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Difficulty: MediumPlanning Compute Engine Resources and Machine Types

A logistics enterprise is designing its Google Cloud compute strategy for a mission-critical, core database engine running on Google Compute Engine. The database requires continuous 24/7 uptime, stable performance without interruptions, and predictable CPU and memory utilization. The financial operations team requires the most cost-effective pricing model for this long-term workload. Which compute provisioning strategy should you recommend?

  1. Provision standard Compute Engine instances for the database workload and purchase Committed Use Discounts (CUDs) for the baseline resource usage.Answer
  2. B
    Provision Spot Virtual Machines (VMs) with custom machine types to achieve maximum cost savings for the database instances.
  3. C
    Deploy the database workload using Cloud Functions triggered by scheduled HTTP endpoints.
  4. D
    Provision standard VM instances and manually reboot them every 24 hours to continuously trigger maximum Sustained Use Discount tiers.

Answer

Provision standard Compute Engine instances for the database workload and purchase Committed Use Discounts (CUDs) for the baseline resource usage.
The correct answer recommends provisioning standard Compute Engine instances combined with Committed Use Discounts (CUDs). Workloads that run continuously (24/7) with predictable resource demands benefit most from CUDs, which offer substantial cost savings without introducing any risk of preemption or interruption.

Step-by-Step Solution

1
Analyze the workload characteristics
Identified a mission-critical, 24/7 continuous database requiring uninterruptible uptime and predictable resource usage.
Fault tolerance requirements dictate whether Spot/Preemptible instances can be used, while usage predictability dictates discount mechanisms.
2
Evaluate availability constraints against VM pricing models
Eliminated Spot VMs because unexpected preemption breaks mission-critical database SLAs.
Spot VMs are designed strictly for fault-tolerant batch processing and stateless scale-out workloads.
3
Select optimal cost reduction mechanism for steady-state workloads
Selected Committed Use Discounts (CUDs) for 1-year or 3-year resource commitments.
CUDs provide predictable, deep discounts without requiring changes to instance availability or operational restarts.

Key Concept

Selecting Compute Engine Instance Types and Discount Models for Continuous Workloads
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Topics

Planning Compute Engine Resources and Machine Types

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