GCP Professional Cloud Architect Practice Question
As the new cloud architect for a media company, you discover two Compute Engine N2-standard-32 VMs that run 24Ă—7 in separate regions to support stateful analytics services. The services cannot tolerate restarts or performance degradation. The CFO has asked you to reduce compute costs quickly with as little engineering effort as possible and without introducing availability risk. Which Google Cloud cost-saving mechanism best satisfies these requirements?
Rely on sustained use discounts that are automatically applied after the VMs run most of the month.
Replace the two large VMs with an autoscaled managed instance group of smaller E2 VMs that can scale to zero when idle.
Purchase one-year committed use discounts for the required vCPU and memory in each region.
Convert the virtual machines to Spot VMs to obtain steep discounts when capacity is available.
Committed use discounts (CUDs) let you purchase a one- or three-year commitment for a specific amount of vCPU and memory in each region. The commitment applies automatically to existing on-demand VMs, so no code changes, re-deployments, or restarts are required. For steady, always-on workloads, a one-year CUD can provide roughly 35 % savings-greater than the automatic sustained-use discount and without the pre-emption risk of Spot VMs. Re-architecting into an autoscaled group could reduce costs but demands considerably more engineering effort and operational change. Therefore, purchasing regional one-year CUDs for the current VM footprint is the most effective, low-effort option that maintains performance and availability.
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What are Committed Use Discounts (CUDs) in Google Cloud?
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Why are Spot VMs not suitable for stateful workloads?
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What are committed use discounts (CUDs) in Google Cloud?
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How do sustained use discounts compare to committed use discounts?
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What are the risks of using Spot VMs for cost savings?
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