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Now that Kubeflow is installed, this short demo inspects the cluster to show what components and custom resources were deployed. Use the commands shown below to explore CRDs, namespaces, and namespace-scoped resources so you understand how Kubeflow wires together multiple subsystems.
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CustomResourceDefinitions (CRDs)

Kubeflow installs many CRDs to extend Kubernetes with ML-specific abstractions and to enable dependent projects (Dex, cert-manager, Istio, Knative, Argo, KServe, Katib, Spark operator, etc.). To list them:
Below is representative output from the demo cluster (timestamps removed for readability):
Selected CRDs map to these subsystems:

Namespaces

Kubeflow and its dependencies create several namespaces. List them with:
Example output from the demo cluster:
Quick lookup table for these namespaces:

Inspecting Istio (ingress / mesh)

Istio is generally used to provide ingress (and service mesh) for Kubeflow. To see Istio components:
Representative output (pods, services, deployments):
Note: istio-ingressgateway is typically the entry point for accessing Kubeflow’s UI (it exposes ports 80 and 443 in this example).

The kubeflow namespace (applications & services)

The kubeflow namespace contains the main Kubeflow application components: central dashboard, pipelines UI, Jupyter frontends, notebook controller, KServe (model serving), Katib (hyperparameter tuning), TensorBoard controllers, Spark operator, storage (MinIO / SeaweedFS), metadata service, and more. Inspect resources in the namespace:
Representative pods:
Representative services:
Representative controllers and sets:
What this demonstrates:
  • Kubeflow installs a broad suite of components: UI (centraldashboard, pipelines UI), Jupyter frontends, metadata services, Argo-based pipeline controllers, KServe for model serving, Katib for hyperparameter tuning, Spark operator, storage backends (MinIO, SeaweedFS), and more.
  • These components are managed using Kubernetes primitives: Deployments, ReplicaSets, StatefulSets, Services, ConfigMaps, Secrets, and CRDs where domain-specific resources are required.
You don’t need to memorize every CRD, pod, or service. The important thing is to recognize that Kubeflow brings in multiple subsystems (auth, networking, orchestration, serving, tuning, storage) and extends Kubernetes via CRDs to provide ML-specific abstractions.

Quick checklist — Commands to explore your installation

Closing
  • This demo walked through how to inspect what Kubeflow installed: CRDs, namespaces, Istio resources, and Kubeflow-specific pods/services/deployments. Use the commands above to explore your cluster and map how the pieces are connected.

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