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Difficulty: MediumPlanning Compute Engine Resources and Machine Types

A financial technology company needs to host a continuous, mission-critical risk assessment service on Google Compute Engine. Benchmarking indicates that the application requires precisely 6 vCPUs and 45 GB of RAM. The service operates 24/7, requires constant resource availability, and cannot tolerate unexpected VM terminations or preemption. Which Compute Engine machine configuration strategy should you recommend to minimize monthly infrastructure costs while meeting these exact resource specifications?

  1. Provision a VM instance using a Custom Machine Type configured with 6 vCPUs and 45 GB of memory, and purchase a 1-year or 3-year Committed Use Discount for the required capacity.Answer
  2. B
    Provision Spot VM instances configured with 6 vCPUs and 45 GB of memory to leverage up to 60-91% discounts off standard compute pricing.
  3. C
    Provision a predefined n2-standard-8 instance (8 vCPUs, 32 GB RAM) and rely on automatic Sustained Use Discounts to optimize monthly spending.
  4. D
    Deploy the application workload using Cloud Functions with maximum memory allocation to completely eliminate VM instance management overhead.

Answer

Provisioning a VM instance using a Custom Machine Type configured with 6 vCPUs and 45 GB of memory combined with a Committed Use Discount.
Custom Machine Types allow tailored vCPU and memory configurations (6 vCPUs and 45 GB RAM) to match non-standard workload specifications without paying for unneeded hardware resources. Combining Custom Machine Types with Committed Use Discounts (CUDs) provides the highest cost optimization for steady, non-interruptible 24/7 production workloads.

Step-by-Step Solution

1
Analyze workload resource requirements and SLA requirements.
Workload needs non-standard core/memory ratio (6 vCPUs, 45 GB RAM) and continuous 24/7 availability with zero tolerance for preemption.
Standard machine families (e.g., n2-standard-8 with 8 vCPUs / 32 GB RAM or n2-standard-16 with 16 vCPUs / 64 GB RAM) either under-provision memory or over-provision vCPUs.
2
Select appropriate Compute Engine machine type tailoring mechanism.
Use Custom Machine Types to specify exact vCPU count (6) and memory capacity (45 GB).
Custom Machine Types eliminate waste by allowing tailored vCPU and RAM provisioning when workload ratios do not align with predefined types.
3
Apply the optimal Google Cloud pricing discount model for steady-state workloads.
Purchase Committed Use Discounts (CUDs) for the predictable 24/7 compute footprint.
Committed Use Discounts offer maximum guaranteed savings (up to 57-70%) for steady production capacity without risking workload preemption.

Key Concept

Compute Engine Custom Machine Types and Committed Use Discounts (CUDs)
Estimated Time:1m 30s
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Topics

Planning Compute Engine Resources and Machine Types

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