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Docker Do's And Don'ts

Vincent Viallet Vincent Viallet on

I gave a short (last minute) presentation at the Shanghai Docker meetup last Saturday at VMware's office. We talked about how experience using Docker while building devo.ps and gave some basic advices as to what to do (and what not to).

Why we chose Docker?

  • Separation of concerns and Scalability: devo.ps is a complex system. We want to isolate features as micro-services and be able, down the road, to easily scale horizontally.
  • Deployment cycles: since we're dealing with a complex stack, the ability to update parts of the systems independently was a huge plus.

How we use Docker?

  • Bus-centric architecture: we basically have RabbitMQ tying up a lot of micro-services.
  • Non-ephemeral containers: we actually treat containers more like VMs with fairly long life-cycles.

The don'ts

  • Don't rush into building your own tools: if you hit a wall, others probably have. GitHub and #docker on IRC (@freenode) are your friends; ask around and make sure you're not building something already solved. For example, we used our DIY DNS management approach until the recent etcd update.
  • If you do write your own tools, don't go crazy: keep if light and simple. Docker is moving extremely fast, your work may become obsolete next week. It happened to us with containers orchestration; we wrote our own tool which became useless 2 weeks later.
  • Don't think Docker will solve all your (DevOps) problems: Docker is just another tool, it adds a layer of complexity, it isn't pixie dust. Use containers for what it's good at, not because it's the new hot thing.

The do's

  • Use caching properly for your Dockerfiles: docker containers are built very quickly as long as you make use of the caching capability. A quick set of gotchas and advices:
    • ADD & VOLUMES are cache invalidators.
    • RUN commands are cached while unchanged.
    • Dockerfile execution is sequential, hence: order matters and a changed step deprecate the next caches.
    • Group your RUN commands (shell sequences) together per type (e.g. ssh related). This allows you to tune and forget a "feature" of your container and focus on the next one without ever blowing up your cache.
    • Maintain common command orders in between your various Dockerfiles. This allow to use "common" caching from one container to another for as long as they share common features
  • Maintain your containers in a registry: it lets you deploy quickly, revert quickly and have matching versions of your containers. Same thing apply for your Dockerfiles: use a VCS. See http://blog.docker.com/2013/07/how-to-use-your-own-registry/, Docker registry & Docker hub.
  • Plan your containers life-cycles: if you are using Docker for computing purpose this may not be critical, but if you intend on having long-running containers it is absolutely required. Among other things:
    • Define what data are persistent, ephemeral or shared.
    • Define the best fit between named or anonymous volumes or devices (LVM / disks). See for example our take on data migration of named docker containers.
    • How will your data be loaded? Does it need to be prepared at run time? Does it have proper permissions/ownership?
  • Log all the things: this seems easy with stdout/err on a few containers, but quickly become complex once you start adding up containers or when you start running services that do not puke their logs on the console. We use a combination of syslog, log.io, logstash and Kibana.
  • Define a proper start logic: containers are not servers, the start workflow is different:
    • there are no init scripts on containers.
    • 1 container = 1 exec on start, if the command exit, the container stops, use run scripts when needed,
    • supervisord lets you manage your services ala init (hurray!).

A few more things

  • Flocker: lets you manage a fleet of containers and handle data migration.
  • Maestro-ng: containers management.
  • Using docker for safe or multi-tenancy execution: safely executing arbitrary code or multiple applications on the same machine. That's actually what we're doing with one of our side projects.

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