1. Kubernetes Cluster Health Monitoring with AWS Node Problem Detector


    To monitor the health of a Kubernetes cluster using AWS with Node Problem Detector, you can deploy the Node Problem Detector as a DaemonSet in your Kubernetes cluster. The Node Problem Detector is a project developed by Kubernetes that aims to surface node problems that either affect node conditions, or are visible to the kernel. It is designed to work with a variety of log monitors and tools and can be extended with custom plugins.

    In this program, we will use Pulumi to deploy a Node Problem Detector DaemonSet into an Amazon Elastic Kubernetes Service (EKS) cluster. Here's how you can accomplish this:

    1. Set up an EKS cluster: Use the aws.eks.Cluster class to create an EKS cluster. This serves as the environment where your Kubernetes resources will run.
    2. Define the Node Problem Detector DaemonSet: Kubernetes resources such as DaemonSets can be defined using pulumi_kubernetes.apps.v1.DaemonSet. The Node Problem Detector will run as a DaemonSet, meaning it will run on every node in the cluster.
    3. Deploy the Node Problem Detector DaemonSet: Use Pulumi's deployment capabilities to deploy the Node Problem Detector to your EKS cluster.

    The following program deploys an EKS cluster and the Node Problem Detector DaemonSet:

    import pulumi import pulumi_aws as aws import pulumi_kubernetes as kubernetes from pulumi_aws import eks # Step 1: Create an EKS cluster eks_cluster = eks.Cluster("eksCluster", region="us-west-2", instance_type="t2.medium") # Step 2: Use the EKS cluster's kubeconfig to interact with the cluster kubeconfig = eks_cluster.kubeconfig.apply(lambda kc: kc) # Step 3: Create a Kubernetes provider to deploy the Node Problem Detector k8s_provider = kubernetes.Provider("k8sProvider", kubeconfig=kubeconfig) # Step 4: Define the Node Problem Detector DaemonSet node_problem_detector_daemonset = kubernetes.apps.v1.DaemonSet("nodeProblemDetector", metadata=kubernetes.meta.v1.ObjectMetaArgs( name="node-problem-detector", namespace="kube-system", # Node Problem Detector is typically deployed in the kube-system namespace ), spec=kubernetes.apps.v1.DaemonSetSpecArgs( selector=kubernetes.meta.v1.LabelSelectorArgs( match_labels={"name": "node-problem-detector"} ), template=kubernetes.core.v1.PodTemplateSpecArgs( metadata=kubernetes.meta.v1.ObjectMetaArgs( labels={"name": "node-problem-detector"} ), spec=kubernetes.core.v1.PodSpecArgs( containers=[kubernetes.core.v1.ContainerArgs( name="node-problem-detector", image="k8s.gcr.io/node-problem-detector/node-problem-detector:v0.8.8", resources=kubernetes.core.v1.ResourceRequirementsArgs( limits={"cpu": "200m", "memory": "100Mi"}, requests={"cpu": "200m", "memory": "100Mi"} ), )], ), ), ), opts=pulumi.ResourceOptions(provider=k8s_provider)) # Step 5: Export the cluster name and kubeconfig pulumi.export("cluster_name", eks_cluster.name) pulumi.export("kubeconfig", eks_cluster.kubeconfig)

    This program does the following:

    • Defines an EKS cluster called eksCluster which will be created in the us-west-2 region using t2.medium instance types.
    • Creates a Provider called k8sProvider which allows Pulumi to communicate with the Kubernetes cluster using the kubeconfig.
    • Specifies a DaemonSet for the Node Problem Detector to ensure it runs on all nodes within the cluster.
    • Assigns the node-problem-detector DaemonSet to the kube-system namespace.
    • Uses the node-problem-detector container image from the official Google Container Registry.
    • Exports the cluster_name and kubeconfig as outputs for you to access your cluster outside of Pulumi.

    Make sure to follow the directions to install Pulumi CLI, set up your AWS credentials, and install kubectl if you haven't done that already. To deploy this program, save it as a Python file, and run pulumi up from within the directory containing your file. Pulumi will provision the necessary resources and deploy the Node Problem Detector DaemonSet to your EKS cluster.