1. EMQX Cluster Deployment for IoT Message Brokering


    To deploy an EMQX cluster for IoT message brokering, it's important to understand the resources involved. EMQX is a highly scalable, distributed MQTT message broker used for large-scale IoT applications. Unfortunately, there doesn't seem to be a native Pulumi resource specifically for EMQX. However, you can still automate the deployment of an EMQX cluster using Pulumi by provisioning the necessary infrastructure on a cloud provider that supports container orchestration services, such as Amazon ECS or Azure Kubernetes Service (AKS), and then deploying EMQX within that infrastructure.

    Below is a high-level outline of steps you would typically follow:

    1. Provision the underlying infrastructure to run EMQX clusters, which can be VMs, Containers, or Managed Kubernetes Service, depending on your preference.
    2. Deploy EMQX as docker containers or as part of a Kubernetes Deployment.
    3. Configure networking, security settings, and possibly a Load Balancer to manage traffic to the EMQX nodes.
    4. Set up monitoring and logging to ensure the health and performance of the EMQX cluster.

    Given the above, I'm going to show you an example of deploying an EMQX cluster using Amazon ECS, as it provides a straightforward platform to run containerized applications.

    Program Description

    First, we'll create an Amazon ECS cluster. Then, we'll define a Task Definition to run EMQX containers. After that, we'll set up a Service within our ECS cluster to manage and scale our EMQX containers. And finally, we'll provision a Load Balancer to distribute the traffic across our running EMQX containers.

    The Load Balancer will ensure that IoT devices can connect to any available EMQX broker in the cluster for message brokering. Let's go ahead with the Pulumi program to achieve this.

    import pulumi import pulumi_aws as aws # Create an ECS cluster to run the EMQX containers. ecs_cluster = aws.ecs.Cluster('emqx-cluster') # Define an IAM role for the ECS Task Execution. This IAM role will allow ECS to pull container images and log to CloudWatch. task_exec_role = aws.iam.Role('task-exec-role', assume_role_policy=( '{"Version": "2008-10-17",' '"Statement": [{"Sid": "","Effect": "Allow","Principal": {"Service": "ecs-tasks.amazonaws.com"},' '"Action": "sts:AssumeRole"}]}' )) # Attach the task execution policy to the IAM role. aws.iam.RolePolicyAttachment('task-exec-role-policy', role=task_exec_role.name, policy_arn=aws.iam.ManagedPolicy.AWS_ECS_TASK_EXECUTION_ROLE_POLICY) # Create a Task Definition for the EMQX brokers. This defines the container to use and resource configuration. emqx_task_definition = aws.ecs.TaskDefinition('emqx-task', family='emqx', cpu='512', memory='2048', network_mode='awsvpc', requires_compatibilities=['FARGATE'], execution_role_arn=task_exec_role.arn, container_definitions=pulumi.Output.all(ecs_cluster.name).apply( lambda args: f""" [ {{ "name": "{args[0]}", "image": "emqx/emqx:latest", "cpu": 512, "memory": 2048, "essential": true, "portMappings": [ {{ "containerPort": 1883, "hostPort": 1883 }}, {{ "containerPort": 8883, "hostPort": 8883 }}, {{ "containerPort": 8083, "hostPort": 8083 }} ] }} ] """)) # Define a Security Group for the Load Balancer to allow traffic to the EMQX broker. emqx_lb_security_group = aws.ec2.SecurityGroup('emqx-lb-sg', vpc_id=vpc.id, ingress=[{'from_port': 1883, 'to_port': 1883, 'protocol': 'tcp', 'cidr_blocks': ['']}, {'from_port': 8883, 'to_port': 8883, 'protocol': 'tcp', 'cidr_blocks': ['']}, {'from_port': 8083, 'to_port': 8083, 'protocol': 'tcp', 'cidr_blocks': ['']}], egress=[{'from_port': 0, 'to_port': 0, 'protocol': '-1', 'cidr_blocks': ['']}]) # Create an Application Load Balancer to distribute traffic to the EMQX containers. emqx_lb = aws.lb.LoadBalancer('emqx-lb', security_groups=[emqx_lb_security_group.id], subnets=subnet_ids, internal=False) # Create a Target Group for the EMQX containers. emqx_target_group = aws.lb.TargetGroup('emqx-tg', port=1883, protocol='TCP', vpc_id=vpc.id, target_type='ip') # Register the Target Group with the Load Balancer. aws.lb.Listener('emqx-listener', load_balancer_arn=emqx_lb.arn, port=1883, default_actions=[{'type': 'forward', 'target_group_arn': emqx_target_group.arn}]) # Create the ECS Service to run the EMQX containers and register them with the Target Group. emqx_service = aws.ecs.Service('emqx-service', cluster=ecs_cluster.arn, task_definition=emqx_task_definition.arn, network_configuration={ 'awsvpc_configuration': { 'subnets': subnet_ids, 'security_groups': [emqx_lb_security_group.id] }, }, desired_count=3, # The desired number of EMQX instances launch_type='FARGATE', load_balancers=[{'target_group_arn': emqx_target_group.arn, 'container_name': ecs_cluster.name, 'container_port': 1883}]) # Export the URL of the Load Balancer to access the EMQX cluster outside. pulumi.export('emqx_load_balancer_dns', emqx_lb.dns_name)

    This program creates an ECS cluster designated for EMQX. It uses the aws.ecs.Cluster resource to create the cluster in AWS ECS (ECS Cluster Docs). We define a task execution role and attach the standard AWS ECS task execution policy using aws.iam.Role and aws.iam.RolePolicyAttachment.

    We defined a task definition for our EMQX cluster named 'emqx-task' using the aws.ecs.TaskDefinition resource, specifying a container to use (emqx/emqx:latest), along with the necessary CPU and memory resources. The task definition also declares the port mappings that will be used by the EMQX broker to communicate with IoT devices.

    Next, we create a security group (`