Question 1

A SaaS company utilizes multiple cloud providers to achieve redundancy and geographic availability. However, managing and optimizing costs across these providers has become a challenge. The company’s FinOps team needs to evaluate cost strategies that minimize management complexity while taking advantage of the strengths of each cloud provider. The company’s workloads are a mix of constant and variable demand across various regions. Which approach would be the most effective for cost management across a multi-cloud environment?

Options :

A : Implement Reserved Instances on all providers for predictable workloads, and use on-demand pricing for variable demand across each provider.

B : Use a Cloud Management Platform (CMP) to monitor costs, and apply a combination of Spot Instances and Reserved Instances for cost efficiency.

C : Negotiate custom pricing agreements with each provider based on total spend, with an emphasis on discounts for predictable usage patterns.

D : Consolidate all predictable workloads to the lowest-cost provider and reserve on-demand usage for burstable workloads on the secondary providers.

Answer: B

Question 2

Which of the following practices can help build a scalable and cost-efficient cloud infrastructure?

Select two correct answers.

Options :

A : Implementing infrastructure as code (IaC) to automate and optimize the provisioning of cloud resources.

B : Manually allocating compute resources to ensure consistent performance under heavy loads.

C : Designing applications with a monolithic architecture to reduce cloud service integration complexity.

D : Using serverless architectures to automatically scale based on event-driven workloads.

Answer: A,D

Question 3

Your company is using multiple cloud providers, including AWS and Azure, and has recently deployed Kubecost to manage Kubernetes costs. However, the finance team notices that some cost data is not aligning with their CloudHealth reports, especially for resources outside Kubernetes. The goal is to ensure unified, accurate cost visibility across all services and cloud providers. As the FinOps Certified Engineer, which two steps would you recommend to achieve this?

Options :

A : Use Kubecost for detailed Kubernetes cost reporting, while

B : Configure CloudHealth and Cloudability to pull cost data from both AWS and Azure, as these tools are designed to aggregate multi-cloud expenses.

C : Integrate Kubecost with CloudHealth to consolidate Kubernetes costs with non-Kubernetes resources in a single platform.

D : Rely solely on Kubecost for cost management across all cloud services, as it aggregates data across providers.

Answer: A,C

Question 4

Your company has recently expanded its cloud footprint to include multiple Azure and AWS accounts across different departments. The FinOps team has decided to implement CloudCheckr for unified cost analysis and optimization. However, the team is unsure how to handle the differences in reserved instance (RI) purchasing options between Azure and AWS to maximize cost savings across both platforms. What would be the best approach to optimize reserved instance purchases using CloudCheckr in a multi-cloud setup?

Options :

A : Use CloudCheckr's Reserved Instance (RI) Planner to evaluate AWS and Azure purchases separately to account for different pricing and terms.

B : Allocate all resources under a single department’s account to simplify RI purchases across both platforms.

C : Set up cross-cloud reservations using CloudCheckr to ensure RI discounts apply across both Azure and AWS workloads.

D : Rely on AWS Savings Plans as a substitute for RIs in both AWS and Azure to avoid dealing with separate RI management processes.

Answer: A

Question 5

Scenario:You are a FinOps engineer for a rapidly growing e-commerce platform. Your organization experiences fluctuations in cloud spending due to seasonal sales and marketing campaigns. Recently, you implemented machine learning (ML) models for forecasting cloud costs, which use historical spending data, usage patterns, and business activity data. However, your stakeholders are concerned about the accuracy of these forecasts, especially for peak periods.

Question:

What actions should you take to improve the accuracy of cost forecasts using ML models in this scenario?

Options :

A : Use a simpler linear model with fewer data inputs to make the model more understandable for stakeholders.

B : Incorporate additional data features like seasonal indicators, campaign schedules, and product release dates to refine the model’s inputs.

C : Set a conservative cost buffer in the forecasted budget to compensate for any potential inaccuracies in the model’s predictions.

D : Regularly retrain the ML model on recent data to ensure that it adapts to new spending patterns and usage trends.

Answer: B,D