A company wants to reduce storage costs for an AI dataset that is accessed frequently for the first 30 days, then rarely accessed afterward. Which strategy is most effective?

Store all data on a single high-performance tier permanently

Apply a lifecycle management policy to move data to a lower-cost tier after 30 days

Delete the data after 30 days to avoid storage costs

Increase the replication factor to ensure data availability

A company has a cloud environment with multiple AI projects. The finance team wants to set a budget for each project and receive alerts when spending exceeds 80% of the budget. They also want to automatically stop non-critical resources when the budget is exceeded. What should they implement?

Use a single budget for all projects and set up alerts.

Manually review costs at the end of each month.

Use spot instances for all projects to reduce costs.

Use resource tags and budget alerts, and configure automated actions to stop non-critical resources.

A startup is building an AI-powered image recognition service. They currently store all training images in a hot storage tier and use a GPU cluster for training. The training job runs once a month and takes 10 hours. The images are accessed frequently during training but rarely otherwise. Which combination of changes would reduce costs without significantly impacting performance?

Move training images to an archive storage tier and use spot instances for training.

Compress the images and use on-demand GPU instances to ensure reliability.

Keep images in hot storage but use reserved GPU instances for training.

Move images to a cool storage tier and use spot instances for training.

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Domain 5Objective 4

Describe Solutions to Optimize Cost CERTIFIED-AI-EXPERT Practice Questions (Page 3)

Part of the AI Common Challenges domain, which accounts for 22% of the CERTIFIED-AI-EXPERT exam. NetApp does not publish an official question count, but from its 90-minute exam (~35–60 total, ~8–13 in this domain), expect 1–2 from this objective — we provide 26 practice questions to prepare you well beyond it. (estimate)

26questions here

6free pages

5concepts

22%of the exam

Questions 11–15

11foundation · medium
A company wants to reduce storage costs for an AI dataset that is accessed frequently for the first 30 days, then rarely accessed afterward. Which strategy is most effective?
Select an answer first
12expert · hard
A company has a cloud environment with multiple AI projects. The finance team wants to set a budget for each project and receive alerts when spending exceeds 80% of the budget. They also want to automatically stop non-critical resources when the budget is exceeded. What should they implement?
Select an answer first
13foundation · medium
Which method reduces data storage costs by eliminating redundant copies of identical data blocks?
Select an answer first
14application · medium
A startup is building an AI-powered image recognition service. They currently store all training images in a hot storage tier and use a GPU cluster for training. The training job runs once a month and takes 10 hours. The images are accessed frequently during training but rarely otherwise. Which combination of changes would reduce costs without significantly impacting performance?
Select an answer first
15foundation · medium
Which compute cost optimization approach offers significant discounts for workloads that can tolerate interruptions?
Select an answer first

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Describe Solutions to Optimize Cost CERTIFIED-AI-EXPERT Practice Questions (Page 3)

Questions 11–15

A company wants to reduce storage costs for an AI dataset that is accessed frequently for the first 30 days, then rarely accessed afterward. Which strategy is most effective?

A company has a cloud environment with multiple AI projects. The finance team wants to set a budget for each project and receive alerts when spending exceeds 80% of the budget. They also want to automatically stop non-critical resources when the budget is exceeded. What should they implement?

Which method reduces data storage costs by eliminating redundant copies of identical data blocks?

Which compute cost optimization approach offers significant discounts for workloads that can tolerate interruptions?

Keep studying — AI Common Challenges