Azure-in-bullet-points

Container agents

• The agent will first fetch and start the container.
  • Then, each step of the job will run inside the container
    • or you can set agent on task level
• Linux

  • E.g.:

    pool:
      vmImage: 'ubuntu-16.04'
    container: ubuntu:16.04
    steps:
    - script: printenv
    

  • On your agent host, ensure:
    • Docker is installed
    • Agent has permission to access the Docker daemon
  • Container requirements:
    • Bash
    • glibc-based
    • Can run Node.js (which the agent provides)
    • Does not define an ENTRYPOINT
    • USER has access to groupadd and other privileges commands without sudo
• Windows (e.g.):

pool:
  vmImage: 'windows-2019'
container: mcr.microsoft.com/windows/servercore:ltsc2019
steps:
- script: set

• Service containers
  • Spin up multiple containers
  • Automatically create, network, and manage the lifecycle

  • E.g.:

    resources:
      containers:
      - container: my_container
        image: ubuntu:16.04
      - container: nginx
        image: nginx
      - container: redis
        image: redis
    
    pool:
      vmImage: 'ubuntu-16.04'
    
    container: my_container
    
    services:
      nginx: nginx
      redis: redis
    
    steps:
    - script: |
        apt install -y curl
        curl nginx
        apt install redis-tools
        redis-cli -h redis ping
    

    • Fetches the latest nginx and redis containers from Docker Hub and then starts the containers
    • The containers are networked together so that they can reach each other by their services name.
    • Pipeline then runs the apt, curl and redis-cli commands inside the ubuntu:16.04 container.
    • From inside this job container, the nginx and redis host names resolve to the correct services using Docker networking
    • All containers on the network automatically expose all ports to each other

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