A financial software company runs an internal batch calculations service on Google Compute Engine. The application requires exactly 6 vCPUs and 28 GB of memory to process daily data efficienty, but none of the predefined machine types match this resource ratio. The workload runs continuously 24 hours a day, 7 days a week, and cannot tolerate unexpected preemptions or terminations. Which Compute Engine machine configuration and pricing model should you select to minimize operational costs while satisfying all system requirements?
- Provision a Custom Machine Type with 6 vCPUs and 28 GB of memory, and purchase a Committed Use Discount (CUD) for the baseline usage.Cevap
- BProvision a Custom Machine Type with 6 vCPUs and 28 GB of memory using Spot VMs to achieve maximum cost savings.
- CProvision a predefined n2-standard-8 instance type and rely on automatic Sustained Use Discounts (SUD) to optimize compute costs.
- DDeploy the application to Cloud Run with custom container CPU and memory allocations to eliminate virtual machine management.
Cevap
Provision a Custom Machine Type with 6 vCPUs and 28 GB of memory, and purchase a Committed Use Discount (CUD) for the baseline usage.
Configuring a Custom Machine Type allows exact allocation of 6 vCPUs and 28 GB of RAM without paying for unused resources of larger predefined types. Pairing continuous, non-interruptible 24/7 workloads with Committed Use Discounts provides the highest cost savings while guaranteeing instance availability.
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Compute Engine Custom Machine Types and Committed Use Discounts (CUD)
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