A multinational SaaS enterprise operating across multiple GCP projects is establishing an organization-wide FinOps governance framework and cost optimization strategy. The current environment consists of steady-state backend API services processing transactional user requests, predictable daily analytical reporting workloads in BigQuery, and highly variable development and testing environments. Which of the following architectural and governance actions should the Cloud Architect recommend to optimize operational spend while enforcing budget accountability? (Select THREE.)
- Enforce mandatory cost-center tag and label policies across all project resources using Organization Policy constraints and map them to BigQuery detailed billing exports.Cevap
- Purchase Flexible Committed Use Discounts (CUDs) for baseline spend to ensure cost savings across fluctuating compute machine families and regions.Cevap
- Transition predictable, high-volume BigQuery analytical query workloads from on-demand pricing to edition-based slot reservations.Cevap
- DPurchase 3-year standard Compute Engine Committed Use Discounts dedicated specifically to the transient development and testing environments.
- EProvision dedicated multi-zone Google Kubernetes Engine (GKE) clusters for simple stateless dev/test workloads to optimize resource management.
Cevap
The Cloud Architect should implement mandatory resource labeling linked to BigQuery billing exports, utilize Flexible Committed Use Discounts for baseline compute spend, and transition predictable analytical workloads to BigQuery slot capacity reservations.
Establishing clear FinOps governance requires structured labeling for cost visibility, flexible commitment models for baseline compute to balance cost and agility, and slot reservations for predictable BigQuery workloads to cap analytical expenses.
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Anahtar Kavram
Enterprise FinOps Governance and Strategic GCP Cost Optimization