1. Smart Traffic Routing for AI APIs using AWS ALB

    Python

    Sure, to implement smart traffic routing for AI APIs using AWS Application Load Balancer (ALB), you'll need to set up a few resources:

    1. AWS ALB (Application Load Balancer) — This will be the central point that receives incoming traffic and routes it to the appropriate backend services (target groups) based on rules you define.

    2. Target Groups — These groups contain the actual endpoints (e.g., EC2 instances, Lambda functions, or IP addresses) where the different versions of your AI API are running. You can have different target groups for different versions of your API.

    3. Listener — The listener checks for connection requests on the ports that you set up and routes traffic to target groups based on the rules you define.

    4. Listener Rules — These are the conditions and priorities you define to route traffic to different target groups. For example, you could route traffic based on the path in the request (e.g., /v1/* goes to version 1 of your API, /v2/* goes to version 2).

    5. Listener Certificates (if using HTTPS) — If you're serving your API over HTTPS, you'll need to provide the necessary SSL/TLS certificate.

    Below is a Pulumi program written in Python that illustrates how to set up smart traffic routing for AI APIs using AWS ALB.

    import pulumi import pulumi_aws as aws # Create a VPC to host our ALB and Targets vpc = aws.ec2.Vpc("app-vpc", cidr_block="10.100.0.0/16", tags={"Name": "application-vpc"}) # Create subnets for the VPC subnet_one = aws.ec2.Subnet("app-subnet-one", vpc_id=vpc.id, cidr_block="10.100.1.0/24", availability_zone="us-west-2a", tags={"Name": "application-subnet-one"}) subnet_two = aws.ec2.Subnet("app-subnet-two", vpc_id=vpc.id, cidr_block="10.100.2.0/24", availability_zone="us-west-2b", tags={"Name": "application-subnet-two"}) # Set up an Internet Gateway for the VPC internet_gateway = aws.ec2.InternetGateway("vpc-igw", vpc_id=vpc.id) # Create a load balancer to listen for incoming requests alb = aws.lb.LoadBalancer("app-lb", subnets=[subnet_one.id, subnet_two.id], security_groups=[], # You should specify your Security Groups here idle_timeout=400, internal=False, load_balancer_type="application", tags={"Name": "application-load-balancer"}) # Create a target group for version 1 of the AI API ai_api_v1_target_group = aws.lb.TargetGroup("ai-api-v1-target-group", vpc_id=vpc.id, port=80, # Specify the port the AI API listens on protocol="HTTP", target_type="ip", # You can also use `instance` or `lambda` health_check=aws.lb.TargetGroupHealthCheckArgs( interval=30, path="/v1/health"), tags={"Name": "ai-api-v1-target-group"}) # Create a target group for version 2 of the AI API ai_api_v2_target_group = aws.lb.TargetGroup("ai-api-v2-target-group", vpc_id=vpc.id, port=80, # Specify the port the AI API listens on protocol="HTTP", target_type="ip", # You can also use `instance` or `lambda` health_check=aws.lb.TargetGroupHealthCheckArgs( interval=30, path="/v2/health"), tags={"Name": "ai-api-v2-target-group"}) # Create a listener for the ALB listener = aws.lb.Listener("app-listener", load_balancer_arn=alb.arn, port=80, default_actions=[aws.lb.ListenerDefaultActionArgs( type="forward", target_group_arn=ai_api_v1_target_group.arn)]) # Create routing rules based on the request path listener_rule_v1 = aws.lb.ListenerRule("listener-rule-v1", listener_arn=listener.arn, priority=100, actions=[aws.lb.ListenerRuleActionArgs( type="forward", target_group_arn=ai_api_v1_target_group.arn)], conditions=[aws.lb.ListenerRuleConditionArgs( path_pattern=aws.lb.ListenerRuleConditionPathPatternArgs( values=["/v1/*"]))]) listener_rule_v2 = aws.lb.ListenerRule("listener-rule-v2", listener_arn=listener.arn, priority=99, actions=[aws.lb.ListenerRuleActionArgs( type="forward", target_group_arn=ai_api_v2_target_group.arn)], conditions=[aws.lb.ListenerRuleConditionArgs( path_pattern=aws.lb.ListenerRuleConditionPathPatternArgs( values=["/v2/*"]))]) # Export the DNS name of the load balancer pulumi.export("load_balancer_dns_name", alb.dns_name)

    How it works:

    • We first set up a VPC and subnets to house our ALB and backend services.
    • We then create an internet gateway to allow outside traffic into our VPC.
    • With our network infrastructure in place, we set up an ALB, which will route incoming traffic based on the configured rules.
    • We create separate target groups for different versions of our AI API.
    • Listener rules are added to the listener to forward traffic to the appropriate target group based on the request path.
    • Finally, we export the DNS name of the ALB so that we can map it to our domain name.

    Deploying and running the above Pulumi program will lead to a fully configured environment where traffic is smartly routed based on the request path to various versions of an AI API.


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