Optimize Compute Cost Cud Sud Sharing

What Resource-Based and Spend-Based CUDs with Discount Sharing Are

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.

How it Meets the Requirements

• Maximizes savings on predictable baseline: Securing resource-based CUDs for the steady-state N2 instances in us-central1 captures the highest percentage discount for hardware configurations that will not change.
• Provides flexible multi-service coverage: Applying spend-based CUDs covers fluctuating compute footprints across different services (Cloud Run, GKE, varied VM families) and regions where rigid resource commitments would risk underutilization.
• Prevents underutilization: Enabling discount sharing at the billing account level ensures that if a specific project scales down, another project's matching usage immediately absorbs the committed discount capacity.

Key Advantages and Capabilities

• Tiered FinOps optimization: Combines deep discounts for static infrastructure with flexible discounts for dynamic architectures.
• Cross-project resource pooling: Eliminates stranded commitments caused by project-level architectural reallocations.
• Multi-product applicability: Spend-based commitments automatically apply across serverless (Cloud Run) and managed container runtimes (GKE).
• Predictable operational budgeting: Establishes a guaranteed hourly spend baseline while letting peak bursts overflow to on-demand pricing.

Why This Is Optimal

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.