portable, lightweight, & interoperable docker containers ... portable, lightweight, & interoperable

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  • Jérôme Petazzoni Tinkerer Extraordinaire Docker, Inc

    Alexander Larsson Principal Software engineer Red Hat, Inc

    Portable, lightweight, & interoperable Docker containers across Red Hat solutions

  • What?

  • Why?

  • Deploy everything

    •Webapps •Backends •SQL, NoSQL •Big data •Message queues •… and desktop apps and more

    If it runs on Linux, it will run in a Docker container!

  • Deploy almost everywhere

    •Linux servers! •Virtual machines •Bare metal •Any distro •Recent kernel

    Currently: focus on x86_64. (But people reported success on arm.)

  • Deploy reliably & consistently

  • Deploy reliably & consistently

    • If it works locally, it will work on the server •With exactly the same behavior •Regardless of versions •Regardless of distros •Regardless of dependencies

  • Deploy efficiently

    •Containers are lightweight •Typical laptop runs 10-100 containers easily •Typical server can run 100-1000 containers

    •Containers can run at native speeds •Lies, damn lies, and other benchmarks: http://qiita.com/syoyo/items/bea48de8d7c6d8c73435

  • The performance! It's over 9000!

    Native NativeDocker containerNative Docker container

  • Is there really no overhead at all?

    •Processes are isolated, but run straight on the host •CPU performance = native performance

    •Memory performance = a few % shaved off for (optional) accounting

    •Network performance = small overhead; can be reduced to zero

    •Disk I/O performance = copy-on-write overhead; can be reduced to zero (use volumes)

  • … Container ?

  • Containers look like lightweight VMs

    •Own process space •Own network interface •Can run stuff as root •Can have its own /sbin/init (different from the host)

    « Machine Container »

  • Containers are really chroot on steroids

    •Can also not have its own /sbin/init •Container = isolated process(es) •Share kernel with host •No device emulation (neither HVM nor PV)

    « Application Container »

  • How does it work? Isolation with namespaces

    •pid •mnt •net •uts • ipc •user

  • How does it work? Isolation with cgroups

    •memory •cpu •blkio •devices

  • How does it work? Copy-on-write storage

    •Create a new machine instantly (Instead of copying its whole filesystem)

    •Storage keeps track of what has changed •Multiple storage plugins available (AUFS, device mapper, BTRFS...)

  • Docker: the big picture

    •Open Source engine to commoditize container technology •Using copy-on-write for quick provisioning •Allowing to create and share images •Standard format for containers •Standard, reproducible way to easily build trusted images (Dockerfile, Stackbrew...)

    •Hosted services to work and cooperate around containers (e.g. docker.io hosted registry for public and private images)

  • Authoring Docker images

  • Authoring images with run/commit

  • 1) docker run centos bash

    2) yum install this and that

    3) docker commit

    4) docker run bash

    5) git clone git://.../mycode

    6) pip install -r requirements.txt

    7) docker commit

    8) repeat steps 4-7 as necessary

    9) docker tag

    10) docker push

  • Authoring images with run/commit

    •Pros •Convenient, nothing to learn •Can roll back/forward if needed

    •Cons •Manual process • Iterative changes stack up •Full rebuilds are boring, error-prone

  • Authoring images with a Dockerfile

  • FROM fedora

    RUN yum -y update RUN yum -y install mongodb-server RUN mkdir -p /data/db RUN sed -i 's,dbpath=/var/lib/mongodb,dbpath=/data,' /etc/mongodb.conf

    VOLUME /data EXPOSE 27017 CMD /usr/bin/mongod

    docker build -t jpetazzo/mongodb .

  • Authoring images with a Dockerfile

    •Minimal learning curve •Rebuilds are easy and reliable •Caching system makes rebuilds faster •Single file to define the whole environment!

  • Docker on Red Hat

  • Red Hat Enterprise Linux 6

    •Available in EPEL: yum install docker-io •Works in 6.4 and later •6.5 has more complete network namespace support •Not supported, but much of the underlying kernel features are •Packages also work on CentOS

  • Red Hat Enterprise Linux 7 Beta

    •Available in EPEL7 beta: yum install docker-io •More recent kernel

  • Fedora

    •Available since Fedora 19: yum install docker-io

  • Storage backends

    •AUFS •Not in upstream kernel or in Red Hat kernels

    •Device Mapper •Contributed by Red Hat •Works everywhere

    •BTRFS •Contributed by Red Hat • /var/lib/docker must be on a btrfs filesystem •Tech preview in RHEL6 kernel

  • Union Filesystems (AUFS, overlayfs)

    Copy-on-write block devices

    Snapshotting filesystems

    Provisioning Superfast Supercheap

    Fast Cheap

    Fast Cheap

    Changing small files

    Superfast Supercheap

    Fast Costly

    Fast Cheap

    Changing large files

    Slow (first time) Inefficient (copy-up!)

    Fast Cheap

    Fast Cheap

    Diffing Superfast Slow Superfast

    Memory usage Efficient Inefficient (at high densities)

    Inefficient (but may improve)

    Drawbacks Random quirks AUFS not mainline

    Higher disk usage Great performance (except diffing)

    ZFS not mainline BTRFS not as nice

    Bottom line Ideal for PAAS and high density things

    Dodge Ram 3500 This is the future (Probably!)

  • Running your own registry

    •yum install docker-registry •Fedora >= 19 •EPEL 6 •EPEL 7 Beta

    Push an image: docker tag 8dbd9e392a96 my-machine:5000/image docker push my-machine:5000/image

    Use it: docker run my-machine:5000/image

  • Base images

    •Fedora •Official images available as “fedora” •Current versions: Fedora 20, rawhide

    •CentOS •Official images available as “centos” •Current version: 6.4

  • RHEL base images

    •Distribution problematic •Working on a nice solution •For now, build base images on entitled RHEL machines •Use yum –installroot + docker import •Distribution rules same as any other Red Hat content

  • Docker, from development to production

  • One-time setup

    •On your servers (Linux) •Packages (not only RPM, but also Ubuntu, Debian, Gentoo, Arch...) •Single binary install (Golang FTW!) •Easy provisioning on Rackspace, Digital Ocean, EC2, GCE...

    •On your developer environment (Linux, OS X, Windows) • In your regular Linux VM (Vagrant or other) •boot2docker (25 MB VM image) •Natively (if you run Linux)

  • The Docker workflow 1/2

    •Work in developer environment (local machine or container)

    •Other services (databases etc.) in containers (and behave just like the real thing!)

    •Whenever you want to test « for real »: •Build in seconds •Run instantly

  • The Docker workflow 2/2

    Satisfied with your local build? •Push it to a registry (public or private) •Run it (automatically!) in CI/CD •Run it in production •Happiness!

    Something goes wrong? Rollback painlessly!

  • Running containers

    •SSH to Docker host and manual pull+run •REST API (feel free to add SSL certs, OAuth...) •Maestro NG (https://github.com/signalfuse/maestro-ng) •Many Open Source PAAS built on Docker: Deis, Flynn, … •And of course, OpenStack!

  • OpenStack integration

    •Nova (OpenStack Compute) •Provisions and manages virtual machines •Docker hypervisor driver •Deploy containers instead of VMs with the same API •Available in Havana release

    •Glance (Image Service) •Docker registry integration

  • OpenStack integration

    •Heat (OpenStack Orchestration) •Template driven engine for automated deployment of infrastructure •Docker plugin •Allows use of full Docker API in your templates •Available in Icehouse release

  • HeatTemplateFormatVersion: '2012-12-12' Parameters: {} Mappings: {} Resources: Blog: Type: OS::Heat::Docker Properties: Image: samalba/wordpress Env: - {"Fn::Join": ["=", ["DB_HOSTNAME", {"Fn::GetAtt": ["Database", "NetworkIp"]}]]} - {"Fn::Join": ["=", ["DB_PORT", {"Fn::GetAtt": ["Database", "NetworkTcpPorts"]}]]} - {"Fn::Join": ["=", ["DB_PASSWORD", {"Fn::GetAtt": ["Database", "LogsHead"]}]]} Database: Type: OS::Heat::Docker Properties: Image: samalba/mysql Outputs: BlogURL: Value: {"Fn::Join": ["", ["http://", {"Fn::GetAtt": ["Blog", "NetworkIp"]}, ":", {"Fn::GetAtt": ["Blog", "NetworkTcpPorts"]}, "/"] ]} Description: Blog URL


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