1. AI Workload Tracing with Istio on Kubernetes


    To enable AI-powered workload tracing with Istio on a Kubernetes cluster, you'll need to follow these high-level steps:

    1. Set up a Kubernetes cluster: Before deploying Istio, you need a running Kubernetes cluster. You can create one using cloud providers like AWS EKS, Azure AKS, or Google GKE, or on-premises using tools like kubeadm.

    2. Install Istio: Once you have the cluster, you can install Istio. Istio provides a powerful suite of tools for observing the traffic within your cluster, including tracing, metrics, and logs.

    3. Configure Istio for Tracing: After you have installed Istio, you must set it up to send traces to a distributed tracing system like Jaeger or Zipkin.

    4. Deploy your workload: With Istio installed and configured, you can now deploy your application onto the cluster.

    5. Enable automatic sidecar injection: Istio uses a sidecar proxy model, where each pod in the Kubernetes cluster is augmented with an additional container responsible for routing, metrics collection, and security. You can enable automatic sidecar injection which will make sure that every pod has a sidecar proxy.

    6. Verify tracing: Finally, you need to verify that tracing is working by sending traffic to your application and checking that traces are correctly reported to your distributed tracing system.

    Below is a Pulumi Python program that illustrates the setup of a Kubernetes cluster with AWS EKS and the installation of Istio on that cluster. After you have the cluster and Istio ready, you can further configure Istio for tracing and deploy workloads accordingly.

    import pulumi from pulumi_eks import Cluster from pulumi_kubernetes import Provider, helm # Create an EKS cluster eks_cluster = Cluster("my-cluster") # Create a Kubernetes Provider referencing the EKS cluster k8s_provider = Provider("k8s-provider", kubeconfig=eks_cluster.kubeconfig) # Install Istio using the Helm chart istio_namespace = "istio-system" helm_chart = helm.v3.Chart( "istio-base", helm.v3.ChartOpts( chart="istio-base", version="1.8.0", # Replace with the version of Istio you would like to use fetch_opts=helm.v3.FetchOpts( repo="https://istio-release.storage.googleapis.com/charts" ), namespace=istio_namespace, values={ "prometheus": {"enabled": False}, # Disabling built-in Prometheus as an example }, ), opts=pulumi.ResourceOptions(provider=k8s_provider) ) # Apply the Istio CRDs for deploying the rest of Istio components. # These are required to be applied separately in a step before we # can deploy components like Istio's pilot, gateways, etc. istio_crds_chart = helm.v3.Chart( "istio-crds", helm.v3.ChartOpts( chart="istio-crds", version="1.8.0", # Use the same version as Istio base fetch_opts=helm.v3.FetchOpts( repo="https://istio-release.storage.googleapis.com/charts" ), namespace=istio_namespace, ), opts=pulumi.ResourceOptions(provider=k8s_provider, depends_on=[helm_chart]) ) # Export the EKS cluster's kubeconfig pulumi.export("kubeconfig", eks_cluster.kubeconfig)

    This program does several things:

    1. Creates an EKS cluster using the pulumi_eks module. This will be the Kubernetes environment where the application and Istio will run.
    2. Sets up a Kubernetes Provider instance, which allows Pulumi to interact with the created EKS cluster.
    3. Installs the Istio Base Helm chart into the istio-system namespace. Istio components like istiod, ingressgateway, and egressgateway are deployed. Specific values can be tuned according to your needs in the values dictionary.
    4. Applies the Istio CRDs which are necessary to fully utilize Istio's control plane features.
    5. Exports the kubeconfig which allows you to interact with your cluster using kubectl or other Kubernetes tools.

    If you're not familiar with Helm, it's a package manager for Kubernetes that automates the deployment and management of applications on Kubernetes.

    Note: You will need to configure your Pulumi program with your AWS credentials, either via environment variables, AWS configuration files, or the Pulumi configuration system.

    After running this Pulumi program with pulumi up, you will have an EKS cluster with Istio installed. You can then proceed to configure Istio to enable tracing as described above, by updating the Istio configuration to integrate with a tracing solution like Jaeger or Zipkin, and deploy your applications and services into the cluster.

    For full details on configuring automatic sidecar injection and verifying tracing, refer to the Istio documentation.