1. Path-based Routing for AI Microservices on Kubernetes.


    Path-based routing in Kubernetes is commonly accomplished through Ingress resources. An Ingress resource manages external access to services inside a Kubernetes cluster, typically HTTP. Ingress can provide load balancing, SSL termination, and name-based virtual hosting.

    In this Pulumi program, we will define an Ingress resource that establishes path-based routing to AI microservices in a Kubernetes cluster. Each path specified in the Ingress resource will correspond to a different microservice.

    First, a Kubernetes Service is created for each microservice to expose it within the cluster. These services are responsible for load balancing the traffic and providing a stable endpoint to reach the pods comprising the microservice.

    Next, an Ingress resource is set up to manage external access to these services. This Ingress includes rules that map incoming requests based on the path to the appropriate microservice.

    Here's how you could set up path-based routing for two AI microservices named "service-a" and "service-b" using Pulumi:

    import pulumi import pulumi_kubernetes as k8s # Define a Kubernetes Service for AI Microservice A service_a = k8s.core.v1.Service("service-a", spec=k8s.core.v1.ServiceSpecArgs( type="ClusterIP", # Type of service is ClusterIP because it's only reachable within the cluster selector={"app": "microservice-a"}, # Selector for the pods this service should target ports=[k8s.core.v1.ServicePortArgs( port=80, # The port the service is exposed on target_port="http", # The target port on the pod(s) )], )) # Define a Kubernetes Service for AI Microservice B service_b = k8s.core.v1.Service("service-b", spec=k8s.core.v1.ServiceSpecArgs( type="ClusterIP", selector={"app": "microservice-b"}, ports=[k8s.core.v1.ServicePortArgs( port=80, target_port="http", )], )) # Define the Ingress resource to route traffic based on paths ingress = k8s.networking.v1.Ingress("ingress", metadata=k8s.meta.v1.ObjectMetaArgs( name="path-based-ingress", annotations={"nginx.ingress.kubernetes.io/rewrite-target": "/"}, ), spec=k8s.networking.v1.IngressSpecArgs( rules=[k8s.networking.v1.IngressRuleArgs( http=k8s.networking.v1.HTTPIngressRuleValueArgs( paths=[ k8s.networking.v1.HTTPIngressPathArgs( path="/service-a", # External path for AI Microservice A path_type="Prefix", backend=k8s.networking.v1.IngressBackendArgs( service=k8s.networking.v1.IngressServiceBackendArgs( name=service_a.metadata.name, port=k8s.networking.v1.ServiceBackendPortArgs( number=80, ), ), ), ), k8s.networking.v1.HTTPIngressPathArgs( path="/service-b", # External path for AI Microservice B path_type="Prefix", backend=k8s.networking.v1.IngressBackendArgs( service=k8s.networking.v1.IngressServiceBackendArgs( name=service_b.metadata.name, port=k8s.networking.v1.ServiceBackendPortArgs( number=80, ), ), ), ), ], ), )], ))

    In the above program, service-a and service-b are Kubernetes Services that expose our AI microservices within the cluster. Then we create an Ingress resource named ingress. The Ingress resource has rules to route traffic coming to /service-a to the service-a backend on port 80, and requests to /service-b go to the service-b backend, also on port 80.

    The nginx.ingress.kubernetes.io/rewrite-target annotation tells the Ingress controller to strip the matched part of the path (/service-a or /service-b) before forwarding the request to the respective service. This is specific to the NGINX Ingress controller. If you're using a different Ingress controller, you'd want to adjust the annotations accordingly.

    To deploy this Pulumi program, you need to have Pulumi installed and configured to communicate with your Kubernetes cluster. Once you've written the code to a file (e.g., main.py), you can run pulumi up from the command line in the same directory as your code, which will provision the resources defined in the program in your cluster.