A research institution processes highly sensitive genomic data and uses custom-built, open-source machine learning models. They need a compute environment that offers strong isolation, precise control over resource allocation, and predictable performance for their specialized, security-critical workloads. The institution also wants to minimize operational overhead for managing the underlying infrastructure. Which GKE mode should they choose?
- AGKE Standard with preemptible VMs
- BGKE Standard with custom node pools
- CGKE Standard with sole-tenant nodes
- DGKE Autopilot
Show answer & explanationAnswer & explanation
Correct answer: B. GKE Standard with custom node pools
GKE Standard with custom node pools provides the necessary control over node types, resource allocation, and isolation needed for specialized, security-critical workloads while still benefiting from GKE's orchestration capabilities. Autopilot abstracts away too much control, preemptible VMs are not for predictable performance, and sole-tenant nodes are for extreme isolation needs often with licensing, not the primary solution for 'precise control over resource allocation' in this context.
Why the other options are wrong
- A. GKE Standard with preemptible VMs is for fault-tolerant, batch-like workloads where cost is prioritized over predictable performance, which is not suitable for 'predictable performance' and 'security-critical' data.
- C. GKE Standard with sole-tenant nodes provides dedicated physical servers for extreme isolation, but 'precise control over resource allocation' often refers to selecting specific VM types and configurations, which custom node pools address more directly and cost-effectively than sole-tenant nodes for most specialized workloads.
- D. GKE Autopilot fully manages node infrastructure, abstracting away control over node types and resource allocation, which contradicts the need for 'precise control'.
GKE Standard Node Pools
In GKE Standard mode, node pools allow users to define groups of nodes with specific machine types, disk sizes, and other configurations, providing granular control over the underlying compute resources.
- User-managed nodes in GKE Standard
- Customizable machine types, GPUs, disks
- Essential for precise resource allocation
- Supports specific hardware requirements
Memory trick: GKE Standard: Fine-Tune Your Nodes, Control Your Destiny.