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To verify and debug the MachineDeployment Resource in the Cluster API Provider for Tinkerbell (CAPT), which manages groups of machines (nodes) in your Kubernetes cluster, you can follow these steps:

1. Verify the MachineDeployment Resource Creation

The first step is to ensure that the MachineDeployment resource has been created correctly and is in the desired state.

Check MachineDeployment Resource Status:

Use kubectl to check the status of the MachineDeployment resource:

kubectl get machinedeployments -A
  • Expected Output: You should see the MachineDeployment resources listed with their associated namespaces. The READY column should show the number of ready replicas compared to the desired number, indicating that the deployment is in a healthy state.

Describe the MachineDeployment Resource:

For more details, you can describe the MachineDeployment resource:

kubectl describe machinedeployment <machinedeployment-name> -n <namespace>
  • Expected Output: This command provides detailed information about the MachineDeployment resource, including its current status, conditions, events, and any errors or warnings.

2. Check Associated Machines

The MachineDeployment resource manages a set of Machine resources. Ensure that these Machines are being created and managed correctly.

Check Machines Managed by MachineDeployment:

kubectl get machines -l cluster.x-k8s.io/deployment-name=<machinedeployment-name> -n <namespace>
  • Expected Output: This command lists all Machines associated with the MachineDeployment. These Machines should be in a Running or Provisioned state.

Describe the Machines:

For more detailed debugging, describe one of the Machines:

kubectl describe machine <machine-name> -n <namespace>
  • Expected Output: Look for conditions, events, or error messages that might indicate issues with the Machines. The status should reflect that the Machines are in a healthy state and have been provisioned correctly.

3. Check Infrastructure-Specific Resources

The MachineDeployment interacts with infrastructure-specific resources like TinkerbellMachineTemplate to define the configuration of the Machines.

Check TinkerbellMachineTemplate:

kubectl get tinkerbellmachinetemplates -A
  • Expected Output: The TinkerbellMachineTemplate associated with your MachineDeployment should be listed and in a Ready state.

Describe the TinkerbellMachineTemplate:

kubectl describe tinkerbellmachinetemplate <template-name> -n <namespace>
  • Expected Output: This command provides detailed information about the template, ensuring that the correct settings (e.g., hardware profile, OS image) are applied to the Machines created by the MachineDeployment.

4. Verify Replicas and Scaling

MachineDeployment resources are responsible for managing the number of replicas (i.e., Machines) in your deployment. Ensure that the desired number of replicas is being maintained.

Check Replica Status:

kubectl get machinedeployments -A
  • Expected Output: The REPLICAS, READY, and UPDATED columns should show that the desired number of replicas is being maintained. For example, if REPLICAS is 3, READY should also be 3.

Scale the MachineDeployment:

You can test scaling by adjusting the number of replicas:

kubectl scale machinedeployment <machinedeployment-name> --replicas=<desired-number> -n <namespace>
  • Expected Output: The MachineDeployment should create or delete Machines to match the desired replica count. Verify that the number of Machines corresponds to the new replica count.

5. Check Events in the Namespace

Kubernetes events can provide insights into what might be going wrong with the MachineDeployment resource or its associated components.

List Events in the Namespace:

kubectl get events -n <namespace> --sort-by='.metadata.creationTimestamp'
  • Expected Output: Review any warning or error events that might indicate problems with the MachineDeployment resource, such as failed Machine creation, scaling issues, or errors from the Tinkerbell infrastructure.

6. Verify Node Registration

Ensure that the Machines created by the MachineDeployment are successfully registering as nodes in the Kubernetes cluster.

Check Node Status:

kubectl get nodes
  • Expected Output: The nodes corresponding to the Machines in your MachineDeployment should be listed in the Kubernetes cluster, with a status of Ready.

Describe Nodes:

If a node is not Ready or is missing, describe the node for more information:

kubectl describe node <node-name>
  • Expected Output: This output will provide details on why the node might not be Ready, such as issues with the kubelet, network configuration, or connectivity to the control plane.

7. Check Logs for CAPT Controller

If there are issues with the MachineDeployment resource, checking the logs of the CAPT controller can provide additional insights.

Check Logs for CAPT Controller:

kubectl logs -n capt-system <pod-name>

Replace <pod-name> with the actual pod name of the CAPT controller managing the MachineDeployment resource.

  • Expected Output: The logs should detail any errors or issues encountered by the controller when managing the MachineDeployment resource, including interactions with Tinkerbell or Kubernetes API.

8. Verify Control Plane Interaction (If Applicable)

If the MachineDeployment is creating control plane nodes (through KubeadmControlPlane), ensure that these nodes are correctly integrated into the cluster.

Check KubeadmControlPlane Status:

kubectl get kubeadmcontrolplanes -A
  • Expected Output: The control plane should be listed with a status indicating Ready. If the MachineDeployment is responsible for creating control plane nodes, ensure they are listed and healthy.

9. Advanced Debugging with Increased Verbosity

If you are still having trouble identifying the issue, you can increase the verbosity of the CAPT controller to gather more detailed logs:

  1. Edit the Deployment:
kubectl edit deployment capt-controller-manager -n capt-system
  1. Add Verbosity Flag:

Add --v=5 or --v=10 to the command section to enable more detailed logging.

  1. Check Logs Again:
kubectl logs -n capt-system <pod-name>

10. Interact with Tinkerbell via Tink CLI (Optional)

If you have direct access to the Tink CLI, you can interact with Tinkerbell resources directly to verify that the MachineDeployment is being provisioned as expected:

tink hardware list
tink workflow list
  • Expected Output: The hardware and workflow related to the Machines in the MachineDeployment should be listed and should indicate whether the provisioning tasks have succeeded.

Conclusion

By following these steps, you can systematically verify and debug the MachineDeployment resource and its interactions with other components in the Cluster API Provider for Tinkerbell. This process ensures that your MachineDeployment is correctly creating and managing machines (nodes) in your Kubernetes cluster, allowing for reliable operation and scaling on bare-metal infrastructure.ovisioned, managed, and integrated into the cluster, allowing for reliable operation on bare-metal infrastructure.