Deploy CircleCI Arm Native Workflows on AWS EC2 Graviton
Introduction
Get Started with CircleCI on AWS Graviton
Create an AWS EC2 Arm64 Graviton Instance
Install CircleCI CLI
Create a resource class in CircleCI
Install CircleCI machine runner on AWS Graviton
Verify CircleCI Arm64 Self-Hosted runner
Next Steps
Deploy CircleCI Arm Native Workflows on AWS EC2 Graviton
Who is this for?
This is an introductory topic for developers and DevOps engineers who want to set up and run CircleCI Arm native workflows on Linux Arm64 virtual machines. You'll use Amazon EC2 instances powered by AWS Graviton (Neoverse N1) and self-hosted runners.
What will you learn?
Upon completion of this Learning Path, you will be able to:
- Create an Amazon EC2 Arm64 virtual machine
- Install and configure CircleCI self-hosted machine runners on Arm64
- Verify the runner by running a simple workflow and test computation
Prerequisites
Before starting, you will need the following:
- An AWS account with billing enabled
- A CircleCI account
- Basic understanding of CircleCI workflows, jobs and resource classes
Summary
This summary was drafted with an approved AI-assisted workflow and reviewed by Arm contributors before publication. Human technical review remains part of the process so the final page reflects engineering rigor, accuracy, and Arm editorial standards.
m6g.large) on Linux and install the CircleCI CLI to work with configurations and pipelines from the terminal. In the CircleCI dashboard, you’ll create a resource class to link a self-hosted machine runner to the correct namespace. Then, you’ll install the CircleCI machine runner on the Arm64 instance using the CircleCI package repository for Debian/Ubuntu systems. By the end, you’ll execute a workflow and test computation to verify that jobs run on the self-hosted Graviton runner as configured.Frequently asked questions
These FAQs were drafted with an approved AI-assisted workflow and reviewed by Arm contributors before publication. Human technical review remains part of the process so the final page reflects engineering rigor, accuracy, and Arm editorial standards.
m6g.large, and choose a Linux AMI such as Ubuntu in the AWS Management Console. You’ll follow a console-based instance launch workflow.