Professional Cloud DevOps Engineer
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An enterprise organization operates multiple Google Cloud projects attached to a single Cloud Billing account. The infrastructure architecture includes the following workload profiles:
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StudyCertsus-central1).As a DevOps and FinOps engineer, you need to implement a commitment strategy that maximizes cost savings for the predictable baseline, provides flexible coverage for dynamic multi-service compute spend, and prevents commitment underutilization across projects.
Which strategy should you implement?
Rely entirely on automated Sustained Use Discounts (SUDs) across all projects while disabling Committed Use Discounts to avoid financial lock-in and multi-year contractual commitments.
Purchase resource-based Committed Use Discounts (CUDs) for the steady-state N2 baseline in us-central1, purchase spend-based CUDs for variable multi-region and multi-product compute, and enable discount sharing across all projects in the Cloud Billing account.
Purchase resource-based CUDs scoped strictly to individual projects for 100% of all projected peak workloads, and disable billing account discount sharing to maintain strict cost attribution.
Purchase spend-based CUDs exclusively for the N2 baseline instances in us-central1 and purchase resource-based CUDs for the distributed GKE and Cloud Run services.
Rely entirely on automated Sustained Use Discounts (SUDs) across all projects while disabling Committed Use Discounts to avoid financial lock-in and multi-year contractual commitments.
Purchase resource-based Committed Use Discounts (CUDs) for the steady-state N2 baseline in us-central1, purchase spend-based CUDs for variable multi-region and multi-product compute, and enable discount sharing across all projects in the Cloud Billing account.
Resource-based Committed Use Discounts (CUDs) provide the deepest discounts (up to 55–70%) in exchange for committing to a specific amount of vCPUs, memory, GPUs, or local SSDs in a single region and specific machine series. Spend-based (Flexible) CUDs offer a predictable dollar-per-hour discount across multiple compute services (including Compute Engine, Google Kubernetes Engine, and Cloud Run) regardless of machine series or region. Discount sharing at the Cloud Billing account level aggregates eligible usage across all linked projects so commitments apply wherever matching resources run.
us-central1 captures the highest percentage discount for hardware configurations that will not change.Layering rigid resource-based CUDs for well-understood, single-region baselines under flexible spend-based CUDs for containerized/serverless components—backed by centralized billing discount sharing—delivers the optimal balance between maximum percentage discount and low financial risk.
Purchase resource-based CUDs scoped strictly to individual projects for 100% of all projected peak workloads, and disable billing account discount sharing to maintain strict cost attribution.
Purchase spend-based CUDs exclusively for the N2 baseline instances in us-central1 and purchase resource-based CUDs for the distributed GKE and Cloud Run services.