An enterprise logistics firm is planning Compute Engine virtual machine specifications for a legacy telemetry parser service. The workload runs continuously 24 hours a day, 7 days a week, and strictly requires 2 vCPUs and 14 GB of memory to run efficiently without waste. Standard machine types provide either too little memory (2 vCPUs with 8 GB) or unnecessary compute (4 vCPUs with 16 GB). Which deployment strategy should the Cloud Engineer recommend to minimize monthly operational costs while meeting these exact workload requirements?
- Provision Compute Engine VMs using Custom Machine Types with 2 vCPUs and 14 GB memory, and purchase Committed Use Discounts (CUDs) for the baseline workload.Cevap
- BProvision Spot VMs configured with Custom Machine Types with 2 vCPUs and 14 GB memory to achieve maximum cost reduction.
- CProvision predefined n1-standard-4 Compute Engine VMs (4 vCPUs, 15 GB RAM) and rely on automatic Sustained Use Discounts (SUDs) for cost reduction.
- DDeploy the legacy parser application onto Cloud Functions with 14 GB memory allocation to run on demand.
Cevap
Provision Compute Engine VMs using Custom Machine Types tailored to 2 vCPUs and 14 GB memory, combined with Committed Use Discounts (CUDs) for steady 24/7 execution.
Configuring Custom Machine Types prevents paying for unused vCPUs when specific memory-to-vCPU ratios are needed, and applying Committed Use Discounts maximizes cost savings for steady-state 24/7 baseline infrastructure.
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Anahtar Kavram
Custom Machine Types & Committed Use Discounts (CUDs) optimization