Articles, notes and random thoughts on Software Development and Technology
I’m starting to dabble with docker-compose to link up some container goodness. If you’ve followed my other Docker related posts the past couple of days (here), then you might have noticed that I have something Raspberry Pi related cooking 🙂
Although I’ll have to redo these with a Pi compatible base images, to get MongoDB running in one container with a separate data volume container is actually pretty simple. Here’s what I ended up with. To start it up, ‘docker-compose up -d’ and you’re up and running (copy this to docker-compose.yml):
mongodata: image: mongo:3.2 volumes: - /data/db entrypoint: /bin/bash mongo: image: mongo:3.2 volumes_from: - mongodata ports: - "27017:27017"
I’m still scratching the surface getting up to speed with Docker, but here’s some rough notes for what seems to be a typical development workflow.
Build an image (from Dockerfile):
docker build -t imagename .
Run an image (create a container):
docker run -d -p port:port imagename
If pushing an image to a local Registry to share to other machines:
Tag an image:
docker tag imagename ip-of-registry:port/imagename
Push image to registry:
docker push ip-of-registry:port/imagename
For my other notes and experiences in Dockerland so far, see here.
There’s plenty of things that amaze me about Docker, but one of the things I find interesting is the number of available images with all sorts of stuff preconfigured and ready to spin up, including Docker management related tools like Shipyard that also run within Docker containers themselves.
Installing couldn’t be simpler, just pull down a script and run it, and it pulls down a number of images and spins them up:
curl -sSL https://shipyard-project.com/deploy | bash -s
Within a few seconds Shipyard is up and running, and after logging on, you get the snappy looking dashboard:
Now, off to do a bit more studying to configure a spin up a Swarm cluster 🙂