand Amazon is pushing ahead with it’s Elastic Container Service, which is native to AWS, and not open source. It works well, allowing you to apply a json manifest to create a task. Then just as with kubernetes you create a “service” to run one or more copies of that. Think of the task as a docker-compose file. It’s in json, but it basically specifies the same types of things. Entrypoint, ports, base image, environment etc.
For those wanting to go multi-cloud, kubernetes certainly has an appeal. But amazon is on the attack. They have announced a service to further ease container deployments. Dubbed Amazon Fargate. Remember how Lambda allowed you to just deploy your *code* into the cloud, and let amazon worry about the rest? Imaging you can do that with containers, and that’s what Fargate is.
Check out what Krish has to say — Why Kubernetes should be scared of AWS
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3. Registries & Deployment
There are a few different options for where to store those docker images.
One choice is dockerhub. It’s not feature rich, but it does the job. There is also Quay.io. Alternatively you can run your own registry. It’s as easy as:
$ docker run -d -p 5000:5000 registry:2
Of course if you’re running your own registry, now you need to manage that, and think about it’s uptime, and dependability to your deployment pipeline.
If you’re using ECS, you’ll be able to use ECR which is a private docker registry that comes with your AWS account. I think you can use this, even if you’re not on ECS. The login process is a little weird.
Once you have those pieces in place, you can do some fun things. Your jenkins deploy pipeline can use docker containers for testing, to spinup a copy of your app just to run some unittests, or it can build your images, and push them to your registry, for later use in ECS tasks or Kubernetes manifests. Awesome sauce!
Related: Is Amazon Web Services too complex for small dev teams?
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Originally published at Scalable Startups.
