1. Scalable AI Workload Management using GitLab Runners on Kubernetes


    Creating a scalable AI workload management system using GitLab Runners on Kubernetes involves a few key components:

    1. Kubernetes Cluster: The first step is setting up a Kubernetes cluster where your CI/CD workloads will run. You can use a managed Kubernetes service like Amazon EKS, Google GKE, or Azure AKS, or you can set up your own Kubernetes cluster.

    2. GitLab Runner: GitLab Runners are agents that run your build jobs and send the results back to GitLab. For Kubernetes, you can install a GitLab Runner inside the cluster, which will listen for jobs from GitLab and execute them within the cluster.

    3. Auto-scaling: To handle varying amounts of workload, you want to set up auto-scaling. For Kubernetes, this typically means using a Horizontal Pod Autoscaler (HPA) which will automatically scale the number of GitLab Runner pods based on the current load.

    Using the Pulumi resources in our program, here's what each will achieve:

    • gitlab.Runner: This resource is used to register a new Runner on your GitLab instance. You need to provide a registration token from your GitLab instance so that the Runner can authenticate and communicate with GitLab.

    • kubernetes.autoscaling/v2beta1.HorizontalPodAutoscaler: This Kubernetes resource is used to set up HPA for your GitLab Runner deployment. This ensures that the number of Runner pods can scale up or down automatically based on the CPU or memory usage.

    Here's the Pulumi program that sets up a scalable AI workload management system with GitLab Runners on a Kubernetes cluster:

    import pulumi import pulumi_kubernetes as k8s import pulumi_gitlab as gitlab # Config values for creating a GitLab Runner gitlab_registration_token = 'YOUR_GITLAB_REGISTRATION_TOKEN' runner_name = 'gitlab-runner' # Create a Kubernetes Namespace for GitLab Runner gitlab_namespace = k8s.core.v1.Namespace('gitlab-runner-namespace', metadata={ 'name': 'gitlab-runners', }) # Register a GitLab Runner gl_runner = gitlab.Runner('gitlab-runner', token=gitlab_registration_token, description='Kubernetes Runner', locked=False, run_untagged=True, active=True, tag_list=[ "kubernetes", "ai-workloads", ], executor='kubernetes', metadata={ 'namespace': gitlab_namespace.metadata['name'], }) # Deploy GitLab Runner into Kubernetes runner_deployment = k8s.apps.v1.Deployment('gitlab-runner-deployment', metadata={ 'namespace': gitlab_namespace.metadata['name'], }, spec={ 'selector': { 'matchLabels': { 'app': 'gitlab-runner', }, }, 'replicas': 1, # Start with 1 replica, scaling will be handled by HPA 'template': { 'metadata': { 'labels': { 'app': 'gitlab-runner', }, }, 'spec': { 'containers': [{ 'name': 'gitlab-runner', 'image': 'gitlab/gitlab-runner:latest', }], }, }, }) # Setup auto-scaling with Horizontal Pod Autoscaler runner_hpa = k8s.autoscaling.v2beta1.HorizontalPodAutoscaler('gitlab-runner-hpa', metadata={ 'namespace': gitlab_namespace.metadata['name'], }, spec={ 'scale_target_ref': { 'api_version': 'apps/v1', 'kind': 'Deployment', 'name': runner_deployment.metadata['name'], }, 'min_replicas': 1, 'max_replicas': 10, 'metrics': [{ 'type': 'Resource', 'resource': { 'name': 'cpu', 'target': { 'type': 'Utilization', 'average_utilization': 50, # Scale up when CPU utilization is over 50% }, }, }], }) # Export the namespace in which the runner is deployed pulumi.export('gitlab_runner_namespace', gitlab_namespace.metadata['name'])

    Make sure to replace YOUR_GITLAB_REGISTRATION_TOKEN with your actual GitLab registration token.

    This program performs the following actions:

    • Sets up a new Kubernetes namespace dedicated to GitLab Runners.
    • Registers a new Runner with your GitLab instance.
    • Deploys the Runner into the Kubernetes cluster with a Deployment resource.
    • Configures an auto-scaler using Horizontal Pod Autoscaler to adjust the number of Runner pods based on CPU utilization.

    Remember to install Pulumi's GitLab and Kubernetes SDKs in your environment with:

    pip install pulumi_gitlab pulumi_kubernetes

    And set up your Pulumi stack with the appropriate Kubernetes and GitLab provider configurations so that Pulumi can authenticate and manage resources in both systems.