Exam Network Appliance NS0-901 Study Guide & New NS0-901 Exam Question

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Network Appliance NS0-901 Exam Syllabus Topics:

Section	Objectives
Industry Use Cases	- AI applications across industries 1. Digital twins 2. Autonomous systems and agents 3. Healthcare AI
AI Lifecycle and Deployment	- End-to-end AI lifecycle 1. Data ingestion and preparation 2. Model training and validation 3. Model deployment and monitoring - Operational challenges 1. Data governance and management 2. Scalability and performance optimization
AI and Machine Learning Fundamentals	- AI, ML, DL concepts 1. Differences between AI, machine learning, and deep learning 2. Training, inference, and prediction workflows - Algorithm types 1. Unsupervised learning 2. Supervised learning 3. Reinforcement learning
AI Infrastructure and NetApp Solutions	- AI-ready data infrastructure 1. High-performance storage for AI workloads 2. Data pipeline optimization for AI/ML workloads - Converged workloads 1. Shared infrastructure design considerations 2. AI, HPC, and analytics convergence

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Network Appliance NetApp Certified AI Expert Exam Sample Questions (Q35-Q40):

NEW QUESTION # 35
An MLOps team is using the BlueXP Workload Factory to automate the deployment of a Jupyter notebook environment for a new data scientist. The deployment job fails. The team reviews the job details in the BlueXP UI.
Job ID: 78a1c-2b3d-4e5f
Service: BlueXP Workload Factory
Action: Deploy JupyterHub on Kubernetes
Status: FAILED
Error Message: "Failed to create PersistentVolumeClaim 'jupyter-pvc-user01'.
User 'service-account- bluexp' does not have permission to 'create' resource
'persistentvolumeclaims' in cluster 'k8s-prod- cluster-01'."
What is the most direct way to resolve this issue?

A. Manually create the PersistentVolumeClaim using 'kubectl'.
B. Modify the Kubernetes RBAC (Role-Based Access Control) configuration to grant the 'service- account-bluexp' the necessary permissions to create PVCs in the target cluster.
C. Restart the BlueXP Connector to refresh its permissions.
D. Increase the storage quota for the 'jupyter-pvc-user01' PVC.

Answer: B

NEW QUESTION # 36
An architect is designing a global infrastructure for a company that develops AI for autonomous vehicles.
The design must accommodate three distinct locations and functions:
1. Edge (Test Tracks): Fleets of test cars generate 100s of TBs of sensor data per day. This data must be ingested locally with high performance.
2. Core (Primary Data Center): The raw data from all edge sites must be aggregated here. This location houses the primary data lake and the main GPU cluster for large-scale model training.
3. Cloud (Public Cloud Provider): Data scientists want to use cloud-native tools for experimental data processing and model development. They also need a cost-effective location for long-term archiving of raw data.
Which combination of deployment locations and NetApp technologies creates the most logical and efficient end-to-end solution?

A. Use NetApp ONTAP systems at the edge and core, and Cloud Volumes ONTAP in the public cloud.
Use SnapMirror to replicate data from edge to core, and FabricPool to tier data from the core to the cloud.
B. Deploy a single, global NetApp StorageGRID across all three locations to act as a unified data plane.
C. Use NetApp E-Series at the edge, NetApp ASA at the core, and NetApp StorageGRID in the cloud.
Use SnapMirror to move data between all three tiers.
D. Use Cloud Volumes ONTAP at the edge, NetApp StorageGRID at the core, and on-premises ONTAP for cloud archive.

Answer: A

NEW QUESTION # 37
The Chief Information Security Officer (CISO) is concerned about the risk of a ransomware attack encrypting the critical vector database hosted on the NetApp AFF A-Series. The CISO wants a solution that can proactively detect and block a live attack in real-time, not just recover from a backup after the fact.
Which NetApp security feature should the architect enable on the vector database volume to meet this requirement?

A. NetApp SnapLock (Compliance Mode)
B. Multi-Admin Verification (MAV)
C. NetApp Volume Encryption (NVE)
D. Autonomous Ransomware Protection (ARP)

Answer: D

NEW QUESTION # 38
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. Enable QoS maximums on the training volume to limit its IOPS.
B. Increase the number of network ports connected to the storage controller.
C. Replace the NFS protocol with iSCSI for all training data access.
D. Implement a NetApp FlexGroup volume to spread the dataset across multiple constituent volumes and aggregates.
E. Use NetApp FlexCache to create a local cache of the training data on each compute node.

Answer: D,E

NEW QUESTION # 39
What is the primary role of NetApp Trident in a Kubernetes environment designed for AI workloads?

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

Answer: C

NEW QUESTION # 40
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