A cloud engineer needs to configure a Google Kubernetes Engine (GKE) Standard cluster to execute fault-tolerant, stateless batch processing workloads while minimizing compute expenditure. The cluster control plane and core system workloads must remain stable, while the batch jobs should run on low-cost compute resources that can be reclaimed at any time. Which TWO actions should the engineer perform to implement this operational strategy?
- Create a secondary node pool configured with Spot VMs to host the batch processing workloads.Answer
- Add node selectors or taints and tolerations to the batch workload deployment manifest to target the Spot VM node pool.Answer
- CConfigure the GKE control plane master nodes to run on Spot VMs to eliminate baseline cluster management fees.
- DConfigure the Horizontal Pod Autoscaler (HPA) to automatically provision additional Compute Engine virtual machines when batch memory utilization increases.
Answer
To minimize compute costs for fault-tolerant workloads on GKE, the engineer should create a secondary node pool utilizing Spot VMs and configure the batch deployment manifests with node selectors or taints and tolerations to ensure pods are scheduled onto the Spot nodes.
For fault-tolerant, stateless batch workloads, creating a dedicated node pool powered by Spot VMs provides maximum cost efficiency. To ensure batch tasks execute strictly on these nodes and do not disrupt system services, node selectors or taints and tolerations must be defined in the workload deployment specification.
Step-by-Step Solution
Key Concept
Deploying fault-tolerant workloads using GKE Spot VM node pools and Kubernetes pod scheduling