1. Nomad as Orchestrator for AI Batch Processing Jobs


    To set up Nomad as an Orchestrator for AI Batch Processing Jobs using Pulumi, we need to deploy a Nomad cluster environment and configure it to run batch processing workloads. Since Nomad itself is agnostic to cloud providers, it can run on any cloud infrastructure or on-premises as long as the necessary compute resources are provided.

    Here, I'll show you how you might deploy a simple Nomad server cluster on AWS using Pulumi. After setting up the cluster, you will be able to submit AI batch processing jobs to Nomad which will manage the job scheduling, deployment, and scaling.

    Let's start by deploying the necessary infrastructure:

    1. Compute Instances for Nomad Servers: We will create an EC2 instance that will run Nomad Server which manages the cluster and client nodes.
    2. Security Groups: For allowing communication between the instances and to allow SSH access.
    3. IAM Roles: To define permissions that we'll attach to our EC2 instances, so they can access other AWS Resources if needed.

    Once the infrastructure is in place, we will install the Nomad software on the server and configure it with basic settings.

    Now, let's write a Pulumi program to model this infrastructure. This example uses the pulumi_aws library to provision the resources in AWS.

    import pulumi import pulumi_aws as aws # Create an EC2 instance to run Nomad Server nomad_server_group = aws.ec2.SecurityGroup('nomad-server-sg', description='Allow all inbound traffic for Nomad', ingress=[{ 'protocol': '-1', 'from_port': 0, 'to_port': 0, 'cidr_blocks': [''], }], egress=[{ 'protocol': '-1', 'from_port': 0, 'to_port': 0, 'cidr_blocks': [''], }] ) # IAM role and instance profile for EC2 instances to manage permissions nomad_instance_role = aws.iam.Role('nomad-instance-role', assume_role_policy=aws.iam.get_policy_document(statements=[{ 'actions': ['sts:AssumeRole'], 'principals': [{ 'type': 'Service', 'identifiers': ['ec2.amazonaws.com'], }], }]).json, ) nomad_instance_profile = aws.iam.InstanceProfile('nomad-instance-profile', role=nomad_instance_role.name ) # Define the AMI, here I am using a generic AWS Linux 2 AMI ami = pulumi_aws.get_ami(most_recent=True, owners=['amazon'], filters=[{'name':'name','values':['amzn2-ami-hvm-*-x86_64-gp2']}] ) # Actual EC2 instance nomad_server_instance = aws.ec2.Instance('nomad-server-instance', instance_type='t2.micro', # You may choose a different type based on your workload security_groups=[nomad_server_group.name], iam_instance_profile=nomad_instance_profile.name, ami=ami.id, user_data="""#!/bin/bash # Commands to install Nomad sudo yum update -y sudo yum install -y wget unzip wget https://releases.hashicorp.com/nomad/1.1.4/nomad_1.1.4_linux_amd64.zip unzip nomad_1.1.4_linux_amd64.zip sudo mv nomad /usr/bin/ nomad agent -dev # Starting Nomad in development mode for demo purposes; for production, use -config flag to point to a proper configuration file """, # This script will run on instance startup to install Nomad tags={'Name': 'nomad-server'} ) # Output the public IP address of the Nomad server pulumi.export('nomad_server_ip', nomad_server_instance.public_ip)

    In the above program:

    • I created an AWS security group (nomad_server_group) that allows inbound traffic on all ports. This is for demonstration purposes. In a production environment, you should restrict the traffic to only required ports.

    • Setup an IAM Role and instance profile to assign to our EC2 instance which might be necessary for tasks that require AWS resource access.

    • Used the Pulumi AWS AMI data source to get the latest Amazon Linux 2 image for the Nomad server.

    • Defined an EC2 instance (nomad_server_instance) that references the security group and IAM role we created, and also uses a user_data script to install Nomad when the instance starts.

    • The user_data script written in the EC2 instance resource is a shell script that updates the system packages, installs dependencies, downloads the Nomad binary, and starts a Nomad agent in development mode.

    Lastly, we exported the public IP address of the Nomad server so you can access the Nomad UI or API.


    • Replace 't2.micro' with the instance type that suits your workloads.
    • The instance is started in dev mode, which is not suitable for production. In a production setup, you would create a configuration file for Nomad and reference it using the -config flag.

    Also, the security groups here are quite permissive; they allow all traffic in and out of the instance. For production use, you should strictly limit the ingress and egress to only the necessary ports and IP ranges.

    This is a simplified demonstration. In a real-world application, you would probably use an Auto Scaling Group or multiple instances for high availability, along with a load balancer, and fine-tune the security configurations. You would also set up Nomad clients on additional EC2 instances which are managed by this Nomad server.