A bioinformatics research laboratory is architecting a Google Kubernetes Engine (GKE) cluster for two main workloads:
1. A continuous API service that requires custom sysctl kernel parameters for specialized network socket tuning.
2. A large-scale genomic sequencing batch job that is stateless, highly fault-tolerant, and needs to run at the lowest possible cost.
Which TWO cluster architectural decisions should the team make to satisfy all requirements? (Select TWO.)
- Provision a GKE Standard cluster to allow custom node pool configurations with modified sysctl kernel settings.Answer
- Configure a secondary node pool using Spot VMs to execute the stateless genomic sequencing batch jobs.Answer
- CDeploy a GKE Autopilot cluster to automatically apply custom OS-level sysctl parameters across all managed nodes.
- DRun the primary API service on a Spot VM node pool to minimize infrastructure spend across all workloads.
- EConfigure Horizontal Pod Autoscaler (HPA) to automatically provision additional Compute Engine VM instances during batch processing spikes.
Answer
The team should provision a GKE Standard cluster to enable custom sysctl kernel configurations for the API service, and create a secondary node pool using Spot VMs for the stateless batch processing jobs.
GKE Standard mode allows custom node configurations, which is necessary when applications require specific Linux sysctl kernel modifications. For stateless and fault-tolerant batch workloads, provisioning a dedicated node pool powered by Spot VMs delivers optimal cost reduction while accepting potential node preemptions.
Step-by-Step Solution
Key Concept
GKE Cluster Architecture Selection (Standard vs. Autopilot and Spot VM Integration)