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Network Appliance NS0-901 Exam Syllabus Topics:

Section	Weight	Objectives
Security, Reliability, and Operations	15%	- Monitoring, logging, and troubleshooting AI environments - Cost management and efficiency - Data security and access control for AI - High availability and data protection
AI Overview	15%	- Convergence of AI, high-performance computing, and analytics - AI industry use cases and applications - AI deployment models: on-premises, cloud, edge - AI, machine learning, and deep learning concepts - Algorithm types: supervised, unsupervised, reinforcement learning
Cloud and Hybrid Cloud AI Deployment	18%	- Data mobility and consistency across environments - Hybrid and multi-cloud AI architectures - Cloud-native AI solutions and integration - NetApp cloud data services for AI
AI Lifecycle	27%	- AI governance, ethics, and compliance - AI lifecycle stages: design, training, deployment, monitoring - Data preparation and management for AI - Predictive vs generative AI - Model training, inference, and optimization
NetApp AI Solutions and Architecture	25%	- ONTAP integration with AI frameworks - NetApp AI-ready infrastructure components - Scalability and performance optimization for AI - Data management and data pipeline design - Storage architectures for AI workloads

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Network Appliance NetApp Certified AI Expert Exam Sample Questions (Q71-Q76):

NEW QUESTION # 71
An organization recently suffered a ransomware attack that encrypted several volumes on their primary ONTAP storage system, including a critical volume containing curated training data. The security team needs to implement a solution that can proactively detect and block ransomware- like file I/O patterns and automatically create a secure Snapshot copy before any damage is done.
The current ONTAP configuration is as follows:
ONTAP_Version: 9.12.1
Security_Features: SnapLock (Compliance Mode) on archive volumes
Anti-Virus_Scan: Enabled (Vscan)
Ransomware_Detection: Not configured
Which ONTAP feature should be enabled to provide this proactive, automated protection?

A. Enable Multi-Admin Verification (MAV) on all volumes.
B. Use BlueXP backup and recovery to back up the volumes to the cloud more frequently.
C. Increase the frequency of scheduled Snapshots.
D. Enable Autonomous Ransomware Protection (ARP).

Answer: D

NEW QUESTION # 72
A data scientist on the team wants to run an experiment on a new vector indexing strategy. To do this, they need a temporary, writable copy of the main vector database. They use the NetApp DataOps Toolkit for Python to automate this process.
The following script is executed:
from netapp_dataops.k8s import clone_pvc
clone_pvc(
source_pvc_name="prod-vector-db-pvc",
new_pvc_name="exp-indexing-clone",
namespace="ds-prod"
)
Assuming the source PVC exists and the user has correct permissions, what is the primary benefit of using this method?

A. It creates a read-only Snapshot, ensuring the integrity of the experimental data.
B. It creates a full physical copy of the data, providing the best performance isolation.
C. It automatically migrates the data from the AFF A-Series to the StorageGRID system for the experiment.
D. It uses NetApp FlexClone technology to create a near-instantaneous, space-efficient writable copy of the volume, accelerating the experimental workflow.

Answer: D

NEW QUESTION # 73
Which of the following techniques are used to maximize GPU utilization in AI workloads? (Choose two)

A. Balancing compute and storage workloads efficiently
B. Scheduling GPU-intensive tasks during off-peak hours
C. Using larger batch sizes
D. Utilizing CPU-based workloads for all tasks

Answer: A,B

NEW QUESTION # 74
The architect is designing the complete, automated data pipeline from the on-premises data center to the Azure cloud for this medical imaging project. The design must prioritize security, efficiency, and reproducibility.
Which sequence of actions provides the most robust and automated solution?

A. Use FabricPool to automatically tier all raw data to Azure Blob storage, then mount the blob container to the training VMs.
B. Use SnapMirror to replicate the raw, sensitive data to Azure first, then run BlueXP classification in the cloud to find PII.
C. Manually copy raw data to Azure, run a cloud-based script to anonymize it, then start training.
D. Use BlueXP classification to scan the on-prem data; use a DataOps Toolkit script to trigger a FlexClone of the source volume for anonymization; use SnapMirror to replicate the anonymized clone to Cloud Volumes ONTAP; then begin training in Azure.

Answer: D

NEW QUESTION # 75
The pod running the vector database on the Kubernetes cluster fails to start. An MLOps engineer runs 'kubectl describe pod vector-db-pod-0' and sees the following event message:
Events:
Type Reason Age From Message
- - - -
Warning FailedScheduling 30s default-scheduler 0/8 nodes are available: 8 node(s) did not match pod anti-affinity rules.
The pod's manifest contains the following 'affinity' definition:
affinity:
podAntiAffinity:
requiredDuringSchedulingIgnoredDuringExecution:
- labelSelector:
matchExpressions:
- key: app
operator: In
values:
- vector-db
topologyKey: "kubernetes.io/hostname"
What is the most likely reason the pod cannot be scheduled?

A. The pod's anti-affinity rule prevents it from being scheduled on any node that is already running another pod with the label 'app=vector-db'.
B. The 'topologyKey' is invalid; it should be 'failure-domain.beta.kubernetes.io/zone'.
C. The 'vector-db-pod-0' is requesting more GPU resources than are available on any node.
D. The PersistentVolumeClaim for the pod is in a 'Pending' state.

Answer: A

NEW QUESTION # 76
......

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