Your organization runs a high-throughput data processing and web application architecture on Google Kubernetes Engine (GKE). During off-peak hours, workload traffic drops substantially; however, FinOps reports indicate that GKE compute costs remain high because underutilized nodes in standard on-demand node pools fail to scale down. Your investigation reveals the following workload characteristics: The stateless web services and batch workers are fault-tolerant and can easily handle node preemptions and brief interruptions. Certain long-lived, non-restartable utility pods and pods using local temporary storage are scattered across standard nodes, preventing GKE Cluster Autoscaler (CA) from draining and deleting idle instances. Pods lack clear lifecycle eviction configurations and autoscaling policies. Which strategy should you implement to optimize workload lifecycle management and minimize idle resource costs?

Gke Cluster Autoscaler Spot Eviction Optimization | Professional Cloud DevOps Engineer

Gke Cluster Autoscaler Spot Eviction Optimization

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Your organization runs a high-throughput data processing and web application architecture on Google Kubernetes Engine (GKE). During off-peak hours, workload traffic drops substantially; however, FinOps reports indicate that GKE compute costs remain high because underutilized nodes in standard on-demand node pools fail to scale down.

Your investigation reveals the following workload characteristics:

The stateless web services and batch workers are fault-tolerant and can easily handle node preemptions and brief interruptions.
Certain long-lived, non-restartable utility pods and pods using local temporary storage are scattered across standard nodes, preventing GKE Cluster Autoscaler (CA) from draining and deleting idle instances.
Pods lack clear lifecycle eviction configurations and autoscaling policies.

Which strategy should you implement to optimize workload lifecycle management and minimize idle resource costs?

Annotate all pods with "cluster-autoscaler.kubernetes.io/safe-to-evict": "false" and configure Cloud Run request-based billing for all batch jobs.

Provision a dedicated Spot VM node pool for the fault-tolerant workloads, isolate non-restartable pods in a separate node pool, and apply the "cluster-autoscaler.kubernetes.io/safe-to-evict": "true" annotation to restartable local-storage pods.

Disable Cluster Autoscaler, set all node pools to manual node allocation with oversized high-memory instances, and eliminate pod resource requests.

Configure both Horizontal Pod Autoscaler (HPA) and Vertical Pod Autoscaler (VPA) simultaneously on CPU metrics for all workloads, and remove all Pod Disruption Budgets (PDBs).

Professional Cloud DevOps Engineer

Gke Cluster Autoscaler Spot Eviction Optimization

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