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Network Appliance NetApp Certified AI Expert Sample Questions:

1. 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.

2. 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.

3. The company's finance department mandates a cost-control strategy for the petabyte-scale StorageGRID data lake. The analysis shows that 80% of the simulation data is not accessed after
90 days but must be retained for five years for regulatory compliance. Which StorageGRID feature should the architect use to automatically reduce the long-term storage costs for this inactive data?

A) Enable deduplication and compression on all StorageGRID storage nodes.
B) Configure an Information Lifecycle Management (ILM) policy that automatically moves objects older than 90 days to a lower-cost cloud archive tier, such as Amazon S3 Glacier Deep Archive.
C) Use NetApp SnapMirror to replicate the cold data to a different, lower-cost StorageGRID cluster.
D) Implement a FabricPool policy to tier the data to a NetApp ASA system.

4. 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) Fine-tune the LLM on a sanitized dataset to teach it to ignore PII.
B) 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.
C) Move the entire client portfolio database to an encrypted, air-gapped system.
D) Use BlueXP classification to perform an initial scan of the portfolio database to identify and tag all columns containing PII.
E) Rely on a disclaimer in the chatbot UI telling advisors not to enter queries related to specific clients.

5. A data scientist is using the NetApp DataOps Toolkit for Python to automate the creation of a new, writable volume for an experiment. The script is intended to clone an existing dataset volume. When the script is executed, it fails with an error.
The relevant portion of the Python script is:
from netapp_dataops.k8s import clone_pvc
clone_pvc(
source_pvc_name="dataset-v1-pvc",
new_pvc_name="experiment-clone-pvc",
namespace="ds-team-1"
)
The script produces the following error in the terminal:
'Error: Failed to clone PVC. Source PVC 'dataset-v1-pvc' not found in namespace 'ds-team-1'.' What is the most likely cause of this error?

A) The source PersistentVolumeClaim (PVC) named 'dataset-v1-pvc' does not exist or is in a different namespace.
B) The Kubernetes cluster does not have NetApp Trident installed.
C) The Python script is missing the necessary import statement for the toolkit.
D) The NetApp DataOps Toolkit does not support cloning volumes.

Solutions: