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Difficulty: HardPlanning Google Kubernetes Engine (GKE) Cluster Architectures

An enterprise IoT solutions provider is designing a Google Kubernetes Engine (GKE) cluster architecture to host two distinct workloads. The first workload is a specialized edge telemetry receiver that requires custom Linux kernel parameters (sysctl settings) configured directly on the underlying node OS. The second workload is a stateless, fault-tolerant data transformation pipeline that processes incoming message queues and must run at the lowest possible infrastructure cost. The operations team aims to minimize management complexity while meeting all technical requirements. Which cluster architecture recommendation best fulfills these requirements?

  1. Deploy a single GKE Standard cluster. Create one node pool with standard Compute Engine instances for the edge telemetry workload to support custom kernel parameters, and create a separate node pool utilizing Spot VMs for the stateless data transformation pipeline.Answer
  2. B
    Deploy a single GKE Autopilot cluster for both workloads, configuring pod security settings to allow the edge telemetry workload to apply sysctl kernel modifications at runtime.
  3. C
    Deploy a GKE Standard cluster configured with a single node pool of Spot VMs to host both the edge telemetry receiver and the data transformation pipeline.
  4. D
    Deploy a GKE Standard cluster using standard instances, and configure the Horizontal Pod Autoscaler (HPA) to provision new Compute Engine nodes whenever worker node CPU usage exceeds limits.

Answer

Deploy a single GKE Standard cluster with a standard node pool for the telemetry receiver and a Spot VM node pool for the stateless transformation pipeline.
The solution correctly identifies that custom Linux sysctl kernel configurations necessitate GKE Standard because GKE Autopilot restricts host OS kernel modifications. Additionally, using a dedicated Spot VM node pool for the stateless transformation pipeline optimizes costs without risking the stability of the telemetry receiver.

Step-by-Step Solution

1
Analyze the operational boundary between GKE Autopilot and GKE Standard.
GKE Autopilot manages the underlying infrastructure and restricts node-level OS modifications, including custom sysctl parameters. Therefore, GKE Standard is required for the telemetry receiver workload.
GKE Autopilot enforces strict security posture and node management boundaries that prevent custom host OS kernel configuration.
2
Evaluate node pool cost-optimization strategies for the stateless workload.
Spot VMs provide significant cost savings (up to 60-91% off standard pricing) and are ideal for fault-tolerant, stateless batch workloads that can handle instance preemptions.
Segmenting workloads into separate node pools allows tailored instance selection and cost optimization per workload profile.
3
Synthesize the cluster architecture design.
A GKE Standard cluster with two dedicated node pools (Standard VMs for telemetry; Spot VMs for stateless processing) satisfies technical and budget constraints.
This setup maintains cluster operational efficiency while respecting underlying node OS customization and fault tolerance boundaries.

Key Concept

Planning GKE Cluster Architectures with Node Pool Segmentation and Operating Model Choices
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Topics

Planning Google Kubernetes Engine (GKE) Cluster Architectures

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