Install on Amazon Web Services

Prerequisites

The instructions assume you have terraform installed on your machine, or use some automation like Atlantis to run apply for you.

Minimum supported versions for Workflows terraform code:

• Terraform >= 1.4
• AWS Provider >= 4.58.0

(Optional) Grant permissions to deploy

If Aspect CSE is expected to deploy resources, then follow this section.

Create a role to hold our policies. This may be done in Terraform, or in the AWS console:

Navigate to IAM > Roles > Create role

1. Select "trusted entity"
   • Trusted entity type: AWS account
   • Another AWS account: 302232432727 (this is Aspect's AWS account number)
   • Require MFA: enable, as Aspect's engineers are required to use multi-factor auth
2. Name, review, and create
   • One choice for the name is aspect-workflows-comaintainers. This name must be known for Aspect engineers to be able to assume the role.

Permissions required for terraform apply

autoscaling:CreateAutoScalingGroup
autoscaling:DeleteAutoScalingGroup
autoscaling:DescribeAutoScalingGroups
autoscaling:DescribeScalingActivities
autoscaling:SetInstanceProtection
autoscaling:UpdateAutoScalingGroup
cloudformation:CreateStack
cloudformation:DeleteStack
cloudformation:DescribeStacks
cloudformation:GetTemplate
cloudwatch:DeleteAlarms
cloudwatch:DescribeAlarms
cloudwatch:ListTagsForResource
cloudwatch:PutMetricAlarm
ec2:AuthorizeSecurityGroupEgress
ec2:AuthorizeSecurityGroupIngress
ec2:CreateLaunchTemplate
ec2:CreateSecurityGroup
ec2:DeleteLaunchTemplate
ec2:DeleteSecurityGroup
ec2:DescribeImages
ec2:DescribeLaunchTemplates
ec2:DescribeLaunchTemplateVersions
ec2:DescribeNetworkAcls
ec2:DescribeNetworkInterfaces
ec2:DescribeRouteTables
ec2:DescribeSecurityGroups
ec2:DescribeSubnets
ec2:DescribeVpcAttribute
ec2:DescribeVpcClassicLink
ec2:DescribeVpcClassicLinkDnsSupport
ec2:DescribeVpcs
ec2:RevokeSecurityGroupEgress
elasticloadbalancing:CreateListener
elasticloadbalancing:CreateLoadBalancer
elasticloadbalancing:CreateTargetGroup
elasticloadbalancing:DeleteListener
elasticloadbalancing:DeleteLoadBalancer
elasticloadbalancing:DeleteTargetGroup
elasticloadbalancing:DescribeListeners
elasticloadbalancing:DescribeLoadBalancerAt
elasticloadbalancing:DescribeLoadBalancers
elasticloadbalancing:DescribeTags
elasticloadbalancing:DescribeTargetGroupAt
elasticloadbalancing:DescribeTargetGroups
elasticloadbalancing:DescribeTargetHealth
elasticloadbalancing:ModifyLoadBalancerAt
elasticloadbalancing:ModifyTargetGroupAt
events:DeleteRule
events:DescribeRule
events:ListTagsForResource
events:ListTargetsByRule
events:PutRule
events:PutTargets
events:RemoveTargets
iam:AddRoleToInstanceProfile
iam:AttachRolePolicy
iam:CreateInstanceProfile
iam:CreatePolicy
iam:CreateRole
iam:DeleteInstanceProfile
iam:DeletePolicy
iam:DeleteRole
iam:DetachRolePolicy
iam:GetInstanceProfile
iam:GetPolicy
iam:GetPolicyVersion
iam:GetRole
iam:ListAttachedRolePolicies
iam:ListInstanceProfilesForRole
iam:ListPolicyVersions
iam:ListRolePolicies
iam:RemoveRoleFromInstanceProfile
lambda:AddPermission
lambda:CreateFunction
lambda:DeleteFunction
lambda:GetFunction
lambda:GetFunctionCodeSigningConfig
lambda:GetPolicy
lambda:ListVersionsByFunction
lambda:RemovePermission
logs:CreateLogGroup
logs:DeleteLogGroup
logs:DescribeLogGroups
logs:ListTagsLogGroup
logs:PutRetentionPolicy
memorydb:CreateCluster
memorydb:CreateSubnetGroup
memorydb:DeleteCluster
memorydb:DeleteSubnetGroup
memorydb:DescribeClusters
memorydb:DescribeSubnetGroups
memorydb:ListTags
s3:CreateBucket
s3:DeleteBucket
s3:DeleteBucketPolicy
s3:DeleteObject
s3:GetAccelerateConfiguration
s3:GetBucketAcl
s3:GetBucketCors
s3:GetBucketLogging
s3:GetBucketPolicy
s3:GetBucketPublicAccessBlock
s3:GetBucketRequestPayment
s3:GetBucketTagging
s3:GetBucketVersioning
s3:GetBucketWebsite
s3:GetEncryptionConfiguration
s3:GetLifecycleConfiguration
s3:GetObject
s3:GetObjectAttributes
s3:GetObjectTagging
s3:GetObjectVersion
s3:GetObjectVersionAttributes
s3:GetReplicationConfiguration
s3:ListAllMyBuckets
s3:ListBucket
s3:ListObjects
s3:PutBucketLogging
s3:PutBucketPolicy
s3:PutBucketPublicAccessBlock
s3:PutEncryptionConfiguration
s3:PutLifecycleConfiguration
s3:PutObject
ssm:DeleteParameter
ssm:DescribeParameters
ssm:GetParameter
ssm:ListTagsForResource
ssm:PutParameter
sts:AssumeRole
sts:GetCallerIdentity

Choose an Amazon Machine Image (AMI)

Aspect Workflows CI runners are EC2 instances, not Kubernetes pods. Therefore, the base image uses an AMI. To help you get started with Workflows, Aspect provides a number of starter AMIs.

Aspect Workflows starter AMIs are currently built on the following Linux distributions,

• Amazon Linux 2 (al2)
• Amazon Linux 2023 (al2023)
• Debian 11 "bullseye" (debian-11)
• Debian 12 "bookworm" (debian-12)
• Ubuntu 20.04 "Focal Fossa" (ubuntu-2004)

for both amd64 (x86_64) and arm64 (aarch64) and come in the following variants,

• minimal (just the bare minimum Workflows deps for fully hermetic builds)
• gcc (minimal + gcc)
• docker (minimal + docker)
• kitchen-sink (minimal + gcc, docker and other misc tools)

These are currently available in us-east-1, us-east-2, us-west-1 and us-west-2. Please contact us if you would like us to publish starter AMIs to additional regions.

tip

To query the list of all Aspect Workflows starter images, run the following command:

aws ec2 describe-images --owners 213396452403 --filters "Name=name,Values=aspect-workflows-*" --query 'sort_by(Images, &Name)[].Name'

This bit of terraform can be used to locate an AMI at plan/apply-time:

data "aws_ami" "aspect_runner_ami" {
  most_recent = true
  owners = ["213396452403"] # Public Aspect Workflows images AWS account (workflows-images)
  filter {
    name   = "name"
    values = ["aspect-workflows-<al2|al2023|debian-11|debian-12|ubuntu-2004>-<minimal|gcc|docker|kitchen-sink>-<amd64|arm64>-*"]
  }
}

The packer scripts we use to build Aspect Workflows starter images are open source and can be found at https://github.com/aspect-build/workflows-images.

note

In a later setup stage, we'll discuss how to build a custom AMI if required to green up your build.

Add the terraform module

Our terraform module is currently delivered in an S3 bucket. You add it to your existing Terraform setup.

Here's an example:

main.tf

module "aspect_workflows" {
  # Replace 5.x.x with an actual version:
  source             = "https://aspect-artifacts.s3.us-east-2.amazonaws.com/5.x.x/workflows/terraform-aws-aspect-workflows.zip"

  # Replace my-region with the AWS region you're deploying to
  # (S3 buckets are global, but terraform uses an API that can't do cross-region reads)
  aspect_artifacts_bucket = "aspect-artifacts-[my-region]"
  
  # Ask us to generate a customer ID for your organization and input it here
  customer_id       = "MyCorp"
  
  vpc_id            = data.terraform_state.outputs.circleci_vpc.vpc_id
  vpc_subnets       = [data.terraform_state.outputs.circleci_vpc.private_subnets[0]]

  # Replace XXX with one of gha, cci, bk
  hosts = ["XXX"]

  # Define Bazel states we know how to warm up
  warming_sets = {
    default = {}
  }

  # Define any customizations for the remote cache here.
  remote_cache = {}

  resource_types = {
    "default" = {
      # One or more instance types can be specified via 'instance_types'.
      # Specifying multiple instance types allows Workflows to scale out when demand
      # for a particular instance is high, or can not be fulfilled.
      instance_types = ["i4i.xlarge", "i4i.2xlarge"]
      image_id       = data.aws_ami.aspect_worker_ami.id
    }
  }

  # Replace XXX with one of gha, cci, bk
  XXX_runner_groups = {
    default = {
      max_runners   = 10
      resource_type = "default" # Corresponds to a resource_types entry above
      warming       = true
      warming_set   = "default" # Corresponds to a warming_sets entry above
      ...
    }
    warming = {
      max_runners   = 1
      resource_type = "default" # Corresponds to a resource_types entry above
      policies = {
        # "default" key in warming_management_policies corresponds to a warming_sets entry above
        warming_manage : module.aspect_workflows.warming_management_policies["default"].arn
      }
      warming_set = "default" # Corresponds to a warming_sets entry above
      ...
    }
  }
}

(Optional) Apply custom security groups to runners

Some organizations have a policy that requires adding custom security groups to the runners that are managed by Aspect workflows. This can be achieved by setting the security_groups attribute on the runners or queue configuration object. This is a map from string -> AWS Security Group ID (the name is not currently used by Workflows).

runners = {
  default = {
    ...
    security_groups = {
      vpn_access : aws_security_group.vpc_access.id
    }
    ...
  }
}

Allowing Aspect read-only support access

The Workflows module takes an optional support.support_role_name configuration option that Workflows attaches policies to, which provide read-only access to key logs, metrics and configuration values. The policies are only created and attached if the role is given; Workflows does not create a role automatically to add these policies too.

Specifically, the policy defined in this document allows:

• Read / List on all /aw SSM parameter store keys
• Describe on all ASGs and their associated instances and the scaling activity
• Get on log streams and log events with the aw_ prefix
• SSM access to running instances and port forwarding for Grafana

For example:

resource "aws_iam_role" "support" {
  name = "AspectWorkflowsSupport"
  ...
}

module "workflows" {
 ...
 support = {
   support_role_name = aws_iam_role.support.name
 }
 ...
}

Allowing Aspect privileged support access

The Workflows module takes an optional support.operator_role_name configuration option that Workflows attaches policies to, that provide privileged access to key resources. This role is a super-set of the above read-only support access role. The policies are only created and attached if the role is given; Workflows does not create a role automatically to add these policies to.

Specifically, the policy defined in this document allows:

• Manage Aspect build runner EC2 hosts, specifically by rebooting, stopping, and terminating.
• Delete S3 objects, only in specific Aspect-managed buckets.
• Manage the Redis cache, including updating/deleting the cluster, and creating snapshots.

For example, it could be extended via:

resource "aws_iam_role" "operator" {
  name = "AspectWorkflowsOperator"
  ...
}

module "aspect_workflows" {
 ...
 support = {
   operator_role_name = aws_iam_role.operator.name
 }
 ...
}

In addition, Workflows can also enable SSM access to key resources which is available via the operator role only. To enable SSM access, set the following property in the support configuration. By default, SSM access is turned off.

module "aspect_workflows" {
 ...
 support = {
    enable_ssm_access = true
 }
 ...
}

Apply

Run terraform apply, or use whatever automation you already use for your Infrastructure-as-code such as Atlantis.

You'll get a resulting infrastructure like the following:

Next steps

Continue by choosing which CI platform you plan to interact with, and follow the corresponding installation steps.