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Zorluk: OrtaOptimizing Business Processes through FinOps and Cloud Cost Management

A global telecommunications enterprise operates its SaaS management portal and telemetry analytics pipelines across multiple Google Cloud projects linked to a central Cloud Billing account. The engineering and finance leaders need to establish a FinOps governance framework to improve cost visibility and optimize spending across compute and storage resources without sacrificing application performance or release agility. Which of the following strategies should the team implement to achieve these FinOps objectives? (Select TWO.)

  1. Export detailed Cloud Billing data to BigQuery to enable granular query analysis and build automated programmatic notifications via Cloud Pub/Sub and Budgets API.Cevap
  2. Purchase Flexible Committed Use Discounts (CUDs) for baseline compute expenditure across projects to secure cost savings while maintaining operational flexibility for variable workloads.Cevap
  3. C
    Purchase 3-year standard Compute Engine Committed Use Discounts (CUDs) targeted to cover maximum peak burst capacity across all projects.
  4. D
    Migrate all regional transactional relational databases from Cloud SQL for PostgreSQL to multi-region Cloud Spanner instances to lower baseline operational costs.
  5. E
    Migrate all lightweight, stateless HTTP microservices from Cloud Run to a dedicated Google Kubernetes Engine (GKE) cluster with static node pools to minimize infrastructure costs.

Cevap

The correct strategies are exporting detailed Cloud Billing data to BigQuery for automated governance and purchasing Flexible Committed Use Discounts (CUDs) to cover baseline compute expenditures.
Establishing a FinOps practice on GCP relies on granular cost visibility and flexible commitment strategies. Exporting detailed billing data to BigQuery provides queryable access to resource-level costs and labels, while linking Pub/Sub to Cloud Budgets enables automated programmatic remediation. Applying Flexible Committed Use Discounts (CUDs) reduces hourly spend on baseline compute capacity across project boundaries without locking into fixed machine types.

Adım Adım Çözüm

1
Analyze visibility and governance requirements
Exporting detailed billing data to BigQuery enables deep SQL analysis across projects, and attaching Pub/Sub to Cloud Budgets enables programmatic cost alerts and actions.
FinOps governance requires automated monitoring and granular cost allocation down to individual resources.
2
Evaluate compute cost optimization strategy
Flexible CUDs provide committed spend discounts across machine series, regions, and projects for steady-state baseline compute usage.
Commitments should cover predictable baseline compute while leaving variable burst traffic to scale dynamically on demand.

Anahtar Kavram

FinOps Cost Governance and Compute Commitment Optimization
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Konular

Optimizing Business Processes through FinOps and Cloud Cost Management