Start Building for Free
CircleCI.comAcademyBlogCommunitySupport

Install machine runner 3.0 on Docker

1 month ago3 min read
Cloud
Server v4.4+
On This Page

This page describes how to install CircleCI’s machine runner 3.0 with the Docker executor. If you are looking to set up self-hosted runners in a private Kubernetes cluster, visit the Container runner page.

Machine-based approach with Docker

Prerequisites

Resource requirements

The host needs to have Docker installed. Once the runner container is started, the container will immediately attempt to start running jobs. The container will be reused to run more jobs indefinitely until it is stopped.

The number of containers running in parallel on the host is constrained by the host’s available resources and your jobs' performance requirements.

Self-hosted runner terms agreement

1. Create namespace and resource class

In order to install self-hosted runners, you will need to create a namespace and authentication token by performing the steps listed below. Please note that to create resource classes and tokens you need to be an organization administrator in the VCS provider.

You can view your installed runners on the inventory page in the web app or your CircleCI server app, by clicking Self-Hosted Runners on the left navigation.

  1. Create a namespace for your organization’s self-hosted runners. Each organization can only create a single namespace. We suggest using a lowercase representation of your CircleCI organization’s account name. If you already use orbs, this namespace should be the same namespace orbs use.

    Use the following command to create a namespace:

    circleci namespace create <name> --org-id <your-organization-id>
  2. Create a resource class for your self-hosted runner’s namespace using the following command:

    circleci runner resource-class create <namespace>/<resource-class> <description> --generate-token

    Make sure to replace <namespace> and <resource-class> with your org namespace and desired resource class name, respectively. You may optionally add a description.

    Example: circleci runner resource-class create my-namespace/my-resource-class my-description --generate-token.

    The resource class token is returned after the runner resource class is successfully created.

2. Create a Dockerfile that extends the machine runner 3.0 image

Create a Dockerfile.runner.extended file. In this example, Python 3 is installed on top of the base image.

FROM circleci/runner-agent:machine-3
RUN sudo apt-get update; \
    sudo apt-get install --no-install-recommends -y \
        python3

3. Build the Docker image

docker build --file ./Dockerfile.runner.extended .

4. Start the Docker container

When the container starts, it will immediately attempt to start running jobs.

Stopping the Docker container

docker stop <container-name>

Remove the Docker container

In some cases you might need to fully remove a stopped machine runner container from the system, such as when recreating a container using the same name.

docker stop <container-name>; docker rm <container-name>;

Migrating from launch agent

To migrate from launch agent to machine runner 3.0 on Docker, stop and remove the launch agent containers and replace them with machine runner 3.0 containers, using the commands described above.

Machine runner configuration example

The fields you must set for a specific job to run using your machine runners are:

  • machine: true

  • resource_class: <namespace>/<resource-class>

Simple example of how you could set up a job:

version: 2.1

workflows:
  build-workflow:
    jobs:
      - runner
jobs:
  runner:
    machine: true
    resource_class: <namespace>/<resource-class>
    steps:
      - run: echo "Hi I'm on Runners!"

Suggest an edit to this page

Make a contribution
Learn how to contribute