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Network Appliance NS0-901 Exam Syllabus Topics:

Network Appliance NetApp Certified AI Expert Sample Questions:

1. 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 is designed for small-scale, departmental AI projects and cannot be scaled.
C) It prioritizes CPU performance over GPU performance for traditional machine learning algorithms.
D) It exclusively uses object storage, which simplifies access for data scientists using S3-native tools.

2. A media company is building a new generative AI service. The project has two main components:
1. Data Lake & Fine-Tuning: A 300 TB repository of unstructured data (videos, images, text) stored as objects will be used to fine-tune a foundational model. This process requires a scalable, cost-effective storage solution that can integrate with cloud-native data processing tools like Apache Spark.
2. Inference & RAG: The fine-tuned model will be used in a customer-facing application that leverages Retrieval-Augmented Generation (RAG). To ensure low-latency responses, the RAG component requires extremely fast lookups from a 10 TB vector database.
The company needs a solution that optimizes both cost and performance for this entire lifecycle.
Which combination of NetApp technologies provides the most appropriate solution for this scenario?

A) Use NetApp StorageGRID for the data lake and a NetApp ASA system for the vector database.
B) Use a single, large NetApp ASA system for both the object data lake and the vector database.
C) Use NetApp E-Series for the data lake and a NetApp ASA system for the vector database.
D) Use NetApp Cloud Volumes ONTAP for the data lake and NetApp StorageGRID for the vector database.

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

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

4. A junior administrator is attempting to delete an old, unused Snapshot copy from a production volume to reclaim space but receives an error. The administrator is certain they are using the correct command and have the appropriate 'vsadmin' role.
The command and error are shown below:
cluster-1::> volume snapshot delete -vserver svm_prod -volume app_data -snapshot nightly.2025- 06-15_0015 Error: command failed: This operation is not permitted. Deletion of Snapshot copy "nightly.2025-
06-15_0015" on volume "app_data" in Vserver "svm_prod" requires approval.
Use the "security multi-admin-verify approval show" command to view pending approvals.
What is the most likely reason the administrator cannot delete the Snapshot?

A) The Snapshot is locked by a SnapMirror relationship.
B) Multi-Admin Verification (MAV) is enabled, and the destructive operation requires approval from another designated administrator.
C) The 'vsadmin' role does not have permission to delete Snapshots.
D) The volume is protected by SnapLock, and the Snapshot has not reached its expiry date.

5. An architect is designing the storage and network infrastructure for a new, large-scale AI cluster dedicated to training foundational models. The primary design goal is to achieve the highest possible data throughput and the lowest latency to ensure multi-million dollar GPU resources are never idle. Which two technologies are essential to include in the design to achieve this goal?
(Choose 2.)

A) A 10GbE Ethernet network for all data traffic.
B) NetApp StorageGRID as the primary storage for the training datasets.
C) An InfiniBand or RoCE-capable Ethernet network fabric.
D) A tiered storage architecture using NetApp FabricPool.
E) GPUDirect Storage support on the storage system.

Solutions: