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gke-tpu

Manage GKE clusters and run TPU workloads on Google Kubernetes Engine. Use this skill when the user wants to: (1) Create or configure a GKE cluster for TPU workloads, (2) Create workload policies for multi-host TPU setups, (3) Create TPU node pools (single-host or multi-host), (4) Create and submit Kubernetes Jobs on TPU nodes, (5) Interact with running pods via kubectl (exec, logs, port-forward), (6) Run services, benchmarks, or tests on GKE TPU pods.

personAuthor: jakexiaohubgithub
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GKE TPU Skill

Manage GKE-based TPU workloads via kubectl. Config-driven via gke.toml in the current working directory (CWD).

Commands

| Command | Description | Reference | |---|---|---| | create | Create TPU pod (single-host) or job (multi-host) | references/create.md | | sync | Sync code + install deps to all containers | references/sync.md | | run | Execute script on multi-process TPU | references/run.md | | status | Check pod/workload status | references/status.md |

Read the relevant reference file for the user's command before executing.

Configuration

Read gke.toml from the current working directory at the start of every command. This keeps configs isolated per worktree/session. Never hardcode project/cluster/zone/bucket. If gke.toml does not exist in CWD, prompt the user to create one.

[gke]
project = "<your-gcp-project>"
cluster = "<your-cluster-name>"
zone = "<your-zone>"

[tpu]
accelerator = "tpu-v6e-slice"   # nodeSelector accelerator label
topology = "4x4"                # TPU topology (determines chip count)
chips_per_node = 4              # google.com/tpu resource per container
machine_type = "ct6e-standard-4t"  # GKE machine type
max_nodes = 4                   # autoscaling max for node pool
reservation = ""                # optional: reservation name for reserved capacity

[workload]
name = "my-workload"
docker_image = "us-docker.pkg.dev/cloud-tpu-images/jax-ai-image/tpu:jax0.8.1-rev1"
service_account = "gcs-account"

[storage]
type = "gcsfuse"                # "gcsfuse" or "pvc"
mount_path = "/inference-models"

# --- gcsfuse-specific (only when type = "gcsfuse") ---
bucket = "inference-model-storage-poc-tpu"
mount_options = "implicit-dirs,file-cache:max-parallel-downloads:256,file-cache:enable-parallel-downloads:true,file-cache:download-chunk-size-mb:128,file-cache:max-size-mb:81920,file-cache:parallel-downloads-per-file:512,metadata-cache:ttl-secs:-1,metadata-cache:stat-cache-max-size-mb:-1,metadata-cache:type-cache-max-size-mb:-1,file-cache:cache-file-for-range-read:true,file-system:kernel-list-cache-ttl-secs:-1,read_ahead_kb=1024"

# --- pvc-specific (only when type = "pvc") ---
# pvc_name = "my-model-pvc"       # name of existing PersistentVolumeClaim
# read_only = false                # mount as read-only (default: false)
# gcsfuse_backed = false           # true if PVC's StorageClass uses GCS Fuse CSI driver
                                   # when true: adds gke-gcsfuse/volumes annotation + gke-gcsfuse-cache volume
                                   # when false: plain PVC mount, no sidecar needed

[repo]
git_url = "https://github.com/sgl-project/sglang-jax.git"
remote_path = "/tmp/sglang-jax"
install_cmd = "pip install -e ."            # run in repo root
# requirements_file = "requirements-tpu.txt"  # optional: extra deps file (relative to repo root)

TPU Topology Reference

See references/tpu-topologies.md for supported topologies (v6e and v7x), machine types, and chips-per-node mappings.

Single-host (1 VM): use Pod. Multi-host (>1 VM): use Indexed Job + headless Service.

Critical Rules

  1. Single vs multi-host: Determine from topology. chips / chips_per_node = hosts. If hosts > 1, must use Job + headless Service.
  2. Storage: Check storage.type:
    • gcsfuse: mount with gke-gcsfuse/volumes: "true" annotation and gke-gcsfuse-cache emptyDir volume.
    • pvc: mount the existing PVC directly. The PVC must already exist in the namespace.
      • If storage.gcsfuse_backed = true: the PVC's StorageClass uses GCS Fuse CSI driver under the hood — still needs gke-gcsfuse/volumes: "true" annotation and gke-gcsfuse-cache emptyDir volume, otherwise mount will fail with "failed to find the sidecar container".
      • If storage.gcsfuse_backed = false (default): plain PVC mount, no gcsfuse annotation or cache volume needed.
  3. Simultaneous launch: For multi-host, jax.distributed.initialize() must run in all pods at the same time.
  4. Same code path: ALL processes must execute the SAME jitted computations.
  5. Docker image must match JAX version in pyproject.toml.
  6. Reservations: If tpu.reservation is set, use --reservation-affinity=specific with fixed node count (no autoscaling).
  7. Multi-host verification: import jax blocks on multi-host TPU. Use /dev/vfio/ for per-pod hardware check, run command for full JAX cluster verification.

Prerequisites

See references/prerequisites.md for gcloud/kubectl install steps.

Troubleshooting

See references/troubleshooting.md for common issues.