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Zorluk: OrtaOptimizing Business Processes through FinOps and Cloud Cost Management

A multinational pharmaceutical enterprise operates a supply chain web portal running on 20 Compute Engine virtual machines 24/7 with consistent resource utilization. Additionally, the enterprise executes a monthly inventory batch analytics job for 6 hours at the end of each month that requires 500 Compute Engine virtual machines. The FinOps team needs to reduce cloud compute expenses while maintaining system availability and operational efficiency. Which cost optimization strategy should the Cloud Architect recommend?

  1. Purchase Committed Use Discounts (CUDs) to cover the 20 web portal virtual machines, and utilize Spot VMs for the monthly 6-hour batch processing workload.Cevap
  2. B
    Purchase 3-year standard Committed Use Discounts for 520 virtual machines to cover the peak resource consumption of both the web portal and the monthly batch processing job.
  3. C
    Migrate both the web portal backend and batch processing datasets to a multi-region Cloud Spanner cluster to take advantage of integrated baseline billing discounts.
  4. D
    Deploy both the 24/7 web portal and the monthly batch analytics workload onto a new Google Kubernetes Engine (GKE) cluster configured with manual node provisioning.

Cevap

Purchase Committed Use Discounts (CUDs) to cover the 20 web portal virtual machines, and utilize Spot VMs for the monthly 6-hour batch processing workload.
Applying Committed Use Discounts (CUDs) to steady, predictable 24/7 baseline capacity while leveraging Spot VMs for fault-tolerant, short-duration batch processing aligns with FinOps best practices by maximizing discount coverage without paying for idle capacity.

Adım Adım Çözüm

1
Analyze workload predictability and operational duration.
Identify the web portal (20 VMs running 24/7) as steady baseline compute capacity, and the monthly inventory analysis (500 VMs for 6 hours) as a short-duration batch workload.
Effective FinOps strategies separate predictable baseline demand from temporary peak demand.
2
Select the optimal Google Cloud pricing model for each workload tier.
Apply 1-year or 3-year Committed Use Discounts (CUDs) to the 24/7 baseline VMs to lock in lower hourly rates, and use Spot VMs for the batch analytics job.
CUDs require continuous hourly utilization to deliver savings, whereas Spot VMs offer heavy discounts suitable for batch jobs that can tolerate interruption.

Anahtar Kavram

FinOps Compute Optimization Strategy
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Optimizing Business Processes through FinOps and Cloud Cost Management