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Network Appliance NS0-901 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: 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
Topic 2: Cloud and Hybrid Cloud AI Deployment	18%	- Cloud-native AI solutions and integration - Data mobility and consistency across environments - NetApp cloud data services for AI - Hybrid and multi-cloud AI architectures
Topic 3: NetApp AI Solutions and Architecture	25%	- Storage architectures for AI workloads - ONTAP integration with AI frameworks - NetApp AI-ready infrastructure components - Scalability and performance optimization for AI - Data management and data pipeline design
Topic 4: AI Lifecycle	27%	- Predictive vs generative AI - Data preparation and management for AI - AI governance, ethics, and compliance - AI lifecycle stages: design, training, deployment, monitoring - Model training, inference, and optimization
Topic 5: AI Overview	15%	- Algorithm types: supervised, unsupervised, reinforcement learning - Convergence of AI, high-performance computing, and analytics - AI deployment models: on-premises, cloud, edge - AI, machine learning, and deep learning concepts - AI industry use cases and applications

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Network Appliance NetApp Certified AI Expert Exam Sample Questions (Q54-Q59):

NEW QUESTION # 54
An architect is designing a cost-optimized storage solution for a large AI environment that has two distinct data temperature profiles:
1. Hot Data (200 TB): Actively used training sets and models requiring all-flash performance.
2. Cold Data (2 PB): Inactive, archived datasets and old model versions that must remain online but are infrequently accessed.
The solution must automatically manage data placement based on activity, without requiring manual intervention or changes to file paths. The environment consists of an on-premises data center and a public cloud account.
Which combination of NetApp technologies provides the most complete and cost-effective solution? (Select all that apply.)

A. Use NetApp XCP to manually script the daily movement of cold files from the AFF system to StorageGRID.
B. Deploy a single, large Cloud Volumes ONTAP instance to hold both the hot and cold data tiers.
C. Use NetApp FabricPool to automatically and transparently tier cold data blocks from the AFF A- Series to the StorageGRID system.
D. Use NetApp SnapMirror to create a full copy of the 2 PB of cold data on the AFF A-Series for faster access if needed.
E. Deploy a NetApp AFF A-Series system on-premises to serve as the high-performance tier for the hot data.
F. Deploy NetApp StorageGRID on-premises to serve as a cost-effective capacity tier for the cold data.

Answer: C,E,F

NEW QUESTION # 55
What is the primary difference between C-Series and A-Series storage for AI workloads?

A. C-Series is designed for high-performance workloads, while A-Series focuses on cost-efficiency for general storage.
B. A-Series provides GPU-based acceleration, while C-Series only supports CPU-based workloads.
C. A-Series is for smaller-scale AI workloads, while C-Series supports large-scale, high-performance AI applications.
D. C-Series supports both file and object-based storage, while A-Series is optimized for object storage.

Answer: A

NEW QUESTION # 56
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. Increase the storage quota for the 'jupyter-pvc-user01' PVC.
C. Restart the BlueXP Connector to refresh its permissions.
D. 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.

Answer: D

NEW QUESTION # 57
The "Advisor Assistant" application, running as a pod in Kubernetes, suddenly cannot access its data on the AFF A-Series. The application logs show "connection timed out" errors. The network team provides a firewall log snippet for the traffic between the application pod and the storage system's NFS data LIF.
TIME | SRC_IP | DST_IP | PROTO | DST_PORT | ACTION
-|--||-|-|-
2025-07-11T16:01:10Z | 10.20.5.101 (Pod) | 10.20.10.55 (LIF) | TCP | 111 | BLOCKED 2025-07-
11T16:01:12Z | 10.20.5.101 (Pod) | 10.20.10.55 (LIF) | TCP | 2049 | BLOCKED What is the most likely cause of the connectivity failure?

A. The ONTAP system's data LIF is offline.
B. The AFF A-Series does not support the NFS protocol.
C. The application pod has incorrect mount options configured.
D. A network firewall between the pod's subnet and the storage subnet is blocking the required NFS ports.

Answer: D

NEW QUESTION # 58
What is the primary architectural benefit of using technologies like RDMA (Remote Direct Memory Access) and GPUDirect Storage in a high-performance AI training cluster?

A. They allow GPUs to communicate directly with each other and with NVMe storage, bypassing the host CPU and system memory, which significantly reduces I/O latency and CPU overhead.
B. They enable the use of lower-cost Ethernet switches in place of InfiniBand fabrics without any performance degradation.
C. They reduce the power consumption of the storage array by offloading checksum calculations.
D. They automatically encrypt data in-flight between the GPU servers and the storage system.

Answer: A

NEW QUESTION # 59
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