pepperize.cdk-autoscaling-gitlab-runner 0.0.120

AWS CDK GitLab Runner autoscaling on EC2 instances using docker+machine executor.

AWS CDK GitLab Runner autoscaling on EC2

This project provides a CDK construct to execute jobs on auto-scaled EC2 instances using the Docker Machine executor.

Running out of Runner minutes, using Docker-in-Docker (dind), speed up jobs with shared S3 Cache, cross compiling/building environment multiarch, cost effective autoscaling on EC2, deploy directly from AWS accounts (without AWS Access Key), running on Spot instances, having a bigger build log size

Install

TypeScript

npm install @pepperize/cdk-autoscaling-gitlab-runner

or

yarn add @pepperize/cdk-autoscaling-gitlab-runner

Python

pip install pepperize.cdk-autoscaling-gitlab-runner

C# / .Net

dotnet add package Pepperize.CDK.AutoscalingGitlabRunner

Quickstart

1. Create a new AWS CDK App in TypeScript with projen

   mkdir gitlab-runner
   cd gitlab-runner
   git init
   npx projen new awscdk-app-ts
   

2. Configure your project in .projenrc.js

   • Add deps: ["@pepperize/cdk-autoscaling-gitlab-runner"],

3. Update project files and install dependencies

   npx projen
   

4. Register a new runner

   Registering runners:

   • For a shared runner, go to the GitLab Admin Area and click Overview > Runners
   • For a group runner, go to Settings > CI/CD and expand the Runners section
   • For a project runner, go to Settings > CI/CD and expand the Runners section

   Optionally enable: Run untagged jobs [x] Indicates whether this runner can pick jobs without tags

   See also Registration token vs. Authentication token

5. Retrieve a new runner authentication token

   Register a new runner

   curl --request POST "https://gitlab.com/api/v4/runners" --form "token=<your register token>" --form "description=gitlab-runner" --form "tag_list=pepperize,docker,production"
   

6. Add to your main.ts

   # Example automatically generated from non-compiling source. May contain errors.
   import { Vpc } from "@aws-cdk/aws-ec2";
   import { App, Stack } from "@aws-cdk/core";
   import { GitlabRunnerAutoscaling } from "@pepperize/cdk-autoscaling-gitlab-runner";
   
   const app = new App();
   const stack = new Stack(app, "GitLabRunnerStack");
   const vpc = Vpc.fromLookup(app, "ExistingVpc", {
     vpcId: "<your vpc id>",
   });
   new GitlabRunnerAutoscaling(stack, "GitlabRunner", {
     gitlabToken: "<your gitlab runner auth token>",
     network: {
       vpc,
     },
   });
   

7. Create service linked role

   (If requesting spot instances, default: true)

   aws iam create-service-linked-role --aws-service-name spot.amazonaws.com
   

8. Configure the AWS CLI

   • AWSume
   • Configuring the AWS CLI
   • AWS Single Sign-On

9. Deploy the GitLab Runner

   npm run deploy
   

Example

Custom cache bucket

By default an AWS S3 is created as GitLab Runner's distributed cache. It's encrypted with a KMS managed key and public access is blocked. A custom S3 Bucket can be configured.

# Example automatically generated from non-compiling source. May contain errors.
const cache = new Bucket(this, "Cache", {
  // Your custom bucket
});

new GitlabRunnerAutoscaling(this, "Runner", {
  gitlabToken: "<auth token>",
  cache: { bucket: cache },
});

Configure Docker Machine

By default, docker machine is configured to run privileged with CAP_SYS_ADMIN to support Docker-in-Docker using the OverlayFS driver and cross compiling/building with multiarch.

See runners.docker section in Advanced configuration

# Example automatically generated from non-compiling source. May contain errors.
import { GitlabRunnerAutoscaling } from "@pepperize/cdk-autoscaling-gitlab-runner";

new GitlabRunnerAutoscaling(this, "Runner", {
  gitlabToken: "<auth token>",
  runners: {
    environment: [], // Reset the OverlayFS driver for every project
    docker: {
      capAdd: [], // Remove the CAP_SYS_ADMIN
      privileged: false, // Run unprivileged
    },
    machine: {
      idleCount: 2, // Number of idle machine
      idleTime: 3000, // Waiting time in idle state
      maxBuilds: 1, // Max builds before instance is removed
    },
  },
});

Bigger instance type

By default, t3.nano is used for the manager/coordinator and t3.micro instances will be spawned. For bigger projects, for example with webpack, this won't be enough memory.

# Example automatically generated from non-compiling source. May contain errors.
new GitlabRunnerAutoscaling(this, "Runner", {
  gitlabToken: "<auth token>",
  manager: {
    instanceType: InstanceType.of(InstanceClass.T3, InstanceSize.NANO),
  },
  runners: {
    instanceType: InstanceType.of(InstanceClass.T3, InstanceSize.LARGE),
  },
});

Different machine image

By default, the latest Amazon 2 Linux will be used for the manager/coordinator. The manager/coordinator instance's cloud init scripts requires yum is installed, any RHEL flavor should work. The requested runner instances by default using Ubuntu 20.04, any OS implemented by the Docker Machine provisioner should work.

# Example automatically generated from non-compiling source. May contain errors.
new GitlabRunnerAutoscaling(this, "Runner", {
  gitlabToken: "<auth token>",
  manager: {
    machineImage: MachineImage.genericLinux(managerAmiMap),
  },
  runners: {
    machineImage: MachineImage.genericLinux(runnerAmiMap),
  },
});

Spot instances

By default, EC2 Spot Instances are requested.

# Example automatically generated from non-compiling source. May contain errors.
new GitlabRunnerAutoscaling(this, "Runner", {
  gitlabToken: "<auth token>",
  runners: {
    machine: {
      machineOptions: {
        requestSpotInstance: false,
        spotPrice: 0.5,
      },
    },
  },
});

Custom runner's role

To deploy from within your GitLab Runner Instances, you may pass a Role with the IAM Policies attached.

# Example automatically generated from non-compiling source. May contain errors.
const role = new Role(this, "RunnersRole", {
  assumedBy: new ServicePrincipal("ec2.amazonaws.com", {}),
  inlinePolicies: {},
});

new GitlabRunnerAutoscaling(this, "Runner", {
  gitlabToken: "<auth token>",
  runners: {
    role: role,
  },
});

Vpc

If no existing Vpc is passed, a VPC that spans a whole region on will be created. This can become costly, because AWS CDK configured also the routing for the private subnets and creates NAT Gateways (one per AZ).

# Example automatically generated from non-compiling source. May contain errors.
const vpc = new Vpc(this, "Vpc", {
  // Your custom vpc
});

new GitlabRunnerAutoscaling(this, "Runner", {
  gitlabToken: "<auth token>",
  network: { vpc: vpc },
});

Zero config

Deploys the Autoscaling GitLab Runner on AWS EC2 with the default settings mentioned above.

Happy with the presets?

# Example automatically generated from non-compiling source. May contain errors.
new GitlabRunnerAutoscaling(this, "Runner", {
  gitlabToken: "<auth token>",
});

Projen

This project uses projen to maintain project configuration through code. Thus, the synthesized files with projen should never be manually edited (in fact, projen enforces that).

To modify the project setup, you should interact with rich strongly-typed class AwsCdkTypeScriptApp and execute npx projen to update project configuration files.

In simple words, developers can only modify .projenrc.js file for configuration/maintenance and files under /src directory for development.

See also Create and Publish CDK Constructs Using projen and jsii.