| name | gke-tpu-dynamic-slices-monitoring |
| description | Monitors, troubleshoots, and manages GKE TPU Dynamic Slices custom resources. Use when checking TPU slice lifecycle states, troubleshooting slice provisioning failures, validating single-slice or multi-slice (JobSet) workload manifests, or safely patching stuck finalizers and disabling the slice controller. Don't use for generic GKE cluster node pool creation or standard non-TPU workload management (use gke-basics or gke-cluster-creation instead). |
| metadata | {"category":"Containers"} |
GKE TPU Dynamic Slices Monitoring & Management
Monitors the status of TPU Slice custom resources, troubleshoots provisioning
failures, validates workload manifests on dynamic slices, and performs cleanups.
Prerequisites
- Cloud Logging enabled for the project.
kubectl and gcloud CLIs configured to access the GKE cluster.
Diagnostic Workflow
Step 0: Context Acquisition & Time Window Definition
Gather project, cluster, and slice context using cluster tools or the following
parameters:
- Project ID:
{project_id} (e.g., my-gcp-project)
- Cluster Name:
{cluster_name} (e.g., tpu-cluster)
- Region/Zone:
{location} (e.g., us-central1-a)
- Slice Name:
{slice_name} (e.g., test-slice)
- Issue Time:
{timestamp} (Optional; default to the last 30 minutes
window [T - 30m] to [T + 30m])
Step 1: Describe the Slice Custom Resource [Low Risk]
When asked to inspect, troubleshoot, or check a slice status, immediately execute kubectl describe slice {slice_name} using available cluster tools to perform the inspection. Parse the resulting Status.Conditions output against the condition table below to diagnose the exact state and provide concrete recommendations.
State & Reason Analysis
Analyze the Status.Conditions (especially Type: Ready and its Reason and
Status):
| Lifecycle State / Reason | Meaning | Recommended Action |
|---|
SliceNotCreated | GKE Slice Controller | Wait a few minutes and |
| : : is initializing the : re-check slice status. : | | |
| : : slice and performing : : | | |
| : : resource checks. : : | | |
SliceCreationFailed | Prerequisites | Verify selected nodes |
| : : validation failed : exist, are unallocated, : | | |
| : : (e.g., selected nodes : and topology matches : | | |
| : : don't exist, nodes are : partition count. : | | |
| : : already used by : : | | |
| : : another slice, or the : : | | |
| : : topology doesn't match : : | | |
| : : the number of : : | | |
| : : partitions). : : | | |
ACTIVATING | GKE is actively | Monitor node |
| : : forming and : provisioning. : |
Provisioning Failure Troubleshooting Checklist
When investigating slice creation or provisioning failures (SliceCreationFailed or FAILED), perform the following verification steps:
- Node Existence & Allocation Check: Verify that the selected TPU nodes exist in the cluster and are not already allocated to another slice (
kubectl get nodes -l cloud.google.com/gke-tpu-slice, kubectl get slice -A).
- Topology Alignment: Confirm that the partition count matches the requested topology dimensions (e.g. topology
2x2 requires 4 nodes).
- Reservation Block Alignment Check: Confirm that all selected TPU nodes belong to the same reservation and reservation block.
Step 2: Verify Workload Specification [Low Risk]
Ensure workload manifests are configured correctly to target the dynamic slice.
1. Single-Slice Workload Requirements
Check that the Pod template contains the following annotations and selectors:
- Annotations:
cloud.google.com/gke-tpu-slice-topology: "{topology}" (e.g.,
"4x4x4")
- NodeSelector:
cloud.google.com/gke-tpu-topology: "{topology}" (e.g., "4x4x4")
cloud.google.com/gke-tpu-accelerator: "{accelerator_type}" (e.g.,
"tpu7x")
cloud.google.com/gke-tpu-slice: "{slice_name}" (e.g., "test-slice")
2. Multi-Slice (JobSet) Workload Requirements
If deploying a multi-slice JobSet, verify:
- JobSet Annotation:
alpha.jobset.sigs.k8s.io/exclusive-topology: cloud.google.com/gke-tpu-slice
- Pod Template Annotations:
cloud.google.com/gke-tpu-slice-topology: "{topology}"
- Pod Template NodeSelector:
cloud.google.com/gke-tpu-topology: "{topology}"
cloud.google.com/gke-tpu-accelerator: "{accelerator_type}"
- Note: Do NOT manually specify
cloud.google.com/gke-tpu-slice in the
nodeSelector; JobSet handles slice assignment automatically.
Resolution & Management Workflow
Resolution 1: Force Delete a Stuck Slice [High Risk]
If a slice is stuck in DEACTIVATING or deletion hangs indefinitely due to stuck finalizers:
-
Identify Cause: Explain that finalizers on the slice resource (metadata.finalizers) are preventing Kubernetes from completing resource deletion.
-
Propose Resolution: Propose removing finalizers from the metadata path (/metadata/finalizers) using a JSON patch operation:
kubectl patch slice {slice_name} --type json -p='[{"op": "remove", "path": "/metadata/finalizers"}]'
-
Provide Warning: Explicitly warn the user that removing finalizers bypasses standard controller dismantling and may leave underlying VM, network, or accelerator resources uncleaned or orphaned.
-
CRITICAL SAFETY MANDATE: The response MUST explicitly ask the user for confirmation (e.g. "Removing finalizers on /metadata/finalizers via JSON patch is a high-risk operation that may leave orphaned resources. Do you confirm you want to apply this patch to slice {slice_name}?") and pause for user confirmation before applying or executing the patch.
Resolution 2: Disable and Clean Up Slice Controller [High Risk]
If dynamic slicing needs to be disabled:
-
Check for existing Slices:
kubectl get slice -A
Ensure all slices are deleted before disabling the controller.
-
Disable Slice Controller via gcloud:
gcloud container clusters update {cluster_name} \
--location={location} \
--no-enable-slice-controller
-
Delete the Slice CRD:
kubectl delete crd slices.accelerator.gke.io
-
Clean up Node Labels: Remove GKE TPU Slice labels from all nodes in the
cluster:
kubectl label nodes --all cloud.google.com/gke-tpu-slice- cloud.google.com/gke-tpu-slice-topology-
- Safety Rule: Propose the exact commands and confirm before executing
disabling or destructive cleanup steps.