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Using the Docker execution environment

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You can use the Docker execution environment to run your jobs in Docker containers. The Docker execution environment is accessed using the Docker executor. Using Docker increases performance by building only what is required for your application.

Specify a Docker image in your .circleci/config.yml file to spin up a container. All steps in your job will be run in this container.

jobs:
  my-job:
    docker:
      - image: cimg/node:lts

A container is an instance of a specified Docker image. The first image listed in your configuration for a job is referred to as the primary container image and this is where all steps in the job will run. Secondary containers can also be specified to run alongside for running services, such as, databases. If you are new to Docker, see the Docker Overview documentation for concepts.

CircleCI maintains convenience images on Docker Hub for popular languages. See the CircleCI Developer Hub for a complete list of image names and tags.

Specifying Docker images

Docker images may be specified in a few ways:

  • By the image name and version tag on Docker Hub, or

  • By using the URL to an image in a registry.

Nearly all of the public images on Docker Hub and other Docker registries are supported by default when you specify the docker: key in your config.yml file. If you want to work with private images/registries, refer to Using Docker Authenticated Pulls.

The following examples show how you can use public images from various sources:

CircleCI’s public convenience images on Docker Hub

  • name:tag

    • cimg/node:14.17-browsers

  • name@digest

    • cimg/node@sha256:aa6d08a04d13dd8a...

Public images on Docker Hub

  • name:tag

    • alpine:3.13

  • name@digest

    • alpine@sha256:e15947432b813e8f...

Public images on Docker registries

  • image_full_url:tag

    • gcr.io/google-containers/busybox:1.24

  • image_full_url@digest

    • gcr.io/google-containers/busybox@sha256:4bdd623e848417d9612...

Available Docker resource classes

The resource_class key allows you to configure CPU and RAM resources for each job.

Specify a resource class using the resource_class key, as follows:

jobs:
  build:
    docker:
      - image: cimg/base:current
    resource_class: xlarge
    steps:
    #  ...  other config

x86

For the Docker execution environment, the following resources classes are available for the x86 architecture:

ClassvCPUsRAMCloudServer

small

1

2GB

medium

2

4GB

medium+

3

6GB

large

4

8GB

xlarge

8

16GB

2xlarge

16

32GB

2xlarge+

20

40GB

Arm

The following resource classes are available for Arm with Docker:

ClassvCPUsRAMCloudServer

arm.medium

2

8 GB

arm.large

4

16 GB

arm.xlarge

8

32 GB

arm.2xlarge

16

64 GB

View resource usage

To view the compute resource usage for the duration of a job in the CircleCI web app:

  1. Select Dashboard from the sidebar menu

  2. Use the dropdown menus to select a project, and a branch

  3. Expand your workflow ( )

  4. Select a job by clicking on the job name

  5. Select the Resources tab to view CPU and RAM usage for the duration of the job

You can use these insights to decide whether to make changes to the job’s configured resource class. You can also access resource class Insights.

Resources tab

Docker benefits and limitations

Docker also has built-in image caching and enables you to build, run, and publish Docker images via Remote Docker. Consider the requirements of your application as well. If the following are true for your application, Docker may be the right choice:

  • Your application is self-sufficient.

  • Your application requires additional services to be tested.

  • Your application is distributed as a Docker image (requires using Remote Docker).

  • You want to use docker-compose (requires using Remote Docker).

Choosing Docker limits your runs to what is possible from within a Docker container (including our Remote Docker feature). For instance, if you require low-level access to the network or need to mount external volumes, consider using machine.

There are tradeoffs to using a docker image versus an Ubuntu-based machine image as the environment for the container, as follows:

Capabilitydockermachine

Start time

Instant

Instant for most (1)

Clean environment

Yes

Yes

Custom images

Yes (2)

No

Build Docker images

Yes (3)

Yes

Full control over job environment

No

Yes

Full root access

No

Yes

Run multiple databases

Yes (4)

Yes

Run multiple versions of the same software

No

Yes

Docker layer caching

Yes

Yes

Run privileged containers

No

Yes

Use Docker compose with volumes

No

Yes

Configurable resources (CPU/RAM)

Yes

Yes

(1) Some less commonly used execution environments may see up to 90 seconds of start time.

(3) Requires using Remote Docker.

(4) While you can run multiple databases with Docker, all images (primary and secondary) share the underlying resource limits. Performance in this regard will be dictated by the compute capacities of your plan.

For more information on machine, see the next section below.

Docker image best practices

  • If you encounter problems with rate limits imposed by your registry provider, using authenticated Docker pulls may grant higher limits.

  • CircleCI has partnered with Docker to ensure that our users can continue to access Docker Hub without rate limits. As of November 1st 2020, with few exceptions, you should not be impacted by any rate limits when pulling images from Docker Hub through CircleCI. However, these rate limits may go into effect for CircleCI users in the future. We encourage you to add Docker Hub authentication to your CircleCI configuration and consider upgrading your Docker Hub plan, as appropriate, to prevent any impact from rate limits in the future.

  • Avoid using mutable tags like latest or 1 as the image version in your config.yml file. It is best practice to use precise image versions or digests, like redis:3.2.7 or redis@sha256:95f0c9434f37db0a4f... as shown in the examples. Mutable tags often lead to unexpected changes in your job environment. CircleCI cannot guarantee that mutable tags will return an up-to-date version of an image. You could specify alpine:latest and actually get a stale cache from a month ago.

  • If you experience increases in your run times due to installing additional tools during execution, consider creating and using a custom-built image that comes with those tools pre-installed. See the Using Custom-Built Docker Images page for more information.

  • When you use AWS ECR images, it is best practice to use us-east-1 region. Our job execution infrastructure is in us-east-1 region, so having your image on the same region reduces the image download time.

  • If your pipelines are failing despite there being little to no changes in your project, you may need to investigate upstream issues with the Docker images being used.

More details on the Docker executor are available on the Configuration reference page.

Using multiple Docker images

It is possible to specify multiple images for your job. Each image will be used to spin up a separate container.

Using multiple containers for a job will be useful if you need to use a database for your tests, or for some other required service.

When using a multi-container job setup, all containers run in a common network and every exposed port will be available on localhost. All containers can communicate with one another. It is also possible to change this hostname using the name key. For a full list of options, see the Configuration reference.

In a multi-image configuration job, all steps are executed in the container created by the first image listed.

jobs:
  build:
    docker:
    # Primary container image where all steps run.
     - image: cimg/base:current
    # Secondary container image on common network.
     - image: cimg/mariadb:10.6

    steps:
      # command will execute in an Ubuntu-based container
      # and can access MariaDB on localhost
      - run: sleep 5 && nc -vz localhost 3306

RAM disks

A RAM disk is available at /mnt/ramdisk that offers a temporary file storage paradigm, similar to using /dev/shm. Using the RAM disk can help speed up your build, provided that the resource_class you are using has enough memory to fit the entire contents of your project (all files checked out from git, dependencies, assets generated etc).

The simplest way to use this RAM disk is to configure the working_directory of a job to be /mnt/ramdisk:

jobs:
  build:
    docker:
     - image: alpine

    working_directory: /mnt/ramdisk

    steps:
      - run: |
          echo '#!/bin/sh' > run.sh
          echo 'echo Hello world!' >> run.sh
          chmod +x run.sh
      - run: ./run.sh

Caching Docker images

The time it takes to spin up a Docker container to run a job can vary based on several different factors, such as the size of the image and if some, or all, of the layers are already cached on the underlying Docker host machine.

If you are using a more popular image, such as CircleCI convenience images, then cache hits are more likely for a larger number of layers. Most of the popular CircleCI images use the same base image. The majority of the base layers are the same between images, so you have a greater chance of having a cache hit.

The environment has to spin up for every new job, regardless of whether it is in the same workflow or if it is a re-run/subsequent run. (CircleCI never reuses containers, for security reasons.) Once the job is finished, the container is destroyed. There is no guarantee that jobs, even in the same workflow, will run on the same Docker host machine. This implies that the cache status may differ.

In all cases, cache hits are not guaranteed, but are a bonus convenience when available. With this in mind, a worst-case scenario of a full image pull should be accounted for in all jobs.

In summary, the availability of caching is not something that can be controlled via settings or configuration, but by choosing a popular image, such as CircleCI convenience images, you will have more chances of hitting cached layers in the "Spin Up Environment" step.

Next steps

Find out more about using Convenience Images with the Docker executor.


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