Question 1

Scenario: You are managing an application on Google Cloud Platform (GCP) that serves a global audience with both static and dynamic content. To improve user experience, you implemented a caching layer in Cloud Memorystore (Redis). However, as usage has increased, so has the cost of maintaining the Redis cache. You notice that the Redis cache hit rate is lower than expected, with many requests still reaching the backend, which drives up costs for both the cache and backend resources.What action would be the most effective way to optimize cache utilization and reduce costs?

Options :

A : Review and update cache keys to ensure that frequently requested data is cached effectively.

B : Increase the Redis instance size to improve cache performance and hit rates.

C : Implement a load balancer with round-robin routing to distribute requests evenly across instances.

D : Set a lower time-to-live (TTL) for cached items to keep the cache fresher.

Answer: A

Question 2

Which of the following strategies is the most effective when developing a budget for a multi-cloud environment that has unpredictable usage spikes?

Options :

A : Allocating a fixed budget for each cloud service provider based on past expenditure

B : Assigning equal budget limits to each cloud environment regardless of service type or region

C : Utilizing a single budget management tool for all cloud environments without considering differences in provider pricing models

D : Implementing a dynamic budgeting model with continuous reallocation based on real-time usage data

Answer: D

Question 3

Your organization uses Kubecost to manage Kubernetes costs and has recently noticed a rise in idle resources across various clusters. The FinOps team needs to reduce costs by optimizing these idle resources. Which of the following actions would be most effective using Kubecost? (Select two correct answers)

Options :

A : Implement Kubecost’s node right-sizing recommendations to allocate optimal instance types based on usage patterns.

B : Disable Kubecost’s cost allocation feature to focus only on cluster-wide cost reductions.

C : Set higher resource requests for applications to maximize node utilization.

D : Leverage Kubecost’s idle resource tracking to identify and consolidate underutilized nodes.

E : Use Kubecost’s showback functionality to distribute idle costs among teams proportionally.

Answer: A,D

Question 4

Scenario: You are managing an application on Google Cloud Platform (GCP) that serves a global audience with both static and dynamic content. To improve user experience, you implemented a caching layer in Cloud Memorystore (Redis). However, as usage has increased, so has the cost of maintaining the Redis cache. You notice that the Redis cache hit rate is lower than expected, with many requests still reaching the backend, which drives up costs for both the cache and backend resources.What action would be the most effective way to optimize cache utilization and reduce costs?

Options :

A : Review and update cache keys to ensure that frequently requested data is cached effectively.

B : Increase the Redis instance size to improve cache performance and hit rates.

C : Implement a load balancer with round-robin routing to distribute requests evenly across instances.

D : Set a lower time-to-live (TTL) for cached items to keep the cache fresher.

Answer: A

Question 5

Which of the following is the most effective approach for enforcing cloud financial policies within an engineering team to ensure compliance without impeding innovation?

Options :

A : Limit engineers' ability to provision resources to pre-approved service types only.

B : Implement strict approval processes for every cloud resource provisioning request.

C : Use automated tagging policies to categorize cloud resources by cost center and application.

D : Set hard budget limits for each engineering team, with automatic shutdowns when limits are exceeded.

Answer: C

Free FinOps-Certified-Engineer Mock Exam – Practice Online Confidently

Buying Options: