/gke-compute-classes

ComputeClass: Gotchas, CUDs & Constraints

Common Traps

• AnyBestEffort Reservation: Consumes On-Demand capacity at the GCE level before evaluating your remaining ComputeClass priorities. Avoid if you want to fall back to Spot or cheaper families; use AnyThenFail (GKE 1.36.0-gke.3204000+) or Specific affinity.
• Reservations are Zonal: Pin zones via reservations.specific[].zones. location.zones (per-priority or priorityDefaults.location) collides with Specific — omit it; a policy-only location.locationPolicy: BALANCED is fine.
• Disk Generation:
  • Gen 4 (n4, c4): Requires Hyperdisk.
  • Gen 2 (n2, c2): Requires Persistent Disk.
  • Rule: For stateful PV workloads, do NOT mix Gen 2 and Gen 4 priorities (fallback attach fails -> ContainerCreating trap).
  • Exception (GKE 1.35.3-gke.1290000+): back data PVs with the built-in dynamic-rwo StorageClass (type: dynamic + use-allowed-disk-topology: "true"). The autoscaler reads disk requirements and scales up only compatible nodes, so mixing generations in priorities[] becomes safe. See Asset: dynamic-rwo-storageclass.yaml.
  • Caveat: dynamic-rwo only governs newly provisioned PVs. An existing PV already created as a fixed PD or Hyperdisk does not retroactively become flexible — migrate its data onto a dynamic-rwo-backed volume (snapshot/restore or app/DB-level copy; PD↔Hyperdisk is not an in-place conversion).
  • Reference: Asset: postgres-primary-compute-class.yaml

Provisioning Nuance

• DWS FlexStart: Queued (~3 min). maxRunDurationSeconds doesn't help obtainability.
• ComputeClass ≠ Full Node API: node pool auto-creation doesn't support every gcloud node-pools create flag. If missing, use a Manual Pool bound to the ComputeClass.

CUDs vs. Reservations

• Committed Use Discounts (CUDs):
  • Automatic Consumption: GKE cluster autoscaler automatically consumes CUDs based on the machine family of the node provisioned. If you have an n4 CUD, provisioning an n4 VM automatically consumes the discount up to exhaustion.
  • No Configuration Required: A ComputeClass does not need to be specifically configured to consume CUDs. Consumption is implicit.
  • Flexible CUDs (FlexCUDs): Portable across most families (C3, N2, N4). The discount follows whichever family the ComputeClass provisions for the On-Demand floor.
• Reservations:
  • Explicit Configuration Required: Unlike CUDs, capacity reservations are not automatically consumed. They must be explicitly configured and targeted via the Node Pool API (for manual pools) or within the ComputeClass reservations block (for node pool auto-creation).

System Configuration Allowlist

GKE allows only specific sysctls and kubeletConfig fields.

• Check CRD: kubectl describe crd computeclasses.cloud.google.com for the authoritative allowlist.
• Symptoms: Unsupported keys show up in status.conditions.
• Version Gating: Many fields (e.g. singleProcessOOMKill) require 1.33+ or 1.34+.

Service Mesh / Networking Nuances

• Nodes provisioned by ComputeClasses (especially via node pool auto-creation) must be compatible with existing network policies or service mesh (e.g., Anthos/Istio) sidecar requirements.
• Ensure any required taints or labels for mesh injection or network traffic routing are included in the nodePoolConfig. An intentional dedication taint is valid here; the only redundant one is cloud.google.com/compute-class — node pool auto-creation applies and auto-tolerates it, so don't re-add it. Manual pools, by contrast, DO require it as label + taint to bind to the ComputeClass. Note: a nodePoolConfig.taints key cannot contain the reserved kubernetes.io substring (GKE Warden rejects it).