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---
last_updated: 2017-11-10
---
# Autoscaling GitLab Runner on AWS
One of the biggest advantages of GitLab Runner is its ability to automatically
spin up and down VMs to make sure your builds get processed immediately. It's a
great feature, and if used correctly, it can be extremely useful in situations
where you don't use your Runners 24/7 and want to have a cost-effective and
scalable solution.
## Introduction
In this tutorial, we'll explore how to properly configure a GitLab Runner in
AWS that will serve as the bastion where it will spawn new Docker machines on
demand.
In addition, we'll make use of [Amazon's EC2 Spot instances](https://aws.amazon.com/ec2/spot/)
which will greatly reduce the costs of the Runner instances while still using
quite powerful autoscaling machines.
## Prerequisites
The first step is to install GitLab Runner in an EC2 instance that will serve
as the bastion to spawning new machines. This doesn't have to be a powerful
machine since it will not run any jobs itself, a `t2.micro` instance will do.
This machine will be a dedicated host since we need it always up and running,
thus it will be the only standard cost.
NOTE: **Note:**
For the bastion instance, choose a distribution that both Docker and GitLab
Runner support, for example either Ubuntu, Debian, CentOS or RHEL will work fine.
Install the prerequisites:
1. Log in your server
1. [Install GitLab Runner from the official GitLab repository](https://docs.gitlab.com/runner/install/linux-repository.html)
1. [Install Docker](https://docs.docker.com/engine/installation/#server)
1. [Install Docker Machine](https://docs.docker.com/machine/install-machine/)
You can now move on to the most important part, configuring GitLab Runner.
## Configuring GitLab Runner to use the AWS machine driver
Before configuring the GitLab Runner, you need to first register it, so that
it connects with your GitLab instance.
Edit `/etc/gitlab-runner/config.toml`:
```toml
concurrent = 3
check_interval = 0
[[runners]]
name = "gitlab-aws-autoscaler"
url = "<url to your GitLab CI host>"
token = "<registration token>"
executor = "docker+machine"
limit = 4
[runners.docker]
image = "alpine"
privileged = true
disable_cache = false
volumes = ["/cache"]
[runners.cache]
Type = "s3"
ServerAddress = "s3.amazonaws.com"
AccessKey = "<your AWS Access Key ID>"
SecretKey = "<your AWS Secret Access Key>"
BucketName = "<the bucket where your cache should be kept>"
BucketLocation = "us-east-1"
Shared = true
[runners.machine]
IdleCount = 1
IdleTime = 1800
MaxBuilds = 100
MachineDriver = "amazonec2"
MachineName = "gitlab-docker-machine-%s"
OffPeakPeriods = ["* * 0-7,19-23 * * mon-fri *", "* * * * * sat,sun *"]
OffPeakIdleCount = 0
OffPeakIdleTime = 1200
MachineOptions = [
"amazonec2-access-key=XXXX",
"amazonec2-secret-key=XXXX",
"amazonec2-region=us-east-1",
"amazonec2-vpc-id=vpc-xxxxx",
"amazonec2-subnet-id=subnet-xxxxx",
"amazonec2-use-private-address=true",
"amazonec2-tags=Name,gitlab-runner-autoscale",
"amazonec2-security-group=docker-machine-scaler",
"amazonec2-instance-type=m4.2xlarge",
"amazonec2-ssh-user=ubuntu",
"amazonec2-ssh-keypath=/etc/gitlab-runner/certs/gitlab-aws-autoscaler",
"amazonec2-zone=a",
"amazonec2-root-size=32",
]
```
Under `MachineOptions` you can add anything that the [AWS Docker Machine driver
supports](https://docs.docker.com/machine/drivers/aws/#options).
## Cutting down costs with Amazon EC2 Spot instances
As described by Amazon:
>
Amazon EC2 Spot instances allow you to bid on spare Amazon EC2 computing capacity.
Since Spot instances are often available at a discount compared to On-Demand
pricing, you can significantly reduce the cost of running your applications,
grow your application’s compute capacity and throughput for the same budget,
and enable new types of cloud computing applications.
In `/etc/gitlab-runner/config.toml` under the `MachineOptions` section:
```toml
MachineOptions = [
"amazonec2-request-spot-instance=true",
"amazonec2-spot-price=0.03",
"amazonec2-block-duration-minutes=60"
]
```
With this configuration, Docker Machines are created on Spot instances with a
maximum bid price of $0.03 per hour and the duration of the Spot instance is
capped at 60 minutes.
To learn more about Amazon EC2 Spot instances, visit the following links:
- https://aws.amazon.com/ec2/spot/
- https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/spot-requests.html
- https://aws.amazon.com/blogs/aws/focusing-on-spot-instances-lets-talk-about-best-practices/
### Caveats of Spot instances
If the Spot price raises, the auto-scale Runner would fail to create new machines.
This eventually eats 60 requests and then AWS won't accept any more. Then once
the spot price is acceptable, you are locked out for a bit because the call amount
limit is exceeded.
You can use the following command in the bastion machine to see the Docker Machines
state:
```sh
docker-machine ls -q --filter state=Error --format "{{.NAME}}"
```
NOTE: **Note:**
Follow [issue 2771](https://gitlab.com/gitlab-org/gitlab-runner/issues/2771)
for more information.
## Conclusion
Using the autoscale feature of GitLab Runner can save you both time and money.
Using the spot instances that AWS provides can save you even more.
You can read the following user cases from which this tutorial was influenced:
- [HumanGeo - Scaling GitLab CI](http://blog.thehumangeo.com/gitlab-autoscale-runners.html)
- [subtrakt Health - Autoscale GitLab CI Runners and save 90% on EC2 costs](https://substrakthealth.com/news/gitlab-ci-cost-savings/)
|
