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Network Appliance NS0-901 Exam Syllabus Topics:

Network Appliance NetApp Certified AI Expert Sample Questions:

Question 1

What is the primary role of NetApp Trident in a Kubernetes environment designed for AI workloads?

A. To provide a web-based IDE, like Jupyter, for data scientists to develop models.
B. To directly accelerate GPU computations using specialized drivers.
C. To function as a container runtime interface for executing AI models.
D. To act as a dynamic storage orchestrator, provisioning persistent storage from NetApp backends on- demand for containerized applications.

Question 2

The company's compliance officer mandates that all raw simulation data in the StorageGRID data lake must be protected from modification or deletion for a period of seven years. Which two StorageGRID features should be implemented to meet this strict, long-term data immutability requirement? (Choose 2.)

A. Configure an Information Lifecycle Management (ILM) rule that applies to the bucket and sets a retention period of seven years.
B. Encrypt all objects in the bucket using server-side encryption (SSE).
C. Create a new S3 bucket with Object Lock enabled in Compliance mode.
D. Use NetApp SnapMirror to replicate the data to a second StorageGRID system.
E. Enable Autonomous Ransomware Protection (ARP) on the StorageGRID system.

Question 3

To comply with the security mandate, the architect must design a process to prevent client PII from the portfolio database from ever being included in the context sent to the LLM. Which two actions are required to build a robust and automated solution for this? (Choose 2.)

A. Use BlueXP classification to perform an initial scan of the portfolio database to identify and tag all columns containing PII.
B. Fine-tune the LLM on a sanitized dataset to teach it to ignore PII.
C. Move the entire client portfolio database to an encrypted, air-gapped system.
D. Implement a data preparation step in the RAG pipeline that programmatically masks or excludes any data fields tagged as PII before the context is constructed.
E. Rely on a disclaimer in the chatbot UI telling advisors not to enter queries related to specific clients.

Question 4

An AI platform is suffering from poor performance during distributed training jobs. The training data resides on a single, large NFS volume. Monitoring shows that while the overall network throughput to the storage system is high, individual GPU nodes experience significant I/O wait times, and the single ONTAP volume is becoming a performance bottleneck. The goal is to re- architect the storage layout to maximize read parallelism and throughput for the training cluster.
Which two actions should the architect take to address this performance bottleneck? (Choose 2.)

A. Use NetApp FlexCache to create a local cache of the training data on each compute node.
B. Increase the number of network ports connected to the storage controller.
C. Implement a NetApp FlexGroup volume to spread the dataset across multiple constituent volumes and aggregates.
D. Enable QoS maximums on the training volume to limit its IOPS.
E. Replace the NFS protocol with iSCSI for all training data access.

Question 5

What is the primary architectural advantage of using a NetApp AIPod with NVIDIA DGX servers for the AI training cluster, as described in the scenario?

A. It is a reference architecture that is pre-validated by NetApp and NVIDIA to eliminate design complexity and ensure predictable performance for AI workloads.
B. It prioritizes CPU performance over GPU performance for traditional machine learning algorithms.
C. It exclusively uses object storage, which simplifies access for data scientists using S3-native tools.
D. It is designed for small-scale, departmental AI projects and cannot be scaled.

Solutions: