AWS support#

If you intend to run your agents on AWS, the agent-aws-stack can help you deploy an auto-scaling fleet of agents on your AWS account.



The agent-aws-stack is an AWS CDK application written in JavaScript, which depends on a few things to work:

  • Node v18+ and NPM, for building and deploying the CDK application and managing its dependencies
  • Make, Python 3.9+, and Packer for AMI creation and provisioning
  • Properly-configured AWS credentials


In order to follow the steps below, please make sure that your AWS user has the required permissions.

1. Download the CDK application and installing dependencies#

curl -sL -o agent-aws-stack.tar.gz
tar -xf agent-aws-stack.tar.gz
cd agent-aws-stack-0.3.4
npm i

You can also fork and clone the repository.

2. Build the AMI#

We use packer to create an AMI with everything the agent needs in your AWS account.

Build a Linux AMI#

The Linux AMI is based on the Ubuntu 20.04 server image. To build it, run the following commands:

make packer.init

Build a Windows AMI#

The Windows AMI is based on the Microsoft Windows Server 2019 with Containers image, provided by AWS. To build it, run the following commands:

make packer.init
make PACKER_OS=windows

Build a MacOS AMI#

Make sure you have an available dedicated host first. After that, an AMD or an ARM AMI can be built. To build it, run the following commands:

make packer.init

# To build an AMD AMI (EC2 mac1 family)
make PACKER_OS=macos AMI_ARCH=x86_64 AMI_INSTANCE_TYPE=mac1.metal

# To build an ARM AMI (EC2 mac2 family)
make PACKER_OS=macos AMI_ARCH=arm64 AMI_INSTANCE_TYPE=mac2.metal

Build the AMIs in a specific AWS region#

By default, the AMI is built in the us-east AWS region. If you want to build the AMI in a different AWS region, you can use the AWS_REGION variable:

make AWS_REGION=us-west-1

3. Create an encrypted SSM parameter for the agent type registration token#

When creating your agent type using the Semaphore UI, you get a registration token. This is a sensitive piece of information, so you should create an encrypted AWS SSM parameter with it.

You can use the default SSM aws/ssm KMS key or a custom KMS key of your choice to encrypt your registration token.

Use the default aws/ssm KMS key#

aws ssm put-parameter \
  --name <your-ssm-parameter-name> \
  --value "<your-agent-type-registration-token>" \
  --type SecureString

Use a customer managed KMS key#

When using a customer managed KMS key, make sure you have kms:Encrypt permissions for that key. If you want to create a new KMS key, you can use the create-key operation.

After that, create the encrypted SSM parameter using your KMS key with:

aws ssm put-parameter \
  --name <your-ssm-parameter-name> \
  --value "<your-agent-type-registration-token>" \
  --type SecureString \
  --key-id <your-kms-key-id>

4. Create the execution policy that will be used by Cloudformation#

When deploying the stack, you can instruct the AWS CDK to use only the permissions it needs to manage all the stack resources. To do that, create an AWS IAM policy with all the required permissions:

aws iam create-policy \
  --policy-name agent-aws-stack-cfn-execution-policy \
  --policy-document file://$(pwd)/execution-policy.json \
  --description "Policy used by Cloudformation to deploy the agent-aws-stack CDK application"

After creating the AWS IAM policy, save the ARN.

4. Create the stack configuration#

The stack accepts a number of parameters for configuration. These parameters can be specified either with a configuration file or using environment variables.

Create configuration for Linux agents#

Create a config.json file with the following:

  "SEMAPHORE_AGENT_STACK_NAME": "<your-stack-name>",
  "SEMAPHORE_AGENT_TOKEN_PARAMETER_NAME": "<your-ssm-parameter-name>",
  "SEMAPHORE_AGENT_TOKEN_KMS_KEY": "<your-ssm-parameter-name>",
  "SEMAPHORE_ENDPOINT": "<your-organization>"

Create configuration for Windows agents#

Create a config.json file with the following:

  "SEMAPHORE_AGENT_STACK_NAME": "<your-stack-name>",
  "SEMAPHORE_AGENT_TOKEN_PARAMETER_NAME": "<your-ssm-parameter-name>",
  "SEMAPHORE_AGENT_TOKEN_KMS_KEY": "<your-ssm-parameter-name>",
  "SEMAPHORE_ENDPOINT": "<your-organization>",
  "SEMAPHORE_AGENT_OS": "windows"

Create configuration for MacOS agents#

Create a config.json file with the following:

  "SEMAPHORE_AGENT_STACK_NAME": "<your-stack-name>",
  "SEMAPHORE_AGENT_TOKEN_PARAMETER_NAME": "<your-ssm-parameter-name>",
  "SEMAPHORE_AGENT_TOKEN_KMS_KEY": "<your-ssm-parameter-name>",
  "SEMAPHORE_ENDPOINT": "<your-organization>",
  "SEMAPHORE_AGENT_OS": "macos",
  "SEMAPHORE_AGENT_AZS": "us-east-1a,us-east-1b,us-east-1d",
  "SEMAPHORE_AGENT_LICENSE_CONFIGURATION_ARN": "arn:aws:license-manager:<region>:<accountId>:license-configuration:<your-license-configuration>"

Rotation of MacOS instances

MacOS EC2 instances run on top of AWS EC2 dedicated hosts. When an instance is terminated, a new instance might take a long time to start in its place, depending on how many dedicated hosts you have available, and the time it takes for MacOS to be launched into them.

See the AWS documentation for more details.

Automatic scaling MacOS instances

AWS EC2 MacOS dedicated hosts need to be allocated for at least 24 hours, so it's recommended to use a SEMAPHORE_AGENT_DISCONNECT_AFTER_IDLE_TIMEOUT of at least 24 hours for agents running in MacOS instances. Also due to that restriction, it's important to note that, if SEMAPHORE_AGENT_USE_DYNAMIC_SCALING is enabled and the stack scales up to meet a burst of new jobs, the new dedicated hosts created might end up being idle for a long time.

See the AWS documentation for more details.

Using environment variables#

Alternatively, you can also configure the stack using environment variables:

export SEMAPHORE_AGENT_TOKEN_PARAMETER_NAME=<your-ssm-parameter-name>
export SEMAPHORE_AGENT_TOKEN_KMS_KEY=<your-kms-key-id>
export SEMAPHORE_AGENT_STACK_NAME=<your-stack-name>
export SEMAPHORE_ENDPOINT=<your-organization>

Note: if your key was encrypted using the default aws/ssm KMS key, SEMAPHORE_AGENT_TOKEN_KMS_KEY does not need to be set.

5. Bootstrap the CDK application#

Using the ARN of the execution policy created in step 3, bootstrap the CDK application:

  npm run bootstrap -- aws://YOUR_AWS_ACCOUNT_ID/YOUR_AWS_REGION \
  --cloudformation-execution-policies <arn-of-the-executed-policy-created-previously>

If you are using environment variables to configure the stack, you can omit SEMAPHORE_AGENT_STACK_CONFIG:

npm run bootstrap -- aws://YOUR_AWS_ACCOUNT_ID/YOUR_AWS_REGION \
  --cloudformation-execution-policies <arn-of-the-executed-policy-created-previously>

Note: if you don't use --cloudformation-execution-policies, the AWS CDK will instruct AWS CloudFormation to deploy your stack using full administrator permissions from the AdministratorAccess policy.

6. Deploy the stack#

SEMAPHORE_AGENT_STACK_CONFIG=config.json npm run deploy

If you are using environment variables to configure the stack, you can omit SEMAPHORE_AGENT_STACK_CONFIG:

npm run deploy

In-place updates#

When changing the configuration of your stack, you can update it in-place. AWS CDK will use AWS Cloudformation changesets to apply the required changes. Before updating, you can check what will be different with the diff command:

npm run diff

To update, use:

npm run deploy

In-place updates might require an agent restart

A few configuration parameters are read by the agent instance during the startup process. If you change them, the running agents won't automatically reload it. Therefore, you will need to restart those instances. You can restart all the agents in your stack by disconnecting them via the Semaphore UI.

Agent type registration token rotation#

After resetting the agent type token via the Semaphore UI, currently-running agents will remain active. However, you will need to update the SSM parameter (SEMAPHORE_AGENT_TOKEN_PARAMETER_NAME) with the new token for new agents to function.

Deleting the stack#

To delete the stack, use:

SEMAPHORE_AGENT_STACK_CONFIG=config.json npm run destroy

If you are using environment variables to configure the stack, you can omit SEMAPHORE_AGENT_STACK_CONFIG:

npm run destroy

Note: make sure SEMAPHORE_AGENT_STACK_NAME indicates to the stack you want to destroy.

Deleting a MacOS stack

After destroying the stack, you'll need to manually delete the host resource group after the dedicated hosts attached to it leave the pending state. You'll also need to manually release the dedicated hosts associated with that resource group.



Parameter name Description
SEMAPHORE_ORGANIZATION or SEMAPHORE_ENDPOINT If SEMAPHORE_ENDPOINT is set, the agents will use that endpoint to register and sync for jobs. If SEMAPHORE_ENDPOINT is not set, but SEMAPHORE_ORGANIZATION is set, it is assumed that the organization is located at <organization>, and that will be the endpoint used.
SEMAPHORE_AGENT_STACK_NAME The name of the stack. This will end up being used as the Cloudformation stack name, and as a prefix to name all the resources of the stack. When deploying multiple stacks for multiple agent types, different stack names are required
SEMAPHORE_AGENT_TOKEN_PARAMETER_NAME The AWS SSM parameter name containing the Semaphore agent registration token


Parameter name Description
SEMAPHORE_AGENT_STACK_CONFIG Path to a JSON file containing the parameters to use. This is an alternative to using environment variables for setting the stack's configuration parameters.
SEMAPHORE_AGENT_INSTANCE_TYPE Instance type used for the agents. Default is t2.micro.
SEMAPHORE_AGENT_ASG_MIN_SIZE Minimum size for the auto-scaling group. Default is 0.
SEMAPHORE_AGENT_ASG_MAX_SIZE Maximum size for the auto-scaling group. Default is 1.
SEMAPHORE_AGENT_ASG_DESIRED Desired capacity for the auto-scaling group. Default is 1.
SEMAPHORE_AGENT_USE_DYNAMIC_SCALING Whether to use a lambda to dynamically scale the number of agents in the auto-scaling group based on the job demand. Default is true
SEMAPHORE_AGENT_SECURITY_GROUP_ID Security group id to use for agent instances. If not specified, a security group will be created with (1) an egress rule allowing all outbound traffic and (2) an ingress rule for SSH, if SEMAPHORE_AGENT_KEY_NAME is specified.
SEMAPHORE_AGENT_KEY_NAME Key name to access agents through SSH. If not specified, no SSH inbound access is allowed
SEMAPHORE_AGENT_DISCONNECT_AFTER_JOB If the agent should shutdown or not after completing a job. Default is true.
SEMAPHORE_AGENT_DISCONNECT_AFTER_IDLE_TIMEOUT Number of seconds of idleness after which the agent will shutdown. Note: setting this to 0 will disable the scaling down behavior for the stack, since the agents won't shutdown due to idleness. Default is 300.
SEMAPHORE_AGENT_CACHE_BUCKET_NAME Existing S3 bucket name to use for caching. If this is not set, caching won't work.
SEMAPHORE_AGENT_TOKEN_KMS_KEY KMS key id used to encrypt and decrypt SEMAPHORE_AGENT_TOKEN_PARAMETER_NAME. If nothing is given, the default alias/aws/ssm key is assumed.
SEMAPHORE_AGENT_VPC_ID The id of an existing VPC to use when launching agent instances. By default, this is blank, and the default VPC on your AWS account will be used.
SEMAPHORE_AGENT_SUBNETS Comma-separated list of existing VPC subnet ids where EC2 instances will run. This is required when using SEMAPHORE_AGENT_VPC_ID. If SEMAPHORE_AGENT_SUBNETS is set, but SEMAPHORE_AGENT_VPC_ID is blank, the subnets will be ignored and the default VPC will be used. Private and public subnets are possible, but isolated subnets cannot be used.
SEMAPHORE_AGENT_AMI The AMI used for all instances. If empty, the stack will use the default AMIs, looking them up by name. If the default AMI isn't sufficient, you can use your own AMIs, but they need to be based off of the stack's default AMI.
SEMAPHORE_AGENT_OS The OS type for agents. Possible values: ubuntu-focal and windows.
SEMAPHORE_AGENT_ARCH The arch type for agents. Possible values: x86_64 and arm64.
SEMAPHORE_AGENT_AZS A comma-separated list of availability zones to use for the auto scaling group.
SEMAPHORE_AGENT_MANAGED_POLICY_NAMES A comma-separated list of custom IAM policy names to attach to the instance profile role.
SEMAPHORE_AGENT_ASG_METRICS A comma-separated list of ASG metrics to collect. Available metrics can be found here.
SEMAPHORE_AGENT_VOLUME_NAME The EBS volume's device name to use for a custom volume. If this is not set, the EC2 instances will have an EBS volume based on the AMI's one.
SEMAPHORE_AGENT_VOLUME_TYPE The EBS volume's type, when using SEMAPHORE_AGENT_VOLUME_NAME. By default, this is gp2.
SEMAPHORE_AGENT_VOLUME_SIZE The EBS volume's size, in GB, when using SEMAPHORE_AGENT_VOLUME_NAME. By default, this is 64.
SEMAPHORE_AGENT_LICENSE_CONFIGURATION_ARN The license configuration ARN associated with the AMI used by the stack.
SEMAPHORE_AGENT_MAC_FAMILY The EC2 Mac instance family to use. Possible values: mac1 and mac2.
SEMAPHORE_AGENT_MAC_DEDICATED_HOSTS A comma-separated list of dedicated host IDs to include in the host resource group.
SEMAPHORE_AGENT_TAGS A comma-separated list of key-value pairs of tags to be added to all resources created for the stack. For example: Name:Something,Category:SomethingElse.
SEMAPHORE_AGENT_USE_PRE_SIGNED_URL Whether to use a pre-signed AWS STS GetCallerIdentity URL for agent registration. Note: the agent type is required to be properly configured to allow this. By default, this is false.



By default, the agents will run in your default AWS VPC. That means that your agents will have a public and a private IPv4 address assigned to them and will run on a public subnet, and traffic bound for the internet will be sent to an internet gateway.

However, since all the communication between agents and the Semaphore API happens unidirectionally (from the agent to Semaphore), the agent instances don't need to be publicly accessible via the Internet -- they only need outbound access. Therefore, you can also run your agents on a private subnet with no public IPv4 address assigned, and use NAT devices to send outbound traffic to the Internet.

Therefore, you don't need to rely on your default AWS VPC. You can create a custom VPC and subnets that fit your needs, and use the SEMAPHORE_AGENT_VPC_ID and SEMAPHORE_AGENT_SUBNETS parameters to configure the stack to use them.

Agent instance access#

There are two different ways to access your agent instances:

  • Using SSH. This approach will only work for instances with a publicly-assigned IP. By default, your instances will have a security group with no inbound access. You can change that behavior by creating an EC2 key and using the SEMAPHORE_AGENT_KEY_NAME parameter, which will add an SSH inbound rule to the default security group created and used in your instances. If you need to further restrict or open up access to your agent instances, you can also create a security group yourself and use the SEMAPHORE_AGENT_SECURITY_GROUP_ID to instruct the stack to use it.
  • Using AWS Systems Manager Session Manager. This kind of access doesn't rely on a publicly-accessible instance. Therefore, this is the only way to access instances running on private subnets. You can also use this approach to access publicly-available instances.

Scaling based on job demand#

By default, the stack will be created to support dynamic scaling of agents based on the job demand for your agent type.

The way the stack determines the need for an increase on the number of agents is by using a Lambda function to periodically poll the Semaphore API for the number of jobs for a given agent type. If an increase is needed, the Lambda function will update the auto-scaling group's desired capacity and new EC2 instances will be launched with new agents.

When the number of running agents outnumbers the number of jobs running, a few agents will be allowed to idle. When an agent remains idle for a given period of time, it will shutdown and decrease the capacity for the auto-scaling group. If all your agents are idle, they will all shutdown and the auto-scaling group will have a count of 0.

Finally, you can control this behavior via several configuration parameters:

  • By default, the idle period after which an agent shuts down is 5 minutes. But you can configure it to what works best for you by using the SEMAPHORE_AGENT_DISCONNECT_AFTER_IDLE_TIMEOUT parameter. Setting this parameter to 0 will stop agents from shutting down when they are idle, so your stack won't ever scale down.
  • Even if you have a lot of jobs, you probably do not want your stack to grow infinitely. You can use the SEMAPHORE_AGENT_ASG_MAX_SIZE parameter to configure a limit for your auto-scaling group. The lambda will respect your configuration and will not increase the number of agents above that limit.
  • You might want some agents to always be running even if no jobs are running. To address that, you can configure a minimum number of agents for your auto-scaling group with the SEMAPHORE_AGENT_ASG_MIN_SIZE parameter.
  • You might also not want a dynamically-sized auto-scaling group at all. You can disable this behavior completely and have a static pool of agents by using the SEMAPHORE_AGENT_USE_DYNAMIC_SCALING parameter.

Job isolation#

By default, agents will shutdown after executing a job. That agent will be replaced by a new one for each subsequent job, which guarantees a clean environment.

This comes with a cost, however, as rotating EC2 instances is not always a fast operation. If you want your instances not to shutdown after a job, you can use the SEMAPHORE_AGENT_DISCONNECT_AFTER_JOB parameter. A faster alternative to EC2 instance rotation is using Docker containers to run your jobs.

Multiple stacks#

Each stack that is deployed creates and starts agents for one agent type only. However, you might need to deploy multiple stacks for multiple agent types. To achieve that, you need to:

  • Set a different SEMAPHORE_AGENT_STACK_NAME parameter for each stack.
  • Create one encrypted SSM parameter for each agent type registration token, and set the SEMAPHORE_AGENT_TOKEN_PARAMETER_NAME appropriately for each one.

AWS permissions#

The following AWS IAM policy document describes all the permissions required:

  "Version": "2012-10-17",
  "Statement": [
      "Effect": "Allow",
      "Action": [
      "Resource": [
      "Effect": "Allow",
      "Action": [
      "Resource": "*"
      "Effect": "Allow",
      "Action": [
      "Resource": "*"
      "Effect": "Allow",
      "Action": [
      "Resource": "arn:aws:s3:::cdk*"
      "Effect": "Allow",
      "Action": [
      "Resource": "arn:aws:ecr:*:*:repository/cdk*"
      "Effect": "Allow",
      "Action": [
      "Resource": "*"
      "Effect": "Allow",
      "Action": [
      "Resource": "arn:aws:iam::*:role/cdk-*"

The policy above is needed due to the following operations:

  • Building the AWS EC2 AMI with Packer
  • Bootstrapping the AWS CDK application
  • Assuming the AWS CDK application's roles

The policy to deploy the CDK application, used by CloudFormation, is a different set of permissions, defined in the execution-policy.json file. That policy should be used when bootstrapping the CDK application with the --cloudformation-execution-policies parameter.


Agent logs, cloud init logs and systems logs are pushed from the EC2 instance to CloudWatch using the CloudWatch agent:

  • Agent logs are pushed to the semaphore/agent log group. In Linux instances, the agent logs are located at /tmp/agent_log. In Windows instances, the agent logs are located at C:\\semaphore-agent\\agent.log.
  • In Linux instances, the cloud init logs are pushed to the /semaphore/cloud-init and /semaphore/cloud-init/output log groups. In Windows instances, the cloud init logs are pushed to the /semaphore/EC2Launch/UserdataExecution log group.
  • System logs are pushed to the /semaphore/system log group

Invalid agent type registration token#

If an invalid agent type registration token is used, the agent won't be able to register with the Semaphore API. To troubleshoot this issue, follow these steps:

  1. Go to the CloudWatch console
  2. Select Log Groups
  3. Select the semaphore/agent log group
  4. Select the EC2 instance id for the instance running your agent
  5. Verify if the agent is running. If not, verify if you have messages of failed registration requests