1. Real-time AI Indexing Services with Milvus in Kubernetes Clusters


    To set up a real-time AI indexing service with Milvus on a Kubernetes cluster using Pulumi, you would need to follow these steps:

    1. Provision a Kubernetes cluster on a cloud provider of your choice (AWS, GCP, Azure, etc.).
    2. Install and configure necessary Kubernetes resources like Deployments, Services, and StatefulSets for Milvus.
    3. Deploy Milvus, which may involve custom resource definitions (CRDs) for specific Milvus components.

    For this explanation, I'll show you how to create a Kubernetes cluster using Pulumi and Azure (since Pulumi supports various cloud providers), although the specifics for setting up Milvus would be similar for any cloud.

    First, we'll create a Kubernetes cluster using Pulumi's azure-native provider. Then, we will define Kubernetes resources for deploying Milvus; this may involve using another Pulumi package, pulumi_kubernetes, which allows us to work with Kubernetes objects.


    • Pulumi CLI installed and configured.
    • Access to an Azure cloud account and credentials configured for Pulumi.
    • Milvus Kubernetes YAML configurations (not shown in this example).

    Program Overview:

    The following Pulumi Python program will achieve these goals:

    • Provision an Azure Kubernetes cluster.
    • Define a Kubernetes namespace for the Milvus services.
    • Placeholder comments for where you would define Kubernetes resources to deploy Milvus.

    Let's begin by writing a Pulumi program:

    import pulumi import pulumi_azure_native as azure_native from pulumi_azure_native import resources, containerservice import pulumi_kubernetes as kubernetes # First, we create a resource group if it doesn't already exist. resource_group = resources.ResourceGroup('milvus-rg') # Now let's provision an Azure Kubernetes Service (AKS) cluster. aks_cluster = containerservice.ManagedCluster( 'milvus-aks-cluster', resource_group_name=resource_group.name, agent_pool_profiles=[{ 'count': 3, 'vm_size': 'Standard_DS2_v2', 'mode': 'System', 'name': 'agentpool' }], dns_prefix='milvus-k8s', enable_rbac=True, # Enable Kubernetes RBAC for the cluster kubernetes_version='1.20.7', linux_profile={ 'adminUsername': 'adminuser', 'ssh': { 'publicKeys': [{ 'keyData': 'ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQCf...' # Replace with your SSH public key }] } }, identity={ 'type': 'SystemAssigned' } ) # We need the `kubeconfig` to connect to the AKS cluster. creds = pulumi.Output.all(resource_group.name, aks_cluster.name).apply( lambda args: containerservice.list_managed_cluster_user_credentials( resource_group_name=args[0], resource_name=args[1] ) ) kubeconfig = creds.kubeconfigs[0].value.apply(lambda enc: enc.decode('utf-8')) # With the `kubeconfig`, we can use Pulumi's Kubernetes provider to interact with the AKS cluster. k8s_provider = kubernetes.Provider('k8s-provider', kubeconfig=kubeconfig) # Next, we'll create a Kubernetes Namespace for Milvus. milvus_namespace = kubernetes.core.v1.Namespace( 'milvus-namespace', metadata={ 'name': 'milvus' }, opts=pulumi.ResourceOptions(provider=k8s_provider) ) # TODO: Define the Kubernetes resources (Deployments, Services, StatefulSets, etc.) for Milvus here. # You will use `milvus_namespace.metadata['name']` as the namespace for each resource. # Placeholder for Milvus deployment - You'd use the configurations as described in Milvus docs. # milvus_deployment = ... # Placeholder for Milvus service - You'd use the configurations as described in Milvus docs. # milvus_service = ... # If you need to install CRDs or other resources for Milvus to operate, you can use Pulumi to deploy those as well. # milvus_crd = ... # Stack exports pulumi.export('kubeconfig', kubeconfig) pulumi.export('resource_group_name', resource_group.name) pulumi.export('aks_cluster_name', aks_cluster.name)

    In the above program:

    • We create an Azure resource group that will hold our AKS cluster.
    • We provision an AKS cluster with a system-assigned identity and enable RBAC.
    • We extract the kubeconfig file from the provisioned AKS cluster which allows us to communicate with the cluster programmatically.
    • We create a Kubernetes provider instance that is used to communicate with the AKS cluster.
    • We create a Kubernetes namespace dedicated to Milvus services.
    • We provide placeholders where you would define the Kubernetes resources needed by Milvus. These will be created based on the YAML files provided by Milvus or customized according to your needs.
    • We export the kubeconfig file and names of the created resources which can be useful if you want to interact with the AKS cluster using kubectl or other tools.

    Note that the actual Milvus deployment (marked as TODO in the code) requires specific details that are beyond the scope of this example. You will need to replace the placeholders with actual Pulumi Kubernetes resource definitions that correspond to Milvus's YAML configurations.

    Remember, this is a basic setup. Depending on your requirements, the creation of the AKS cluster and the Milvus deployment may involve additional steps like configuring persistent storage, setting up network policies, etc. Be sure to consult the Milvus documentation and customize the Kubernetes resource definitions as needed.