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Create An AWS EC2 Instance

Overview

In the following guide, you are going to create a self-service action in Port that executes a GitLab pipeline to create an EC2 Instance in AWS using Terraform templates.

Prerequisites

  1. A Gitlab project to contain your action resources i.e. the gitlab pipeline file.

  2. An AWS Account or IAM user with permission to create access keys. Learn more

  3. An SSH Key Pair to connect with the provisioned instance. Learn more

  4. In your GitLab project, go to the Settings menu at the sidebar on the left, select CI/CD and create the following Variables:

    • PORT_CLIENT_ID - Port Client ID learn more
    • PORT_CLIENT_SECRET - Port Client Secret learn more
    • AWS_ACCESS_KEY_ID - An aws access key with the right iam permission to create an ec2 instance learn more
    • AWS_SECRET_ACCESS_KEY - An aws access key secret with permission to create an ec2 instance learn more
    • AWS_DEFAULT_REGION - The aws region where you would like to provision your ec2 instances.

GitLab Pipeline

  1. Create a gitlab project to host the terraform template files and the .gitlab-ci.yaml file.

  2. Create the terraform templates ( main.tf, variables.tf and outputs.tf ) at the root of your gitlab project.

main.tf
main.tf
# Configure the providers
terraform {
required_providers {
port = {
source = "port-labs/port-labs"
version = "~> 2.0.3"
}
aws = {
source = "hashicorp/aws"
}
}

required_version = ">= 1.1.0"
}


data "aws_ami" "ubuntu" {
most_recent = true

filter {
name = "name"
values = ["ubuntu/images/hvm-ssd/*22.04-amd64-server-*"]
}

filter {
name = "virtualization-type"
values = ["hvm"]
}

owners = ["099720109477"] # Canonical
}

locals {
ami_id = var.ec2_ami != "" ? var.ec2_ami : data.aws_ami.ubuntu.id
}

provider "aws" {
region = var.aws_region
}

resource "aws_instance" "app_server" {
ami = local.ami_id
instance_type = var.ec2_instance_type

tags = {
Name = var.ec2_name
}
}

resource "port_entity" "ec2_instance" {
count = length(aws_instance.app_server) > 0 ? 1 : 0
identifier = aws_instance.app_server.id
title = var.ec2_name
blueprint = "ec2Instance"
run_id = var.port_run_id
properties = {
string_props = {
"instance_state" = aws_instance.app_server.instance_state,
"instance_type" = aws_instance.app_server.instance_type,
"availabilityZone" = aws_instance.app_server.availability_zone,
"public_dns" = aws_instance.app_server.public_dns,
"public_ip" = aws_instance.app_server.public_ip,
"private_dns" = aws_instance.app_server.private_dns,
"private_ip" = aws_instance.app_server.private_ip,
"monitoring" = aws_instance.app_server.monitoring,
"key_name" = aws_instance.app_server.key_name,
"subnet_id" = aws_instance.app_server.subnet_id
}
array_props = {
"tags" = aws_instance.app_server.tags,
"security_group_ids" = aws_instance.app_server.vpc_security_group_ids,
}
}
relations = {
single_relations = {
"operatingSystem" = local.ami_id
}
}

depends_on = [aws_instance.app_server]
}
variables.tf
variable "ec2_name" {
type = string
}

variable "aws_region" {
type = string
}

variable "ec2_instance_type" {
type = string
}

variable "ec2_ami" {
type = string
}

variable "port_run_id" {
type = string
}
outputs.tf
outputs.tf

output "instance_id" {
description = "The unique identifier for the provisioned EC2 instance."
value = aws_instance.app_server.id
}

output "instance_state" {
description = "The state of the EC2 instance (e.g., running, stopped)."
value = aws_instance.app_server.instance_state
}

output "instance_type" {
description = "The type of EC2 instance (e.g., t2.micro, m5.large)."
value = aws_instance.app_server.instance_type
}

output "availability_zone" {
description = "The Availability Zone where the EC2 instance is deployed."
value = aws_instance.app_server.availability_zone
}

output "public_dns" {
description = "The public DNS name assigned to the EC2 instance."
value = aws_instance.app_server.public_dns
}

output "public_ip" {
description = "The public IP address assigned to the EC2 instance."
value = aws_instance.app_server.public_ip
}

output "private_dns" {
description = "The private DNS name assigned to the EC2 instance within its VPC."
value = aws_instance.app_server.private_dns
}

output "private_ip" {
description = "The private IP address assigned to the EC2 instance within its VPC."
value = aws_instance.app_server.private_ip
}

output "monitoring" {
description = "Indicates if detailed monitoring is enabled for the EC2 instance."
value = aws_instance.app_server.monitoring
}

output "security_group_ids" {
description = "The list of security group IDs assigned to the EC2 instance."
value = aws_instance.app_server.vpc_security_group_ids
}

output "key_name" {
description = "The name of the key pair associated with the EC2 instance."
value = aws_instance.app_server.key_name
}

output "subnet_id" {
description = "The ID of the subnet to which the instance is attached."
value = aws_instance.app_server.subnet_id
}

output "tags" {
description = "A map of tags assigned to the resource."
value = aws_instance.app_server.tags
}

  1. Create a GitLab Workflow file under .gitlab-ci.yaml with the following content:
GitLab workflow
modification required

Replace QUOTA_CODE on line 17 with your service quota code for vCPUs.

You can view your quotas for each region using the Service Quotas console.

Get the quota code for Running On-Demand Standard (A, C, D, H, I, M, R, T, Z) instances

gitlab-ci.yaml
stages:
- prerequisites
- terraform
- port-update

image:
name: hashicorp/terraform:light
entrypoint:
- '/usr/bin/env'
- 'PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin'

variables:
TF_VAR_gitlab_token: ${GITLAB_ACCESS_TOKEN}
AWS_ACCESS_KEY_ID: ${AWS_ACCESS_KEY_ID}
AWS_SECRET_ACCESS_KEY : ${AWS_SECRET_ACCESS_KEY}
AWS_DEFAULT_REGION: ${AWS_DEFAULT_REGION}
QUOTA_CODE: "L-1216C47A"
PORT_CLIENT_ID: ${PORT_CLIENT_ID}
PORT_CLIENT_SECRET: ${PORT_CLIENT_SECRET}

before_script:
- rm -rf .terraform
- export AWS_ACCESS_KEY=${AWS_ACCESS_KEY_ID}
- export AWS_SECRET_ACCESS_KEY=${AWS_SECRET_ACCESS_KEY}
- export AWS_DEFAULT_REGION=${AWS_DEFAULT_REGION}

fetch-port-access-token:
stage: prerequisites
except:
- pushes
before_script:
- apk update
- apk add --upgrade curl jq -q
script:
- |
echo "Getting access token from Port API"
accessToken=$(curl -X POST \
-H 'Content-Type: application/json' \
-d '{"clientId": "'"$PORT_CLIENT_ID"'", "clientSecret": "'"$PORT_CLIENT_SECRET"'"}' \
-s 'https://api.getport.io/v1/auth/access_token' | jq -r '.accessToken')

echo "ACCESS_TOKEN=$accessToken" >> data.env
runId=$(cat $TRIGGER_PAYLOAD | jq -r '.context.runId')
echo "RUN_ID=$runId" >> data.env
curl -X POST \
-H 'Content-Type: application/json' \
-H "Authorization: Bearer $accessToken" \
-d '{"message":"🏃‍♂️ Starting action to create an EC2 instance"}' \
"https://api.getport.io/v1/actions/runs/$runId/logs"
curl -X PATCH \
-H 'Content-Type: application/json' \
-H "Authorization: Bearer $accessToken" \
-d '{"link":"'"$CI_PIPELINE_URL"'"}' \
"https://api.getport.io/v1/actions/runs/$runId"
artifacts:
reports:
dotenv: data.env

check-quota:
stage: prerequisites
image: registry.gitlab.com/gitlab-org/cloud-deploy/aws-base:latest
except:
- pushes
needs:
- job: fetch-port-access-token
artifacts: true
script:
- |
echo "Checking AWS quota for CPU, Memory, and storage..."
EC2_COUNT=1

runId=$(cat $TRIGGER_PAYLOAD | jq -r '.context.runId')

curl -X POST \
-H 'Content-Type: application/json' \
-H "Authorization: Bearer $ACCESS_TOKEN" \
-d '{"statusLabel": "Checking Quota", "message":"🔍 Checking AWS quota for CPU, Memory, and storage..."}' \
"https://api.getport.io/v1/actions/runs/$runId/logs"

INSTANCE_TYPE=$(cat $TRIGGER_PAYLOAD | jq -r '.payload.properties.size')
AMI_ID=$(cat $TRIGGER_PAYLOAD | jq -r '.payload.properties.os')

# Ensure environment variables are available
if [[ -z "$INSTANCE_TYPE" || -z "$AMI_ID" ]]; then
echo "Error: INSTANCE_TYPE and AMI_ID environment variables are required."
exit 1
fi

# Get EC2 instance details
instance_vcpus=$(aws ec2 describe-instance-types --instance-types $INSTANCE_TYPE --query 'InstanceTypes[].VCpuInfo.DefaultVCpus' --output text)
instance_memory_gb=$(aws ec2 describe-instance-types --instance-types $INSTANCE_TYPE --query 'InstanceTypes[].MemoryInfo.SizeInMiB' --output text | awk '{print $1 / 1024}')

# Get relevant AMI storage requirements (EBS)
ami_storage_gb=$(aws ec2 describe-images --image-ids $AMI_ID --query 'Images[].BlockDeviceMappings[?DeviceName == `/dev/sda1`].Ebs.VolumeSize' --output text)

# Calculate required resources
required_vcpus=$((instance_vcpus * EC2_COUNT))
required_memory_gb=$((instance_memory_gb * EC2_COUNT))
required_storage_gb=$((ami_storage_gb * EC2_COUNT))

# print required resources
echo "Required vCPUs: $required_vcpus"
echo "Required Memory (GB): $required_memory_gb"
echo "Required Storage (GB): $required_storage_gb"

# Get EC2 quota
ec2_quota=$(aws service-quotas get-service-quota --service-code ec2 --quota-code $QUOTA_CODE --region $AWS_DEFAULT_REGION)
current_vcpus=$(echo $ec2_quota | jq -r '.Quota.UsageMetric.CurrentUsage.Value // 0')
vcpu_limit=$(echo $ec2_quota | jq -r '.Quota.Value')


# Quota data output
echo "INSTANCE_TYPE=$INSTANCE_TYPE" >> data.env
echo "AMI_ID=$AMI_ID" >> data.env
echo "EC2_COUNT=$EC2_COUNT" >> data.env
echo "REQUIRED_VCPUS=$required_vcpus" >> data.env
echo "REQUIRED_MEMORY_GB=$required_memory_gb" >> data.env
echo "REQUIRED_STORAGE_GB=$required_storage_gb" >> data.env

echo "Current vCPUs in use: $current_vcpus"
echo "vCPU quota limit: $vcpu_limit"
# ... add similar output for memory and storage

# Quota Checks
if [ $current_vcpus -lt $required_vcpus ] && [ $vcpu_limit -ge $required_vcpus ]; then
echo "vCPU quota is sufficient."
else
echo "Insufficient vCPU quota."
curl -X POST \
-H 'Content-Type: application/json' \
-H "Authorization: Bearer $ACCESS_TOKEN" \
-d '{"message":"Insufficient vCPU quota to create EC2 instance"}' \
"https://api.getport.io/v1/actions/runs/$runId/logs"
exit 1 # Fail pipeline if needed
fi

# Get Instance Type EBS Volume Type
ebs_volume_type=$(aws ec2 describe-images --image-id $AMI_ID --query 'Images[].BlockDeviceMappings[0].Ebs.VolumeType' --output text)

# Get EBS Volume Quota
ebs_quota=$(aws service-quotas get-service-quota --service-code ec2 --quota-code 'L-1216C47A' --region $AWS_DEFAULT_REGION)
current_storage_gb=$(echo $ebs_quota | jq -r '.Quota.UsageMetric.CurrentUsage.Value // 0')
storage_limit_gb=$(echo $ebs_quota | jq -r '.Quota.Value')

# Quota data output
echo "EBS_VOLUME_TYPE=$ebs_volume_type" >> data.env
echo "CURRENT_STORAGE_GB=$current_storage_gb" >> data.env
echo "STORAGE_LIMIT_GB=$storage_limit_gb" >> data.env

echo "Current storage in use: $current_storage_gb"
echo "Storage quota limit: $storage_limit_gb"

# Check if storage quota is sufficient
if [ $current_storage_gb -lt $required_storage_gb ] && [ $storage_limit_gb -ge $required_storage_gb ]; then
echo "Storage quota is sufficient."
else
echo "Insufficient storage quota."
curl -X POST \
-H 'Content-Type: application/json' \
-H "Authorization: Bearer $ACCESS_TOKEN" \
-d '{"terminationStatus":"FAILURE", "message":"Insufficient storage quota to create EC2 instance"}' \
"https://api.getport.io/v1/actions/runs/$runId/logs"
exit 1
fi

echo "All quotas are sufficient for deployment."
artifacts:
reports:
dotenv: data.env

search-role-entities:
stage: prerequisites
except:
- pushes
before_script:
- apk update
- apk add --upgrade curl jq -q
needs:
- job: check-quota
artifacts: true
script:
- |
echo "Searching for role entities in Port"
accessToken=$(curl -X POST \
-H 'Content-Type: application/json' \
-d '{"clientId": "'"$PORT_CLIENT_ID"'", "clientSecret": "'"$PORT_CLIENT_SECRET"'"}' \
-s 'https://api.getport.io/v1/auth/access_token' | jq -r '.accessToken')

runId=$(cat $TRIGGER_PAYLOAD | jq -r '.context.runId')
roleName=$(cat $TRIGGER_PAYLOAD | jq -r '.payload.properties.role_name')
blueprint=$(cat $TRIGGER_PAYLOAD | jq -r '.context.blueprint')

searchQuery='{
"combinator": "and",
"rules": [
{
"property": "$blueprint",
"operator": "=",
"value": "'$blueprint'"
},
{
"property": "$title",
"operator": "contains",
"value": "aws-'$roleName'"
}
]
}'

roleEntities=$(curl -X POST \
'https://api.getport.io/v1/entities/search?exclude_calculated_properties=false&attach_title_to_relation=false' \
-H "Authorization: Bearer $accessToken" \
-H 'Content-Type: application/json' \
-d "$searchQuery" | jq -c .)

echo "ROLE_ENTITIES=$roleEntities" >> data.env

# Parse the search response to calculate the next available number
nextNumber=$(echo "$roleEntities" | jq '.entities | length + 1')

# Construct the EC2 machine name
ec2MachineName="aws-${roleName}-${nextNumber}"

echo "ec2MachineName: $ec2MachineName"

echo "EC2_MACHINE_NAME=$ec2MachineName" >> data.env

runId=$(cat $TRIGGER_PAYLOAD | jq -r '.context.runId')

curl -X POST \
-H 'Content-Type: application/json' \
-H "Authorization: Bearer $accessToken" \
-d '{"statusLabel": "Provisioning", "message":"🏗️ Creating EC2 instance '$ec2MachineName'"}' \
"https://api.getport.io/v1/actions/runs/$runId/logs"
artifacts:
reports:
dotenv: data.env

apply:
stage: terraform
needs:
- job: check-quota
artifacts: true
- job: search-role-entities
artifacts: true
except:
- pushes
before_script:
- apk update
- apk add --upgrade curl jq -q
- terraform --version
- terraform init
- export TF_VAR_ec2_name=$EC2_MACHINE_NAME
- export TF_VAR_ec2_instance_type=${SERVICE_NAME:-$(cat $TRIGGER_PAYLOAD | jq -r '.payload.properties.size')}
- export TF_VAR_ec2_ami=${AMI_ID:-$(cat $TRIGGER_PAYLOAD | jq -r '.payload.properties.os')}
- export TF_VAR_aws_region=${AWS_DEFAULT_REGION}
- export TF_VAR_port_run_id=$(cat $TRIGGER_PAYLOAD | jq -r '.context.runId')
script:
- terraform validate
- terraform plan -out="planfile"
- |
terraform apply -input=false "planfile"

echo "INSTANCE_ID=$(terraform output -raw instance_id)" >> data.env
echo "INSTANCE_STATE=$(terraform output -raw instance_state)" >> data.env
echo "INSTANCE_TYPE=$(terraform output -raw instance_type)" >> data.env
echo "AVAILABILITY_ZONE=$(terraform output -raw availability_zone)" >> data.env
echo "PUBLIC_DNS=$(terraform output -raw public_dns)" >> data.env
echo "PUBLIC_IP=$(terraform output -raw public_ip)" >> data.env
echo "PRIVATE_DNS=$(terraform output -raw private_dns)" >> data.env
echo "PRIVATE_IP=$(terraform output -raw private_ip)" >> data.env
echo "MONITORING=$(terraform output -raw monitoring)" >> data.env
security_group_ids_json=$(terraform output -json security_group_ids | jq -c .)
echo "SECURITY_GROUP_IDS=$security_group_ids_json" >> data.env
echo "KEY_NAME=$(terraform output -raw key_name)" >> data.env
echo "SUBNET_ID=$(terraform output -raw subnet_id)" >> data.env
tags=$(terraform output -json tags | jq -c .)
echo "TAGS=$tags" >> data.env

update-run-status:
stage: port-update
needs:
- job: apply
artifacts: true
except:
- pushes
before_script:
- apk update
- apk add --upgrade curl jq -q
script:
- |
echo "Updating Port action run status and final logs"
accessToken=$(curl -X POST \
-H 'Content-Type: application/json' \
-d '{"clientId": "'"$PORT_CLIENT_ID"'", "clientSecret": "'"$PORT_CLIENT_SECRET"'"}' \
-s 'https://api.getport.io/v1/auth/access_token' | jq -r '.accessToken')
runId=$(cat $TRIGGER_PAYLOAD | jq -r '.context.runId')

curl -X POST \
-H 'Content-Type: application/json' \
-H "Authorization: Bearer $accessToken" \
-d '{"terminationStatus":"SUCCESS", "message":"✅ Finished creation successfully with 🔗 Instance ID: '$INSTANCE_ID'!"}' \
"https://api.getport.io/v1/actions/runs/$runId/logs"

Port Configuration

  1. Head over to the Builder page to create the following blueprints:
    • Click on the + Blueprint button.
    • Click on the {...} Edit JSON button.
    • Copy and paste the following JSON configuration into the editor.
    • Click Save.
AMI Blueprint
{
"identifier": "ami",
"description": "AMIs for creating EC2 instances",
"title": "Amazon Machine Images",
"icon": "EC2",
"schema": {
"properties": {
"image_id": {
"type": "string",
"title": "Image ID",
"pattern": "^ami-[0-9a-f]{8,17}$"
},
"description": {
"type": "string",
"title": "Description"
}
},
"required": [
"image_id",
"description"
]
},
"mirrorProperties": {},
"calculationProperties": {},
"aggregationProperties": {},
"relations": {}
}
EC2 Instance Blueprint
{
"identifier": "ec2Instance",
"description": "This blueprint represents an AWS EC2 instance in our software catalog.",
"title": "EC2 Instance",
"icon": "EC2",
"schema": {
"properties": {
"instance_state": {
"type": "string",
"title": "Instance State",
"description": "The state of the EC2 instance (e.g., running, stopped).",
"enum": [
"pending",
"running",
"shutting-down",
"terminated",
"stopping",
"stopped"
],
"enumColors": {
"pending": "yellow",
"running": "green",
"shutting-down": "pink",
"stopped": "purple",
"stopping": "orange",
"terminated": "red"
}
},
"instance_type": {
"type": "string",
"title": "Instance Type",
"description": "The type of EC2 instance (e.g., t2.micro, m5.large)."
},
"availability_zone": {
"type": "string",
"title": "Availability Zone",
"description": "The Availability Zone where the EC2 instance is deployed."
},
"public_dns": {
"type": "string",
"title": "Public DNS",
"description": "The public DNS name assigned to the EC2 instance."
},
"public_ip": {
"type": "string",
"title": "Public IP Address",
"description": "The public IP address assigned to the EC2 instance."
},
"private_dns": {
"type": "string",
"title": "Private DNS",
"description": "The private DNS name assigned to the EC2 instance within its VPC."
},
"private_ip": {
"type": "string",
"title": "Private IP Address",
"description": "The private IP address assigned to the EC2 instance within its VPC."
},
"monitoring": {
"type": "boolean",
"title": "Monitoring",
"description": "Indicates if detailed monitoring is enabled for the EC2 instance."
},
"security_group_ids": {
"type": "array",
"title": "Security Group IDs",
"description": "The list of security group IDs assigned to the EC2 instance."
},
"key_name": {
"type": "string",
"title": "Key Name",
"description": "The name of the key pair associated with the EC2 instance."
}
},
"required": []
},
"mirrorProperties": {},
"calculationProperties": {},
"aggregationProperties": {},
"relations": {
"operatingSystem": {
"title": "Operating System",
"target": "ami",
"required": false,
"many": false
}
}
}
AMI Entities

Before we continue, add some entities onto the AMI blueprint. The identifier will be the AMI Image ID.

AMI IdentifierAMI TitleDescription
ami-0f007bf1d5c770c6eAmazon Linux 2023Amazon Linux 2023 (AL2023)
ami-0c1c30571d2dae5c9Ubuntu Server 22.04 LTSCanonical, Ubuntu, 22.04 LTS
ami-08e592fbb0f535224RHEL 9Red Hat Enterprise Linux 9

  1. To create the Port action, go to the self-service page:
    • Click on the + New Action button.
    • Choose the EC2 Instance blueprint and click Next.
    • Click on the {...} Edit JSON button.
    • Copy and paste the following JSON configuration into the editor.
Port Action: Create An EC2 Instance
modification required
  • <PROJECT_ID> - your project ID.
  • <PIPELINE_TRIGGER_TOKEN> - your pipeline trigger token. Learn more.
{
"identifier": "ec2Instance_create_ec_2_instance_with_git_lab",
"title": "Create EC2 Instance with GitLab",
"description": "Trigger instance creation with GitLab and Terraform",
"trigger": {
"type": "self-service",
"operation": "CREATE",
"userInputs": {
"properties": {
"project": {
"type": "string",
"title": "Project",
"description": "AWS Account",
"default": "851725549828",
"enum": [
"851725549828",
"851745549766"
],
"enumColors": {
"851725549828": "lightGray",
"851745549766": "lightGray"
}
},
"size": {
"icon": "DefaultProperty",
"title": "Size",
"type": "string",
"default": "t2.micro",
"enum": [
"t2.micro",
"t2.small",
"t2.medium",
"t2.large"
],
"enumColors": {
"t2.micro": "lightGray",
"t2.small": "lightGray",
"t2.medium": "lightGray",
"t2.large": "lightGray"
}
},
"role_name": {
"icon": "DefaultProperty",
"type": "string",
"title": "Role Name",
"minLength": 4,
"maxLength": 8,
"pattern": "^[a-z0-9]+$"
},
"os": {
"icon": "EC2",
"title": "OS",
"description": "The operating system",
"type": "string",
"blueprint": "ami",
"format": "entity"
}
},
"required": [
"project",
"role_name",
"os",
"size"
],
"order": [
"project",
"os",
"size",
"role_name"
]
},
"blueprintIdentifier": "ec2Instance"
},
"invocationMethod": {
"type": "WEBHOOK",
"url": "https://gitlab.com/api/v4/projects/<PROJECT_ID>/ref/main/trigger/pipeline?token=<PIPELINE_TRIGGER_TOKEN>",
"agent": false,
"synchronized": false,
"method": "POST",
"body": {
"action": "{{ .action.identifier[(\"ec2Instance_\" | length):] }}",
"resourceType": "run",
"status": "TRIGGERED",
"trigger": "{{ .trigger | {by, origin, at} }}",
"context": {
"entity": "{{.entity.identifier}}",
"blueprint": "{{.action.blueprint}}",
"runId": "{{.run.id}}"
},
"payload": {
"entity": "{{ (if .entity == {} then null else .entity end) }}",
"action": {
"invocationMethod": {
"type": "WEBHOOK",
"url": "https://gitlab.com/api/v4/projects/<PROJECT_ID>/ref/main/trigger/pipeline?token=<PIPELINE_TRIGGER_TOKEN>",
"agent": false,
"synchronized": false,
"method": "POST"
},
"trigger": "{{.trigger.operation}}"
},
"properties": {
"{{if (.inputs | has(\"project\")) then \"project\" else null end}}": "{{.inputs.\"project\"}}",
"{{if (.inputs | has(\"size\")) then \"size\" else null end}}": "{{.inputs.\"size\"}}",
"{{if (.inputs | has(\"role_name\")) then \"role_name\" else null end}}": "{{.inputs.\"role_name\"}}",
"{{if (.inputs | has(\"os\")) then \"os\" else null end}}": "{{.inputs.\"os\" | if type == \"array\" then map(.identifier) else .identifier end}}"
},
"censoredProperties": "{{.action.encryptedProperties}}"
}
}
},
"requiredApproval": false,
"publish": true
}
  • Fill out the backend form section with your values:
    • For the Endpoint URL you need to add a URL in the following format:
      • To create a pipeline trigger token, follow this guide.
        https://gitlab.com/api/v4/projects/{PROJECT_ID}/ref/main/trigger/pipeline?token={PIPELINE_TRIGGER_TOKEN}
    • Set HTTP method to POST.
    • Set Request type to Async.
    • Set Use self-hosted agent to No.

Let's test it!

  1. Head to the Self Service hub
  2. Click on the Create An EC2 Instance action
  3. Fill the pop-up form with details of the EC2 Instance you wish to create
  1. Click on Execute
  2. Wait for the EC2 Instance to be created in AWS

Congrats 🎉 You've created an EC2 Instance in Port 🔥

Next Steps

  1. Add a disk to the EC2 instance