Design GKE AI workloads so a reclaimed Spot node costs you a recoverable amount of work—not the entire run. That means persisting progress outside the node, making retries safe, and keeping enough non-Spot capacity available when a job must continue. A Kubernetes controller can recreate a Pod, but it cannot restore progress that existed only in the terminated process.
What happens when GKE reclaims Spot capacity?
Spot capacity is interruptible, not reserved. In a Standard cluster, Spot VMs are Compute Engine instances in node pools; in Autopilot, you request Spot Pods and Autopilot manages the Spot-backed capacity. Both modes can be interrupted, but their documented shutdown windows differ.
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| GKE mode | Documented shutdown behavior | What to design for |
|---|---|---|
| Standard cluster with Spot VMs | Google Cloud documents a default 30-second graceful termination period after a preemption notice. See GKE Spot VM concepts. | Treat 30 seconds as platform behavior, not a guarantee that your application can use every second to finish work. |
| Autopilot Spot Pods | A preempted Pod can request a maximum 15-second grace period, granted on a best-effort basis. Google documents that the Pod receives SIGTERM and should shut down during its grace period. See GKE Autopilot Spot Pods. | Make shutdown fast and safe, but rely on persisted progress for recovery rather than expecting shutdown to complete a long task. |
Neither window is a promise that a training step, inference request, or batch unit will finish before termination. Google also warns that data on Spot nodes—including attached Local SSD data—is deleted when the instance is preempted. A managed workload controller may replace a Pod, but replacement does not recover its in-memory state or files on ephemeral node storage. See Google Cloud’s GKE Spot VM guidance.
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Persist durable state away from the Spot node
Store checkpoints, job metadata, and completed-work records in an external service or persistent storage with a recovery model suited to the workload. Do not use node-local files as the sole copy of a checkpoint or result. The right storage choice depends on checkpoint size, write frequency, consistency needs, and how the application resumes; Spot documentation establishes the node-data loss risk, not a universal storage design.
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Checkpoint according to the cost of lost work
For training and long-running pipelines, choose a checkpoint interval by balancing the cost of recomputing work against the overhead of writing checkpoints. There is no universal interval: a frequent checkpoint reduces the possible replay window but consumes resources and can affect throughput. Make checkpoints usable after an abrupt process end; graceful shutdown may not leave enough time to write one.
Make retries idempotent
Record which work units have completed durably, and make it safe for a replacement Pod to retry a unit whose completion is uncertain. For example, a pipeline can commit an output and its completion record together, or assign work using stable identifiers so a retry can detect an already-finished unit. This is application-level design advice: Pod recreation does not itself prevent duplicate work or restore progress.
Use termination as an opportunity, not the recovery plan
On SIGTERM, stop accepting new work, finish or safely abandon in-flight work, flush essential state, and exit promptly. Keep the handler bounded by the usable grace period. A checkpoint that is still being written when the process is killed is not a recovery mechanism; resumable computation and durable external state must handle that case.
How should you place workloads across Spot and standard capacity?
Google recommends Spot for fault-tolerant, stateless, or batch workloads. If a workload must proceed even when Spot capacity is unavailable, Google recommends a mix of Spot and standard node pools. See GKE guidance for running workloads with Spot VMs.
- Interruption tolerance: Can the workload resume or be recreated without compromising correctness?
- Recovery cost: How much computation or user work is lost if a process ends before its next durable checkpoint?
- Capacity assurance: Must the job continue when Spot capacity cannot be provisioned? Retain standard capacity options when the answer is yes.
- State handling: Does durable progress live outside ephemeral node data?
- Shutdown behavior: Can the process react to termination promptly within the applicable, best-effort window?
- Operating mode: Is this a Standard Spot node pool or an Autopilot Spot Pod? The configuration model and documented grace period differ.
Use taints and tolerations to keep critical Pods off Spot pools when their interruption tolerance does not fit Spot capacity. GKE’s Spot VM documentation describes the Spot taint pattern and scheduling controls; follow the current instructions for your cluster version rather than copying a configuration without checking its applicability. See the GKE Spot VM setup guidance.
Do not assume that a StatefulSet is safe on Spot simply because it uses persistent volumes. Google advises testing that stateful workloads can terminate gracefully within 25 seconds to reduce the risk of persistent-volume corruption. Treat that as a test target in Google’s guidance, not proof that every workload or storage configuration is safe. See GKE Spot VM concepts.
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Can a PodDisruptionBudget stop a Spot eviction?
No. A PodDisruptionBudget (PDB) limits tolerated voluntary disruptions; it does not prevent an involuntary infrastructure reclamation. Google’s preemptible VM guidance explicitly says that involuntary reclamation is not covered by PDB protections. PDBs can still help protect availability during supported voluntary disruptions such as node upgrades or maintenance. See GKE preemptible VM guidance and GKE workload disruption readiness.
Readiness probes serve a different purpose: they inform health and routing decisions. They do not save process memory, preserve local files, or prevent a Spot reclaim. Use readiness alongside correct shutdown handling and externalized durable state, not as an eviction shield.
How can you tell whether a node was preempted?
Expected Spot or preemptible preemption may appear as a node briefly entering NotReady. For the underlying VM, Cloud Audit Logs can show the compute.instances.preempted event. GKE troubleshooting guidance says to investigate other causes if a node remains NotReady for more than 10 minutes. See GKE’s NotReady troubleshooting guide.
Keep infrastructure preemption distinct from autoscaler placement. GKE’s cluster autoscaler can favor less expensive Spot pools when workload constraints and available resources allow, making Pods on Spot more likely to be evicted. That scheduling choice is separate from Compute Engine reclaiming a Spot VM. See GKE cluster autoscaling.
What changes if you still use preemptible VMs?
Preemptible VMs are the legacy comparison, not the preferred starting point for a new fault-tolerant design; Google recommends the corresponding newer Spot VM or Spot Pod options. The documented preemption notice precedes shutdown, and the 30-second window is divided into best-effort time for non-system Pods followed by critical system Pods. Reclamation remains involuntary and outside PDB protection. See GKE’s preemptible VM instructions.
Quick Recap
A practical recovery checklist
- Classify the workload: decide whether it can be interrupted, how much work it may lose, and whether it needs guaranteed continuation.
- Choose the GKE mode: identify whether you are using Standard Spot node pools or Autopilot Spot Pods, then apply the matching configuration and shutdown expectations from the relevant GKE documentation.
- Move recovery state off-node: ensure checkpoints and completion records survive node reclamation.
- Test interruption paths: verify that the process responds to SIGTERM, stops or drains work safely, and can resume from its last durable checkpoint after termination.
- Provide a capacity fallback when needed: use standard capacity options for jobs that must continue when Spot capacity is unavailable.
- Monitor and diagnose: correlate brief NotReady states and preemption audit events with application recovery behavior; investigate prolonged NotReady states separately.
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