1. Intelligent Request Routing for AI APIs with AWS ALB


    Intelligent request routing is a crucial feature for distributing incoming traffic across multiple targets, such as EC2 instances, containers, and Lambda functions, which is useful when you set up AI APIs to ensure high availability and low latency. AWS Application Load Balancer (ALB) is designed to offer advanced request routing capabilities, making it well-suited for such tasks.

    Below, I will guide you through a basic Pulumi program written in Python to create an AWS ALB that can route requests intelligently to different targets based on the rules we define. This setup is optimal for directing traffic to AI APIs based on criteria like request paths or header values.

    The following Pulumi program will:

    1. Create an EC2 VPC to host our AI APIs.
    2. Set up an ALB within the VPC to route traffic to our APIs.
    3. Define target groups, which is where our requests will ultimately be sent.
    4. Establish listener rules to intelligently route requests based on the request content.

    Here is a Pulumi program that defines these resources:

    import pulumi import pulumi_aws as aws # Create a new security group for the ALB sec_group = aws.ec2.SecurityGroup('secgroup', description='Enable HTTP access', ingress=[{ 'protocol': 'tcp', 'from_port': 80, 'to_port': 80, 'cidr_blocks': [''], }], egress=[{ 'protocol': '-1', 'from_port': 0, 'to_port': 0, 'cidr_blocks': [''], }] ) # Create a VPC to host our services vpc = aws.ec2.Vpc('app-vpc', cidr_block='', enable_dns_hostnames=True, enable_dns_support=True) # Create subnets subnet1 = aws.ec2.Subnet('app-vpc-subnet-1', vpc_id=vpc.id, cidr_block='', availability_zone='us-west-2a') subnet2 = aws.ec2.Subnet('app-vpc-subnet-2', vpc_id=vpc.id, cidr_block='', availability_zone='us-west-2b') # Create an ALB alb = aws.lb.LoadBalancer('app-lb', internal=False, load_balancer_type='application', security_groups=[sec_group.id], subnets=[subnet1.id, subnet2.id]) # Create a target group for our default route default_target_group = aws.lb.TargetGroup('default-target', port=80, protocol='HTTP', vpc_id=vpc.id) # Create a listener for the ALB that forwards to the default target group listener = aws.lb.Listener('listener', load_balancer_arn=alb.arn, port=80, default_actions=[{ 'type': 'forward', 'target_group_arn': default_target_group.arn }]) # Define target group for the AI API ai_api_group = aws.lb.TargetGroup('ai-api-target', port=80, protocol='HTTP', vpc_id=vpc.id) # Create a listener rule to route based on request path to the AI API target group listener_rule = aws.lb.ListenerRule('listener-rule', listener_arn=listener.arn, priority=100, actions=[{ 'type': 'forward', 'target_group_arn': ai_api_group.arn }], conditions=[{ 'path_pattern': { 'values': ['/ai-api/*'] } }]) # Export the DNS name of the ALB pulumi.export('alb_dns_name', alb.dns_name)

    Each part of this program sets up a piece of the infrastructure:

    • Security Group: This defines a group that specifies what type of traffic is allowed to reach the load balancer. In the example, it's configured to only allow HTTP traffic on port 80.
    • VPC and Subnets: These provide the necessary networking capabilities for your ALB and API resources. We create two subnets across different availability zones for high availability.
    • ALB (Load Balancer): This is the application load balancer that will route incoming requests. It is not set as internal since we expect requests from the internet.
    • Target Groups: These groups are used to route requests to one or more registered targets, like EC2 instances running our AI APIs.
    • Listener: This listens for incoming traffic on port 80 (HTTP traffic in this case) and forwards it to the target groups based on rules.
    • Listener Rule: This rule specifies that any traffic which is to the specified path (/ai-api/*) should be forwarded to the ai_api_group target group, where our AI API services can process the requests.
    • Export: At the end, we export the ALB's DNS name, which allows us to know where to direct our AI API requests.

    Before running this program, make sure that AWS CLI is configured on your machine with proper access keys and default region set. This will allow Pulumi to deploy resources to your AWS account.

    The resources above are documented in the AWS Pulumi docs. You can expand and modify this program depending on the complexity and requirements of your application. For example, adding auto-scaling groups, specifying health checks, or setting up SSL/TLS listeners could be next steps for production readiness.