Question 1

Your organization has a significant number of underutilized virtual machines (VMs) across multiple cloud environments, resulting in unnecessary expenses. The team aims to develop an automation solution to identify and handle underutilized VMs. Which solution best balances cost optimization, compliance, and operational continuity for underutilized resources?

Options :

A : Create an automated script that identifies underutilized VMs based on specific usage metrics and tags them. These tagged VMs are terminated at the end of the month.

B : Develop a script that detects underutilized VMs based on predefined metrics, schedules them for shutdown during non-peak hours, and sends regular reports to the team for review.

C : Use a script to analyze VM utilization, downscale all VMs to the smallest instance size if they remain idle for 24 hours, and notify team members daily.

D : Write a script to automatically shut down any VM that has been idle for more than 48 hours and alert the team after termination.

Answer: B

Question 2

Your company uses Kubecost to manage and allocate Kubernetes cloud costs for multiple teams working within a shared cluster. Recently, the FinOps team noticed unexpected cost increases in certain namespaces. They want to identify the primary cost drivers and adjust settings to better control future expenses. Which of the following actions in Kubecost would provide the most comprehensive insights into cost spikes and help optimize resource usage?

Options :

A : Set up cost alerts to notify the FinOps team when a namespace exceeds its daily cost limit.

B : Examine the "Cost Allocation" view to analyze per-namespace costs and allocate a budget cap to prevent overspending.

C : Use the "Savings Recommendations" feature to identify underutilized resources across namespaces and adjust requests and limits accordingly.

D : Configure resource quotas on each namespace to restrict CPU and memory usage and prevent cost spikes.

Answer: C

Question 3

A FinOps team is building a custom integration to aggregate and analyze cloud spend from AWS, Azure, and GCP. They aim to create a unified dashboard for real-time cost insights across all cloud environments. The team needs to decide on the appropriate tools and configurations for data retrieval and aggregation to support both historical and real-time analysis. Which two of the following approaches should they take to ensure reliable, scalable cost data ingestion and analysis?

Options :

A : Set up AWS Lambda functions to retrieve cost data from AWS Cost Explorer API and store it in Amazon RDS for continuous historical and real-time analysis.

B : In GCP, configure the Billing Export to BigQuery for detailed cost information, then build custom SQL queries to extract real-time cost trends and export these summaries to a centralized reporting platform.

C : Leverage Amazon Athena with the AWS Cost and Usage Report (CUR) to perform SQL-based analysis on AWS costs directly, using Athena to feed this data into a centralized dashboard for cross-cloud cost analysis.

D : Use Azure Data Factory (ADF) to schedule and automate the ingestion of data from Azure Cost Management API, storing the data in a centralized data lake such as Azure Data Lake or AWS S3.

Answer: B,D

Question 4

When using the GCP Billing API to automate cost management, which of the following is possible? (Select two)

Options :

A : Apply discounts directly to specific projects in real-time

B : Modify pricing tiers of GCP services based on usage patterns

C : Set budget alerts and automate notifications for threshold breaches

D : Integrate with external reporting systems by exporting billing data

Answer: C,D

Question 5

When implementing a multi-cloud strategy, which actions should be prioritized to effectively manage and optimize cloud spend across different cloud providers?

(Choose two)

Options :

A : Standardizing workload deployment patterns across clouds to allow easier comparison of costs and performance.

B : Implementing a unified FinOps tool that provides real-time visibility into usage and costs across all cloud environments.

C : Prioritizing the lowest-cost provider for each workload, regardless of differences in performance or service quality.

D : Utilizing reserved instances in each cloud to ensure maximum savings over a multi-cloud deployment.

Answer: A,B

Higher Test Marks with Free Online FinOps-Certified-Engineer Exam Practice

Buying Options: