1. Scalable and Secure AI Platform Endpoints with GCP Load Balancing


    If you need a scalable and secure AI Platform on Google Cloud Platform (GCP), you can leverage a variety of GCP services to achieve this. Here's a breakdown of what we'll do:

    1. Create Network Endpoint Groups (NEGs): NEGs allow you to specify endpoints for your applications on your VM instances. Instances within NEGs can be spread across multiple zones, which provides scalability.

    2. Set up Load Balancers: GCP offers different types of load balancers. For global reach (HTTP(S) traffic), you might choose a global external HTTP(S) load balancer.

    3. Utilize Autoscaling: To ensure your application can scale in response to load, we'll tie in autoscaling policies to adjust the number of instances automatically.

    4. Implement Health Checks: Health checks will be used by the load balancer to determine which instances are healthy and can handle requests.

    5. Secure with SSL Certificates: To secure the traffic between the clients and the load balancer, we'll attach an SSL certificate.

    6. Backend Services: They act as a logical entity that can be a TCP/UDP service, which you can attach to your load balancer to balance the traffic.

    Let's get started with a Pulumi program that sets up the necessary infrastructure on Google Cloud Platform:

    import pulumi import pulumi_gcp as gcp # Create the network endpoint group (NEG) for the AI Platform instances. # Documentation: https://www.pulumi.com/registry/packages/gcp/api-docs/compute/networkendpointgroup/ ai_platform_neg = gcp.compute.NetworkEndpointGroup("aiPlatformNeg", default_port=80, # AI platform will serve on port 80 by default network="default", # Using the default network for simplicity zone="us-central1-a", # Zone where to locate the NEG ) # Define a health check for the instances. It can be HTTP, HTTPS, TCP, etc. # Documentation: https://www.pulumi.com/registry/packages/gcp/api-docs/compute/healthcheck/ health_check = gcp.compute.HealthCheck("healthCheck", check_interval_sec=5, timeout_sec=5, healthy_threshold=2, unhealthy_threshold=2, tcp_health_check={ "port": 80, }, ) # Create a backed service to link the NEG and enable the CDN. # Documentation: https://www.pulumi.com/registry/packages/gcp/api-docs/compute/backendservice/ backend_service = gcp.compute.BackendService("backendService", backends=[{ "group": ai_platform_neg.id, }], health_checks=[health_check.id], port_name="http", protocol="HTTP", enable_cdn=True, ) # Create an SSL certificate to secure our AI Platform endpoint. # Documentation: https://www.pulumi.com/registry/packages/gcp/api-docs/compute/sslcertificate/ ssl_certificate = gcp.compute.SSLCertificate("sslCertificate", private_key="""-----BEGIN PRIVATE KEY----- # private_key_here -----END PRIVATE KEY-----""", certificate="""-----BEGIN CERTIFICATE----- # certificate_here -----END CERTIFICATE-----""", ) # Configure an HTTP load balancer to route traffic to the backend service. # Documentation: https://www.pulumi.com/registry/packages/gcp/api-docs/compute/urlmap/ url_map = gcp.compute.URLMap("urlMap", default_service=backend_service.id, ) # Create the target HTTP proxy to route requests to your URL map. # Documentation: https://www.pulumi.com/registry/packages/gcp/api-docs/compute/targethttpproxy/ http_proxy = gcp.compute.TargetHttpProxy("httpProxy", url_map=url_map.id, ssl_certificates=[ssl_certificate.id] ) # Establish a forwarding rule to tie the IP, target proxy, and SSL certificate together. # Documentation: https://www.pulumi.com/registry/packages/gcp/api-docs/compute/globalforwardingrule/ forwarding_rule = gcp.compute.GlobalForwardingRule("forwardingRule", ip_protocol="TCP", port_range="443", target=http_proxy.id, ) pulumi.export('backend_service_url', backend_service.self_link) pulumi.export('forwarding_rule_ip', forwarding_rule.ip_address)

    This program sets up a scalable and secure endpoint suitable for an AI platform. Although not explicitly creating an AI Platform service, it prepares infrastructure for scaling and securing AI applications. If you have an AI application, the corresponding service could be tied to the Network Endpoint Group created here.

    This will create:

    • A Network Endpoint Group to register your AI instances.
    • A health check to ensure traffic only goes to healthy instances.
    • A Backend Service that uses the NEG as backends.
    • An SSL certificate for secure communication.
    • A URL map, HTTP proxy, and forwarding rule to route incoming traffic.

    Keep in mind that real-world usage may require additional setup, such as configuring IAM permissions, setting up a custom VPC network, and more, depending on your specific requirements.