Your company developed an application to deploy on Google Kubernetes Engine. Certain parts of the application are not fault-tolerant and are allowed…

This strategy correctly aligns the infrastructure with the application's requirements while optimizing for cost. Critical, stateful, or long-running workloads that cannot tolerate interruption should be placed on a node pool with standard VMs, which provide high availability. Fault-tolerant, stateless, or batch workloads that can handle preemption are ideal candidates for Spot VMs. Spot VMs offer significant cost savings but can be reclaimed at any time. By creating two distinct node pools and scheduling the appropriate workloads to each, the solution achieves both high availability for critical services and cost-efficiency for non-critical ones.

A. This approach fails to optimize costs because it exclusively uses more expensive standard VMs. A Kubernetes label alone does not enable the use of Spot VMs.

B. This configuration jeopardizes the availability of critical applications by running them on a node pool composed entirely of Spot VMs, which can be preempted at any time.

C. This option incorrectly reverses the deployment logic. It places critical deployments on unstable Spot VMs and fault-tolerant deployments on expensive standard VMs, failing both availability and cost-optimization goals.

1. Google Cloud Documentation

GKE Concepts

"Spot VMs": "Spot VMs are a good fit for running stateless

batch

or fault-tolerant workloads. They are not recommended for workloads that are not fault-tolerant

such as stateful applications." This directly supports placing fault-tolerant workloads on Spot VMs and implies critical workloads should be elsewhere.

2. Google Cloud Documentation

GKE Concepts

"About node pools": "Node pools are a subset of nodes within a cluster that all have the same configuration... For example

you might create a node pool in your cluster with Spot VMs for running fault-tolerant workloads and another node pool with standard VMs for workloads that require higher availability." This describes the exact architecture proposed in the correct answer.

3. Google Cloud Documentation

GKE How-to guides

"Separate workloads in GKE": This guide explains the use of node taints and tolerations to control scheduling. To implement the solution

you would add a taint to the Spot VM node pool (e.g.

cloud.google.com/gke-spot=true:NoSchedule) and add a corresponding toleration only to the fault-tolerant deployments

ensuring they are scheduled there while critical workloads are placed on the standard node pool.