Terraform module for scalable self hosted GitHub action runners

This Terraform module creates the required infrastructure needed to host GitHub Actions self-hosted, auto-scaling runners on AWS spot instances. It provides the required logic to handle the life cycle for scaling up and down using a set of AWS Lambda functions. Runners are scaled down to zero to avoid costs when no workflows are active.

📢 v2 support via a Terraform submodule an option to create multiple runners at once. The webhook will deliver based on matching rules the events to a dedicated queue for the runners. Next per queue a scaling lambda will ensure the specific runner is created. For more details checkout the examples.

📢 v1 is available on a dedicated branch. The default branch main is related to v2, for fixes or backports you can submit a PR to the branch v1. For feature PR's we will ask you to at least submit a PR to main

📢 The main branch is the new default branch, we will not merge PR's back to develop. Please update and rebase your PR to main for v2, or to the branch v1 for v1.

📢 HELP WANTED: We are running the AWS self-hosted GitHub runners OS project in Philips Labs for over two years! And we are incredibly happy with all the feedback and contribution of the open-source community. In the next months we will speak at some conferences to share the solution and story of running this open-source project. Via this questionaire we would like to gather feedback from the community to use in our talks.

Motivation
Overview
- Major configuration options.
- AWS SSM Parameters
Usages
Examples
Sub modules
Debugging
Security Consideration
Requirements
Providers
Modules
Resources
Inputs
Outputs
Contribution
Philips Forest

Motivation

GitHub Actions self-hosted runners provide a flexible option to run CI workloads on the infrastructure of your choice. Currently, no option is provided to automate the creation and scaling of action runners. This module creates the AWS infrastructure to host action runners on spot instances. It provides lambda modules to orchestrate the life cycle of the action runners.

Lambda is chosen as the runtime for two major reasons. First, it allows the creation of small components with minimal access to AWS and GitHub. Secondly, it provides a scalable setup with minimal costs that works on repo level and scales to organization level. The lambdas will create Linux based EC2 instances with Docker to serve CI workloads that can run on Linux and/or Docker. The main goal is to support Docker-based workloads.

A logical question would be, why not Kubernetes? In the current approach, we stay close to how the GitHub action runners are available today. The approach is to install the runner on a host where the required software is available. With this setup, we stay quite close to the current GitHub approach. Another logical choice would be AWS Auto Scaling groups. However, this choice would typically require much more permissions on instance level to GitHub. And besides that, scaling up and down is not trivial.

Overview

The moment a GitHub action workflow requiring a self-hosted runner is triggered, GitHub will try to find a runner which can execute the workload. This module reacts to GitHub's workflow_job event for the triggered workflow and creates a new runner if necessary.

For receiving the workflow_job event by the webhook (lambda), a webhook needs to be created in GitHub. The check_run option is dropped from version 2.x. The following options to sent the event are supported.

Create a GitHup app, define a webhook and subscribe the app to the workflow_job event.
Create a webhook on enterprise, org or repo level, define a webhook and subscribe the app to the workflow_job event.

In AWS a API gateway endpoint is created that is able to receive the GitHub webhook events via HTTP post. The gateway triggers the webhook lambda which will verify the signature of the event. This check guarantees the event is sent by the GitHub App. The lambda only handles workflow_job events with status queued and matching the runner labels. The accepted events are posted on a SQS queue. Messages on this queue will be delayed for a configurable amount of seconds (default 30 seconds) to give the available runners time to pick up this build.

The "scale up runner" lambda listens to the SQS queue and picks up events. The lambda runs various checks to decide whether a new EC2 spot instance needs to be created. For example, the instance is not created if the build is already started by an existing runner, or the maximum number of runners is reached.

The Lambda first requests a registration token from GitHub, which is needed later by the runner to register itself. This avoids that the EC2 instance, which later in the process will install the agent, needs administration permissions to register the runner. Next, the EC2 spot instance is created via the launch template. The launch template defines the specifications of the required instance and contains a user_data script. This script will install the required software and configure it. The registration token for the action runner is stored in the parameter store (SSM), from which the user data script will fetch it and delete it once it has been retrieved. Once the user data script is finished, the action runner should be online, and the workflow will start in seconds.

Scaling down the runners is at the moment brute-forced, every configurable amount of minutes a lambda will check every runner (instance) if it is busy. In case the runner is not busy it will be removed from GitHub and the instance terminated in AWS. At the moment there seems no other option to scale down more smoothly.

Downloading the GitHub Action Runner distribution can be occasionally slow (more than 10 minutes). Therefore a lambda is introduced that synchronizes the action runner binary from GitHub to an S3 bucket. The EC2 instance will fetch the distribution from the S3 bucket instead of the internet.

Secrets and private keys are stored in SSM Parameter Store. These values are encrypted using the default KMS key for SSM or passing in a custom KMS key.

Permission are managed on several places. Below the most important ones. For details check the Terraform sources.

The GitHub App requires access to actions and publish workflow_job events to the AWS webhook (API gateway).
The scale up lambda should have access to EC2 for creating and tagging instances.
The scale down lambda should have access to EC2 to terminate instances.

Besides these permissions, the lambdas also need permission to CloudWatch (for logging and scheduling), SSM and S3. For more details about the required permissions see the documentation of the IAM module which uses permission boundaries.

Major configuration options.

To be able to support a number of use-cases the module has quite a lot of configuration options. We try to choose reasonable defaults. The several examples also show for the main cases how to configure the runners.

Org vs Repo level. You can configure the module to connect the runners in GitHub on an org level and share the runners in your org. Or set the runners on repo level and the module will install the runner to the repo. There can be multiple repos but runners are not shared between repos.
Multi-Runner module. This modules allows to create multiple runner configurations with a single webhook and single GitHub App to simply deployment of different types of runners. Refer to the ReadMe for more information to understand the functionality.
Workflow job event. You can configure the webhook in GitHub to send workflow job events to the webhook. Workflow job events are introduced by GitHub in September 2021 and are designed to support scalable runners. We advise when possible using the workflow job event.
Linux vs Windows. you can configure the OS types linux and win. Linux will be used by default.
Re-use vs Ephemeral. By default runners are re-used for till detected idle. Once idle they will be removed from the pool. To improve security we are introducing ephemeral runners. Those runners are only used for one job. Ephemeral runners are only working in combination with the workflow job event. We also suggest using a pre-build AMI to improve the start time of jobs.
GitHub Cloud vs GitHub Enterprise Server (GHES). The runner support GitHub Cloud as well GitHub Enterprise Server. For GHES we rely on our community to test and support. We have no possibility to test ourselves on GHES.
Spot vs on-demand. The runners use either the EC2 spot or on-demand life cycle. Runners will be created via the AWS CreateFleet API. The module (scale up lambda) will request via the CreateFleet API to create instances in one of the subnets and of the specified instance types.
ARM64 support via Graviton/Graviton2 instance-types. When using the default example or top-level module, specifying instance_types that match a Graviton/Graviton 2 (ARM64) architecture (e.g. a1, t4g or any 6th-gen g or gd type), you must also specify runner_architecture = "arm64" and the sub-modules will be automatically configured to provision with ARM64 AMIs and leverage GitHub's ARM64 action runner. See below for more details.

AWS SSM Parameters

The module uses the AWS System Manager Parameter store to store configuration for the runners, registration tokens and secrets for the Lambda's. Via the variable ssm_paths paths for the parameters can be configured. The location of the configuration parameters is retrieved buy the runners via the instance tag ghr:ssm_config_path. The following default paths will be used.

Path	Description
`ssm_paths.root`/`var.prefix`?/app/	App secrets used by Lambda's
`ssm_paths.root`/`var.prefix`?/runners/config/`<name>`	Configuration parameters used by runner start script
`ssm_paths.root`/`var.prefix`?/runners/tokens/`<ec2-instance-id>`	Registration tokens for the runners generate by the scale-up lambda, consumed by the start script on the runner.

Available configuration parameters:

Parameter name	Description
`agent_mode`	Indicates if the agent is running in ephemeral mode or not.
`enable_cloudwatch`	Configuration for the cloudwatch agent to stream logging.
`run_as`	The user used for running the GitHub action runner agent.
`token_path`	The path where tokens are stored.

Usages

Examples are provided in the example directory. Please ensure you have installed the following tools.

Terraform, or tfenv.
Bash shell or compatible
Docker (optional, to build lambdas without node).
AWS cli (optional)
Node and yarn (for lambda development).

The module supports two main scenarios for creating runners. On repository level a runner will be dedicated to only one repository, no other repository can use the runner. On organization level you can use the runner(s) for all the repositories within the organization. See GitHub self-hosted runner instructions for more information. Before starting the deployment you have to choose one option.

The setup consists of running Terraform to create all AWS resources and manually configuring the GitHub App. The Terraform module requires configuration from the GitHub App and the GitHub app requires output from Terraform. Therefore you first create the GitHub App and configure the basics, then run Terraform, and afterwards finalize the configuration of the GitHub App.

Setup GitHub App (part 1)

Go to GitHub and create a new app. Beware you can create apps for your organization or for a user. For now we support only organization level apps.

Create app in Github
Choose a name
Choose a website (mandatory, not required for the module).
Disable the webhook for now (we will configure this later or create an alternative webhook).
Permissions for all runners:
- Repository:
  - Actions: Read-only (check for queued jobs)
  - Checks: Read-only (receive events for new builds)
  - Metadata: Read-only (default/required)
Permissions for repo level runners only:
- Repository:
  - Administration: Read & write (to register runner)
Permissions for organization level runners only:
- Organization
  - Self-hosted runners: Read & write (to register runner)
Save the new app.
On the General page, make a note of the "App ID" and "Client ID" parameters.
Generate a new private key and save the app.private-key.pem file.

Setup terraform module

Download lambdas

To apply the terraform module, the compiled lambdas (.zip files) need to be available either locally or in an S3 bucket. They can be either downloaded from the GitHub release page or build locally.

To read the files from S3, set the lambda_s3_bucket variable and the specific object key for each lambda.

The lambdas can be downloaded manually from the release page or using the download-lambda terraform module (requires curl to be installed on your machine). In the download-lambda directory, run terraform init && terraform apply. The lambdas will be saved to the same directory.

For local development you can build all the lambdas at once using .ci/build.sh or individually using yarn dist.

Service-linked role

To create spot instances the AWSServiceRoleForEC2Spot role needs to be added to your account. You can do that manually by following the AWS docs. To use terraform for creating the role, either add the following resource or let the module manage the service linked role by setting create_service_linked_role_spot to true. Be aware this is an account global role, so maybe you don't want to manage it via a specific deployment.

resource "aws_iam_service_linked_role" "spot" {
  aws_service_name = "spot.amazonaws.com"
}

Terraform module

Next create a second terraform workspace and initiate the module, or adapt one of the examples.

Note that github_app.key_base64 needs to be a base64-encoded string of the .pem file i.e. the output of base64 app.private-key.pem. The decoded string can either be a multiline value or a single line value with new lines represented with literal \n characters.

module "github-runner" {
  source  = "philips-labs/github-runner/aws"
  version = "REPLACE_WITH_VERSION"

  aws_region = "eu-west-1"
  vpc_id     = "vpc-123"
  subnet_ids = ["subnet-123", "subnet-456"]

  prefix = "gh-ci"

  github_app = {
    key_base64     = "base64string"
    id             = "1"
    webhook_secret = "webhook_secret"
  }

  webhook_lambda_zip                = "lambdas-download/webhook.zip"
  runner_binaries_syncer_lambda_zip = "lambdas-download/runner-binaries-syncer.zip"
  runners_lambda_zip                = "lambdas-download/runners.zip"
  enable_organization_runners = true
}

Run terraform by using the following commands

terraform init
terraform apply

The terraform output displays the API gateway url (endpoint) and secret, which you need in the next step.

The lambda for syncing the GitHub distribution to S3 is triggered via CloudWatch (by default once per hour). After deployment the function is triggered via S3 to ensure the distribution is cached.

Setup the webhook / GitHub App (part 2)

At this point you have 2 options. Either create a separate webhook (enterprise, org, or repo), or create webhook in the App.

Option 1: Webhook

Create a new webhook on repo level for repo level for repo level runner, or org (or enterprise level) for an org level runner.
Provide the webhook url, should be part of the output of terraform.
Provide the webhook secret (terraform output -raw <NAME_OUTPUT_VAR>).
Ensure content type as application/json.
In the "Permissions & Events" section and then "Subscribe to Events" subsection, check either "Workflow Job" or "Check Run" (choose only 1 option!!!).
In the "Install App" section, install the App in your organization, either in all or in selected repositories.

Option 2: App

Go back to the GitHub App and update the following settings.

Enable the webhook.
Provide the webhook url, should be part of the output of terraform.
Provide the webhook secret (terraform output -raw <NAME_OUTPUT_VAR>).
In the "Permissions & Events" section and then "Subscribe to Events" subsection, check either "Workflow Job" or "Check Run" (choose only 1 option!!!).

Install app

Finally you need to ensure the app is installed to all or selected repositories.

Go back to the GitHub App and update the following settings.

In the "Install App" section, install the App in your organization, either in all or in selected repositories.

Encryption

The module support 2 scenarios to manage environment secrets and private key of the Lambda functions.

Encrypted via a module managed KMS key (default)

This is the default, no additional configuration is required.

Encrypted via a provided KMS key

You have to create and configure you KMS key. The module will use the context with key: Environment and value var.environment as encryption context.

resource "aws_kms_key" "github" {
  is_enabled = true
}

module "runners" {

  ...
  kms_key_arn = aws_kms_key.github.arn
  ...

Pool

The module basically supports two options for keeping a pool of runners. One is via a pool which only supports org-level runners, the second option is keeping runners idle.

The pool is introduced in combination with the ephemeral runners and is primary meant to ensure if any event is unexpected dropped, and no runner was created the pool can pick up the job. The pool is maintained by a lambda. Each time the lambda is triggered a check is preformed if the number of idler runners managed by the module are meeting the expected pool size. If not, the pool will be adjusted. Keep in mind that the scale down function is still active and will terminate instances that are detected as idle.

pool_runner_owner = "my-org"                  # Org to which the runners are added
pool_config = [{
  size                = 20                    # size of the pool
  schedule_expression = "cron(* * * * ? *)"   # cron expression to trigger the adjustment of the pool
}]

The pool is NOT enabled by default and can be enabled by setting at least one object of the pool config list. The ephemeral example contains configuration options (commented out).

Idle runners

The module will scale down to zero runners by default. By specifying a idle_config config, idle runners can be kept active. The scale down lambda checks if any of the cron expressions matches the current time with a margin of 5 seconds. When there is a match, the number of runners specified in the idle config will be kept active. In case multiple cron expressions matches, only the first one is taken into account. Below is an idle configuration for keeping runners active from 9:00am to 5:59pm on working days. The cron expression generator by Cronhub is a great resource to set up your idle config.

idle_config = [{
   cron      = "* * 9-17 * * 1-5"
   timeZone  = "Europe/Amsterdam"
   idleCount = 2
}]

Note: When using Windows runners it's recommended to keep a few runners warmed up due to the minutes-long cold start time.

Supported config

Cron expressions are parsed by cron-parser. The supported syntax.

*    *    *    *    *    *
┬    ┬    ┬    ┬    ┬    ┬
│    │    │    │    │    |
│    │    │    │    │    └ day of week (0 - 7) (0 or 7 is Sun)
│    │    │    │    └───── month (1 - 12)
│    │    │    └────────── day of month (1 - 31)
│    │    └─────────────── hour (0 - 23)
│    └──────────────────── minute (0 - 59)
└───────────────────────── second (0 - 59, optional)

For time zones please check TZ database name column for the supported values.

Ephemeral runners

You can configure runners to be ephemeral, runners will be used only for one job. The feature should be used in conjunction with listening for the workflow job event. Please consider the following:

The scale down lambda is still active, and should only remove orphan instances. But there is no strict check in place. So ensure you configure the minimum_running_time_in_minutes to a value that is high enough to got your runner booted and connected to avoid it got terminated before executing a job.
The messages sent from the webhook lambda to scale-up lambda are by default delayed delayed by SQS, to give available runners to option to start the job before the decision is made to scale more runners. For ephemeral runners there is no need to wait. Set delay_webhook_event to 0.
All events on the queue will lead to a new runner crated by the lambda. By setting enable_job_queued_check to true you can enforce only create a runner if the event has a correlated queued job. Setting this can avoid creating useless runners, for example whn jobs got cancelled before a runner is created. We suggest to use this in combination with a pool.
To ensure runners are created in the same order GitHub sends the events we use by default a FIFO queue, this is mainly relevant for repo level runners. For ephemeral runners you can set enable_fifo_build_queue to false.
Error related to scaling should be retried via SQS. You can configure job_queue_retention_in_seconds redrive_build_queue to tune the behavior. We have no mechanism to avoid events will never processed, which means potential no runner could be created and the job in GitHub can time out in 6 hours.

The example for ephemeral runners is based on the default example. Have look on the diff to see the major configuration differences.

Prebuilt Images

This module also allows you to run agents from a prebuilt AMI to gain faster startup times. You can find more information in the image README.md

Experimental - Optional queue to publish GitHub workflow job events

This queue is an experimental feature to allow you to receive a copy of the wokflow_jobs events sent by the GItHub App. For example to calculate matrix or monitor the system.

To enable the feature set enable_workflow_job_events_queue = true. Be-aware the feature in experimental!

Messages received on the queue are using the same format as published by GitHub wrapped in a property workflowJobEvent.

export interface GithubWorkflowEvent {
  workflowJobEvent: WorkflowJobEvent;
}

This extendible format allows to add more fields to be added if needed. You can configure the queue by setting properties to workflow_job_events_queue_config

NOTE: By default, a runner AMI update requires a re-apply of this terraform config (the runner AMI ID is looked up by a terraform data source). To avoid this, you can use ami_id_ssm_parameter_name to have the scale-up lambda dynamically lookup the runner AMI ID from an SSM parameter at instance launch time. Said SSM parameter is managed outside of this module (e.g. by a runner AMI build workflow).

Examples

Examples are located in the examples directory. The following examples are provided:

Default: The default example of the module
ARM64: Example usage with ARM64 architecture
Ephemeral: Example usages of ephemeral runners based on the default example.
Multi Runner : Example usage of creating a multi runner which creates multiple runners/ configurations with a single deployment
Permissions boundary: Example usages of permissions boundaries.
Prebuilt Images: Example usages of deploying runners with a custom prebuilt image.
Ubuntu: Example usage of creating a runner using Ubuntu AMIs.
Windows: Example usage of creating a runner using Windows as the OS.

Sub modules

The module contains several submodules, you can use the module via the main module or assemble your own setup by initializing the submodules yourself.

The following submodules are the core of the module and are mandatory:

runner-binaries-syncer - Syncs the action runner distribution.
runners - Scales the action runners up and down
webhook - Handles GitHub webhooks
_multi-runner - Creates multiple runner configurations in a single deployment

The following sub modules are optional and are provided as example or utility:

download-lambda - Utility module to download lambda artifacts from GitHub Release
setup-iam-permissions - Example module to setup permission boundaries

ARM64 configuration for submodules. When using the top level module configure runner_architecture = "arm64" and ensure the list of instance_types matches. When not using the top-level, ensure these properties are set on the submodules.

Debugging

In case the setup does not work as intended follow the trace of events:

In the GitHub App configuration, the Advanced page displays all webhook events that were sent.
In AWS CloudWatch, every lambda has a log group. Look at the logs of the webhook and scale-up lambdas.
In AWS SQS you can see messages available or in flight.
Once an EC2 instance is running, you can connect to it in the EC2 user interface using Session Manager (use enable_ssm_on_runners = true). Check the user data script using cat /var/log/user-data.log. By default several log files of the instances are streamed to AWS CloudWatch, look for a log group named <environment>/runners. In the log group you should see at least the log streams for the user data installation and runner agent.
Registered instances should show up in the Settings - Actions page of the repository or organization (depending on the installation mode).

Security Consideration

This module creates resources in your AWS infrastructure, and EC2 instances for hosting the self-hosted runners on-demand. IAM permissions are set to a minimal level, and could be further limit by using permission boundaries. Instances permissions are limit to retrieve and delete the registration token, access the instance own tags, and terminate the instance itself.

The examples are using standard AMI's for different operation systems. Instances are not hardened, and sudo operation are not blocked. To provide an out of the box working expierence by default the module installs and configure the runner. However secrets are not hard coded, they finally end up in the memory of the instances. You can harden the instance by providing your own AMI and overwriting the cloud-init script.

We welcome any improvement to the standard module to make the default as secure as possible, in the end it remains your responsibility to keep your environment secure.

Requirements

Name	Version
terraform	>= 1.3.0
aws	~> 4.41
random	~> 3.0

Providers

Name	Version
aws	~> 4.41
random	~> 3.0

Modules

Name	Source	Version
runner_binaries	./modules/runner-binaries-syncer	n/a
runners	./modules/runners	n/a
ssm	./modules/ssm	n/a
webhook	./modules/webhook	n/a

Resources

Name	Type
aws_sqs_queue.queued_builds	resource
aws_sqs_queue.queued_builds_dlq	resource
aws_sqs_queue.webhook_events_workflow_job_queue	resource
aws_sqs_queue_policy.build_queue_dlq_policy	resource
aws_sqs_queue_policy.build_queue_policy	resource
aws_sqs_queue_policy.webhook_events_workflow_job_queue_policy	resource
random_string.random	resource
aws_iam_policy_document.deny_unsecure_transport	data source

Inputs

Name	Description	Type	Default	Required
ami_filter	List of maps used to create the AMI filter for the action runner AMI. By default amazon linux 2 is used.	`map(list(string))`	`null`	no
ami_id_ssm_parameter_name	Externally managed SSM parameter (of data type aws:ec2:image) that contains the AMI ID to launch runner instances from. Overrides ami_filter	`string`	`null`	no
ami_owners	The list of owners used to select the AMI of action runner instances.	`list(string)`	[ "amazon" ]	no
aws_partition	(optiona) partition in the arn namespace to use if not 'aws'	`string`	`"aws"`	no
aws_region	AWS region.	`string`	n/a	yes
block_device_mappings	The EC2 instance block device configuration. Takes the following keys: `device_name`, `delete_on_termination`, `volume_type`, `volume_size`, `encrypted`, `iops`, `throughput`, `kms_key_id`, `snapshot_id`.	list(object({ delete_on_termination = optional(bool, true) device_name = optional(string, "/dev/xvda") encrypted = optional(bool, true) iops = optional(number) kms_key_id = optional(string) snapshot_id = optional(string) throughput = optional(number) volume_size = number volume_type = optional(string, "gp3") }))	[ { "volume_size": 30 } ]	no
cloudwatch_config	(optional) Replaces the module default cloudwatch log config. See https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch-Agent-Configuration-File-Details.html for details.	`string`	`null`	no
create_service_linked_role_spot	(optional) create the serviced linked role for spot instances that is required by the scale-up lambda.	`bool`	`false`	no
delay_webhook_event	The number of seconds the event accepted by the webhook is invisible on the queue before the scale up lambda will receive the event.	`number`	`30`	no
disable_runner_autoupdate	Disable the auto update of the github runner agent. Be-aware there is a grace period of 30 days, see also the GitHub article	`bool`	`false`	no
enable_cloudwatch_agent	Enabling the cloudwatch agent on the ec2 runner instances, the runner contains default config. Configuration can be overridden via `cloudwatch_config`.	`bool`	`true`	no
enable_enable_fifo_build_queue	DEPCRECATED: Replaced by `enable_fifo_build_queue` / `fifo_build_queue`.	`string`	`null`	no
enable_ephemeral_runners	Enable ephemeral runners, runners will only be used once.	`bool`	`false`	no
enable_fifo_build_queue	Enable a FIFO queue to remain the order of events received by the webhook. Suggest to set to true for repo level runners.	`bool`	`false`	no
enable_job_queued_check	Only scale if the job event received by the scale up lambda is is in the state queued. By default enabled for non ephemeral runners and disabled for ephemeral. Set this variable to overwrite the default behavior.	`bool`	`null`	no
enable_managed_runner_security_group	Enabling the default managed security group creation. Unmanaged security groups can be specified via `runner_additional_security_group_ids`.	`bool`	`true`	no
enable_organization_runners	Register runners to organization, instead of repo level	`bool`	`false`	no
enable_runner_binaries_syncer	Option to disable the lambda to sync GitHub runner distribution, useful when using a pre-build AMI.	`bool`	`true`	no
enable_runner_detailed_monitoring	Should detailed monitoring be enabled for the runner. Set this to true if you want to use detailed monitoring. See https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/using-cloudwatch-new.html for details.	`bool`	`false`	no
enable_runner_workflow_job_labels_check_all	If set to true all labels in the workflow job must match the GitHub labels (os, architecture and `self-hosted`). When false if any label matches it will trigger the webhook.	`bool`	`true`	no
enable_ssm_on_runners	Enable to allow access the runner instances for debugging purposes via SSM. Note that this adds additional permissions to the runner instances.	`bool`	`false`	no
enable_user_data_debug_logging_runner	Option to enable debug logging for user-data, this logs all secrets as well.	`bool`	`false`	no
enable_userdata	Should the userdata script be enabled for the runner. Set this to false if you are using your own prebuilt AMI.	`bool`	`true`	no
enable_workflow_job_events_queue	Enabling this experimental feature will create a secondory sqs queue to wich a copy of the workflow_job event will be delivered.	`bool`	`false`	no
enabled_userdata	DEPCRECATED: Replaced by `enable_userdata`.	`string`	`null`	no
environment	DEPRECATED, no longer used. See `prefix`	`string`	`null`	no
fifo_build_queue	DEPCRECATED: Replaced by `enable_fifo_build_queue`.	`string`	`null`	no
ghes_ssl_verify	GitHub Enterprise SSL verification. Set to 'false' when custom certificate (chains) is used for GitHub Enterprise Server (insecure).	`bool`	`true`	no
ghes_url	GitHub Enterprise Server URL. Example: https://github.internal.co - DO NOT SET IF USING PUBLIC GITHUB	`string`	`null`	no
github_app	GitHub app parameters, see your github app. Ensure the key is the base64-encoded `.pem` file (the output of `base64 app.private-key.pem`, not the content of `private-key.pem`).	object({ key_base64 = string id = string webhook_secret = string })	n/a	yes
idle_config	List of time period that can be defined as cron expression to keep a minimum amount of runners active instead of scaling down to 0. By defining this list you can ensure that in time periods that match the cron expression within 5 seconds a runner is kept idle.	list(object({ cron = string timeZone = string idleCount = number }))	`[]`	no
instance_allocation_strategy	The allocation strategy for spot instances. AWS recommends to use `price-capacity-optimized` however the AWS default is `lowest-price`.	`string`	`"lowest-price"`	no
instance_max_spot_price	Max price price for spot intances per hour. This variable will be passed to the create fleet as max spot price for the fleet.	`string`	`null`	no
instance_profile_path	The path that will be added to the instance_profile, if not set the environment name will be used.	`string`	`null`	no
instance_target_capacity_type	Default lifecycle used for runner instances, can be either `spot` or `on-demand`.	`string`	`"spot"`	no
instance_types	List of instance types for the action runner. Defaults are based on runner_os (amzn2 for linux and Windows Server Core for win).	`list(string)`	[ "m5.large", "c5.large" ]	no
job_queue_retention_in_seconds	The number of seconds the job is held in the queue before it is purged	`number`	`86400`	no
key_name	Key pair name	`string`	`null`	no
kms_key_arn	Optional CMK Key ARN to be used for Parameter Store. This key must be in the current account.	`string`	`null`	no
lambda_architecture	AWS Lambda architecture. Lambda functions using Graviton processors ('arm64') tend to have better price/performance than 'x86_64' functions.	`string`	`"arm64"`	no
lambda_principals	(Optional) add extra principals to the role created for execution of the lambda, e.g. for local testing.	list(object({ type = string identifiers = list(string) }))	`[]`	no
lambda_runtime	AWS Lambda runtime.	`string`	`"nodejs18.x"`	no
lambda_s3_bucket	S3 bucket from which to specify lambda functions. This is an alternative to providing local files directly.	`string`	`null`	no
lambda_security_group_ids	List of security group IDs associated with the Lambda function.	`list(string)`	`[]`	no
lambda_subnet_ids	List of subnets in which the action runners will be launched, the subnets needs to be subnets in the `vpc_id`.	`list(string)`	`[]`	no
log_level	Logging level for lambda logging. Valid values are 'silly', 'trace', 'debug', 'info', 'warn', 'error', 'fatal'.	`string`	`"info"`	no
log_type	Logging format for lambda logging. Valid values are 'json', 'pretty', 'hidden'.	`string`	`"pretty"`	no
logging_kms_key_id	Specifies the kms key id to encrypt the logs with	`string`	`null`	no
logging_retention_in_days	Specifies the number of days you want to retain log events for the lambda log group. Possible values are: 0, 1, 3, 5, 7, 14, 30, 60, 90, 120, 150, 180, 365, 400, 545, 731, 1827, and 3653.	`number`	`180`	no
minimum_running_time_in_minutes	The time an ec2 action runner should be running at minimum before terminated if not busy.	`number`	`null`	no
pool_config	The configuration for updating the pool. The `pool_size` to adjust to by the events triggered by the `schedule_expression`. For example you can configure a cron expression for week days to adjust the pool to 10 and another expression for the weekend to adjust the pool to 1.	list(object({ schedule_expression = string size = number }))	`[]`	no
pool_lambda_reserved_concurrent_executions	Amount of reserved concurrent executions for the scale-up lambda function. A value of 0 disables lambda from being triggered and -1 removes any concurrency limitations.	`number`	`1`	no
pool_lambda_timeout	Time out for the pool lambda in seconds.	`number`	`60`	no
pool_runner_owner	The pool will deploy runners to the GitHub org ID, set this value to the org to which you want the runners deployed. Repo level is not supported.	`string`	`null`	no
prefix	The prefix used for naming resources	`string`	`"github-actions"`	no
queue_encryption	Configure how data on queues managed by the modules in ecrypted at REST. Options are encryped via SSE, non encrypted and via KMSS. By default encryptes via SSE is enabled. See for more details the Terraform `aws_sqs_queue` resource https://registry.terraform.io/providers/hashicorp/aws/latest/docs/resources/sqs_queue.	object({ kms_data_key_reuse_period_seconds = number kms_master_key_id = string sqs_managed_sse_enabled = bool })	{ "kms_data_key_reuse_period_seconds": null, "kms_master_key_id": null, "sqs_managed_sse_enabled": true }	no
redrive_build_queue	Set options to attach (optional) a dead letter queue to the build queue, the queue between the webhook and the scale up lambda. You have the following options. 1. Disable by setting `enabled` to false. 2. Enable by setting `enabled` to `true`, `maxReceiveCount` to a number of max retries.	object({ enabled = bool maxReceiveCount = number })	{ "enabled": false, "maxReceiveCount": null }	no
repository_white_list	List of repositories allowed to use the github app	`list(string)`	`[]`	no
role_path	The path that will be added to role path for created roles, if not set the environment name will be used.	`string`	`null`	no
role_permissions_boundary	Permissions boundary that will be added to the created roles.	`string`	`null`	no
runner_additional_security_group_ids	(optional) List of additional security groups IDs to apply to the runner	`list(string)`	`[]`	no
runner_allow_prerelease_binaries	(Deprecated, no longer used), allow the runners to update to prerelease binaries.	`bool`	`null`	no
runner_architecture	The platform architecture of the runner instance_type.	`string`	`"x64"`	no
runner_as_root	Run the action runner under the root user. Variable `runner_run_as` will be ignored.	`bool`	`false`	no
runner_binaries_s3_logging_bucket	Bucket for action runner distribution bucket access logging.	`string`	`null`	no
runner_binaries_s3_logging_bucket_prefix	Bucket prefix for action runner distribution bucket access logging.	`string`	`null`	no
runner_binaries_s3_sse_configuration	Map containing server-side encryption configuration for runner-binaries S3 bucket.	`any`	`{}`	no
runner_binaries_syncer_lambda_timeout	Time out of the binaries sync lambda in seconds.	`number`	`300`	no
runner_binaries_syncer_lambda_zip	File location of the binaries sync lambda zip file.	`string`	`null`	no
runner_boot_time_in_minutes	The minimum time for an EC2 runner to boot and register as a runner.	`number`	`5`	no
runner_ec2_tags	Map of tags that will be added to the launch template instance tag specifications.	`map(string)`	`{}`	no
runner_egress_rules	List of egress rules for the GitHub runner instances.	list(object({ cidr_blocks = list(string) ipv6_cidr_blocks = list(string) prefix_list_ids = list(string) from_port = number protocol = string security_groups = list(string) self = bool to_port = number description = string }))	[ { "cidr_blocks": [ "0.0.0.0/0" ], "description": null, "from_port": 0, "ipv6_cidr_blocks": [ "::/0" ], "prefix_list_ids": null, "protocol": "-1", "security_groups": null, "self": null, "to_port": 0 } ]	no
runner_enable_workflow_job_labels_check_all	DEPCRECATED: Replaced by `enable_runner_workflow_job_labels_check_all`.	`string`	`null`	no
runner_extra_labels	Extra (custom) labels for the runners (GitHub). Separate each label by a comma. Labels checks on the webhook can be enforced by setting `enable_workflow_job_labels_check`. GitHub read-only labels should not be provided.	`string`	`""`	no
runner_group_name	Name of the runner group.	`string`	`"Default"`	no
runner_iam_role_managed_policy_arns	Attach AWS or customer-managed IAM policies (by ARN) to the runner IAM role	`list(string)`	`[]`	no
runner_log_files	(optional) Replaces the module default cloudwatch log config. See https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch-Agent-Configuration-File-Details.html for details.	list(object({ log_group_name = string prefix_log_group = bool file_path = string log_stream_name = string }))	`null`	no
runner_metadata_options	Metadata options for the ec2 runner instances. By default, the module uses metadata tags for bootstrapping the runner, only disable `instance_metadata_tags` when using custom scripts for starting the runner.	`map(any)`	{ "http_endpoint": "enabled", "http_put_response_hop_limit": 1, "http_tokens": "optional", "instance_metadata_tags": "enabled" }	no
runner_os	The EC2 Operating System type to use for action runner instances (linux,windows).	`string`	`"linux"`	no
runner_run_as	Run the GitHub actions agent as user.	`string`	`"ec2-user"`	no
runners_lambda_s3_key	S3 key for runners lambda function. Required if using S3 bucket to specify lambdas.	`string`	`null`	no
runners_lambda_s3_object_version	S3 object version for runners lambda function. Useful if S3 versioning is enabled on source bucket.	`string`	`null`	no
runners_lambda_zip	File location of the lambda zip file for scaling runners.	`string`	`null`	no
runners_maximum_count	The maximum number of runners that will be created.	`number`	`3`	no
runners_scale_down_lambda_timeout	Time out for the scale down lambda in seconds.	`number`	`60`	no
runners_scale_up_lambda_timeout	Time out for the scale up lambda in seconds.	`number`	`30`	no
scale_down_schedule_expression	Scheduler expression to check every x for scale down.	`string`	`"cron(/5 * * ? *)"`	no
scale_up_reserved_concurrent_executions	Amount of reserved concurrent executions for the scale-up lambda function. A value of 0 disables lambda from being triggered and -1 removes any concurrency limitations.	`number`	`1`	no
ssm_paths	The root path used in SSM to store configuration and secreets.	object({ root = optional(string, "github-action-runners") app = optional(string, "app") runners = optional(string, "runners") use_prefix = optional(bool, true) })	`{}`	no
subnet_ids	List of subnets in which the action runners will be launched, the subnets needs to be subnets in the `vpc_id`.	`list(string)`	n/a	yes
syncer_lambda_s3_key	S3 key for syncer lambda function. Required if using S3 bucket to specify lambdas.	`string`	`null`	no
syncer_lambda_s3_object_version	S3 object version for syncer lambda function. Useful if S3 versioning is enabled on source bucket.	`string`	`null`	no
tags	Map of tags that will be added to created resources. By default resources will be tagged with name and environment.	`map(string)`	`{}`	no
userdata_post_install	Script to be ran after the GitHub Actions runner is installed on the EC2 instances	`string`	`""`	no
userdata_pre_install	Script to be ran before the GitHub Actions runner is installed on the EC2 instances	`string`	`""`	no
userdata_template	Alternative user-data template, replacing the default template. By providing your own user_data you have to take care of installing all required software, including the action runner. Variables userdata_pre/post_install are ignored.	`string`	`null`	no
vpc_id	The VPC for security groups of the action runners.	`string`	n/a	yes
webhook_lambda_apigateway_access_log_settings	n/a	object({ destination_arn = string format = string })	`null`	no
webhook_lambda_s3_key	S3 key for webhook lambda function. Required if using S3 bucket to specify lambdas.	`string`	`null`	no
webhook_lambda_s3_object_version	S3 object version for webhook lambda function. Useful if S3 versioning is enabled on source bucket.	`string`	`null`	no
webhook_lambda_timeout	Time out of the webhook lambda in seconds.	`number`	`10`	no
webhook_lambda_zip	File location of the webhook lambda zip file.	`string`	`null`	no
workflow_job_queue_configuration	Configuration options for workflow job queue which is only applicable if the flag enable_workflow_job_events_queue is set to true.	object({ delay_seconds = number visibility_timeout_seconds = number message_retention_seconds = number })	{ "delay_seconds": null, "message_retention_seconds": null, "visibility_timeout_seconds": null }	no

Outputs

Name	Description
binaries_syncer	n/a
queues	SQS queues.
runners	n/a
ssm_parameters	n/a
webhook	n/a

Contribution

We welcome contribution, please checkout the contribution guide. Be-aware we use pre commit hooks to update the docs.

Philips Forest

This module is part of the Philips Forest.

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                                                                 Infrastructure

Talk to the forestkeepers in the runners-channel on Slack.

Name		Name	Last commit message	Last commit date
Latest commit History 1,931 Commits
.ci		.ci
.github		.github
.vscode		.vscode
docs		docs
examples		examples
images		images
modules		modules
policies		policies
.editorconfig		.editorconfig
.gitignore		.gitignore
.pre-commit-config.yaml		.pre-commit-config.yaml
.tflint.hcl		.tflint.hcl
CHANGELOG.md		CHANGELOG.md
CONTRIBUTING.md		CONTRIBUTING.md
LICENSE.md		LICENSE.md
MAINTAINERS.md		MAINTAINERS.md
README.md		README.md
main.tf		main.tf
outputs.tf		outputs.tf
variables.deprecated.tf		variables.deprecated.tf
variables.tf		variables.tf
versions.tf		versions.tf

License

anjosluc/terraform-aws-github-runner

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Terraform module for scalable self hosted GitHub action runners

Motivation

Overview

Major configuration options.

AWS SSM Parameters

Usages

Setup GitHub App (part 1)

Setup terraform module

Download lambdas

Service-linked role

Terraform module

Setup the webhook / GitHub App (part 2)

Option 1: Webhook

Option 2: App

Install app

Encryption

Encrypted via a module managed KMS key (default)

Encrypted via a provided KMS key

Pool

Idle runners

Supported config

Ephemeral runners

Prebuilt Images

Experimental - Optional queue to publish GitHub workflow job events

Examples

Sub modules

Debugging

Security Consideration

Requirements

Providers

Modules

Resources

Inputs

Outputs

Contribution

Philips Forest

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