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Network Appliance NetApp Certified AI Expert Sample Questions:

1. A financial services company has deployed a real-time fraud detection model at the edge. The model is designed for low-latency inference. However, monitoring reports indicate that the infrastructure costs are excessively high, and GPU utilization is consistently low. The architect reviews the deployment configuration.
Instance_Type: NVIDIA DGX A100 (8 GPUs)
Storage_Tier: High-Performance All-Flash (NetApp ASA)
Network: 100GbE RoCE
GPU_Utilization_Avg: 5%
Monthly_Cost: $15,000
Workload_Profile: Low-volume, sporadic, real-time predictions
What is the most likely cause of the high costs and low utilization?

A) The storage tier is too slow, causing the GPUs to wait for data.
B) The network latency is too high for an edge deployment.
C) The compute and storage infrastructure is sized for a large-scale training workload, not a lightweight inference workload.
D) The model was trained using supervised learning, which is inefficient for fraud detection.

2. The firm decides to implement a disaster recovery (DR) site for the "Advisor Assistant" application in a secondary data center. The Recovery Point Objective (RPO) is 15 minutes, and the Recovery Time Objective (RTO) is 4 hours. The design must protect both the document data lake and the vector database.
The primary site contains:
- Data Lake: NetApp StorageGRID
- Vector DB: NetApp AFF A-Series
Which combination of technologies and processes provides a complete and robust DR solution?
(Select all that apply.)

A) Use BlueXP disaster recovery to orchestrate and automate the failover and failback workflows for the application and its data dependencies.
B) Use NetApp FlexCache at the DR site to cache data from the primary site.
C) Use StorageGRID's built-in replication rules to replicate object data from the primary site's grid to a StorageGRID instance at the DR site.
D) Rely on tape backups to be shipped to the DR site in the event of a disaster.
E) Use NetApp SnapMirror to create an asynchronous replication relationship for the AFF A-Series volume containing the vector database, with a schedule of 10 minutes.
F) Use the NetApp DataOps Toolkit to manually script the failover process.

3. An organization is developing a new AI-powered application. The initial phase involves feeding a curated 50 TB dataset of labeled images into a complex neural network, allowing the model to learn and adjust its internal parameters over millions of iterations. The second phase involves deploying this finalized model to a web service where it will process single, user-uploaded images and return a classification in real-time.
Which statement accurately describes these two phases?

A) Both Phase 1 and Phase 2 are examples of inferencing.
B) Phase 1 is training, and Phase 2 is inferencing.
C) Phase 1 is inferencing, and Phase 2 is training.
D) Both Phase 1 and Phase 2 are examples of training.

4. A financial services company is required by regulators to be able to trace any version of their deployed fraud detection model back to the exact dataset and source code commit used to train it.
The current MLOps workflow is as follows:
Code_Repository: Git (commit hash: a1b2c3d4)
Dataset_Location: /vol/prod_data/fraud_dataset_v3
Storage_System: NetApp ONTAP 9
Model_Output: /vol/models/fraud_model_v3.2
Which NetApp technology should be used to create an immutable, point-in-time, and space- efficient copy of the dataset that can be linked to the specific code commit and model version?

A) NetApp Snapshots
B) NetApp FlexClone
C) NetApp SnapMirror
D) NetApp FabricPool

5. An AI architect is designing a storage solution for a new training cluster. The primary workload consists of training large language models, which involves sequential reads of massive datasets.
The key requirement is to maximize GPU utilization by providing the highest possible data throughput. Cost is a secondary concern to performance.
Which NetApp storage system is the most appropriate choice for this workload?

A) NetApp C-Series
B) NetApp E-Series
C) NetApp StorageGRID
D) NetApp ASA (All-SAN Array)

Solutions: