NS0-901시험패스가능덤프문제기출문제공부하기

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Network Appliance NS0-901 Exam Syllabus Topics:

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

>> NS0-901시험패스 가능 덤프문제 <<

Network Appliance NS0-901최신기출자료 & NS0-901덤프샘플문제 체험

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최신 NetApp Certified AI Expert NS0-901 무료샘플문제 (Q48-Q53):

질문 # 48
An architect is designing a data pipeline for a predictive AI model that will forecast retail sales.
The pipeline must be robust, version-controlled, and efficient.
The proposed data flow is as follows:
1. Ingest: Raw sales data is copied daily from multiple point-of-sale (POS) systems to a central staging area on an on-premises ONTAP cluster.
2. Prepare: The raw data is messy. A data engineering team needs a clean, isolated, and writable copy of the latest daily data to perform cleansing and feature engineering tasks without impacting the original raw data.
3. Train: Once prepared, the cleansed dataset is used to retrain the predictive model on a GPU cluster.
This step must be repeatable with the exact same dataset for compliance.
4. Deploy: The newly trained model is pushed to production inference servers.
Which combination of NetApp technologies best supports this entire predictive AI lifecycle?
(Select all
that apply.)

A. Use BlueXP backup and recovery to perform the initial data ingest from the POS systems.
B. Use NetApp FlexClone to create an instantaneous, space-efficient, writable copy of the daily raw data for the data preparation stage.
C. Use NetApp StorageGRID as the primary storage for the high-performance training stage.
D. Use NetApp Snapshots on the prepared dataset volume just before training to create an immutable, point-in-time version for compliance and reproducibility.
E. Use a RAG architecture for the sales forecasting model.
F. Use NetApp XCP to efficiently aggregate the raw sales data from POS systems into the central staging area.

정답：B,D,F

질문 # 49
An organization is planning to deploy a large AI infrastructure but wants to avoid a large, upfront capital expenditure. They prefer an operational expenditure (OpEx) model where they pay for storage and compute resources as they are consumed. They also need the flexibility to scale resources up or down based on project demands.
Which NetApp consumption model is specifically designed to meet these financial and operational requirements?

A. A standard capital purchase of AFF and ASA systems.
B. NetApp Cloud Volumes ONTAP PAYGO licensing only.
C. A perpetual licensing model for all ONTAP software features.
D. NetApp Keystone, which provides a subscription-based, pay-as-you-go service for on-premises and cloud storage.

정답：D

질문 # 50
The company decides to establish a disaster recovery (DR) site in a secondary data center for the entire Digital Twin platform. The DR plan must protect the HPC data, the AI training data, and the central data lake.
The DR requirements are:
- RPO: 4 hours for all data.
- RTO: 24 hours for the entire platform.
- Process: The failover and failback process should be as automated as possible.
Which combination of technologies provides the most comprehensive DR solution?

A. Use NetApp SnapMirror for the ASA, StorageGRID replication for the data lake, and rely on tape backups for the E-Series/BeeGFS data.
B. Deploy a MetroCluster configuration spanning the primary and DR sites for all three storage systems.
C. Use BlueXP backup and recovery to back up all three storage systems (ASA, E-Series, StorageGRID) to a single cloud target.
D. Use NetApp SnapMirror for the ASA, StorageGRID's built-in replication for the data lake, and a host- based tool like 'rsync' for the E-Series/BeeGFS data, all orchestrated via BlueXP disaster recovery.

정답：D

질문 # 51
What is the primary role of NetApp Trident in a Kubernetes environment designed for AI workloads?

A. To provide a web-based IDE, like Jupyter, for data scientists to develop 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 function as a container runtime interface for executing AI models.

정답：C

질문 # 52
The AI training jobs on the AIPod are performing below expectations. The NVIDIA DGX servers' GPUs show low utilization. A performance analysis reveals that the bottleneck is not the storage system itself, but the network path between the storage and the compute nodes.
The current network configuration is as follows:
Network_Fabric: 100GbE Standard Ethernet
Protocol: NFS over TCP/IP
Data_Path: Storage -> Host CPU -> GPU Memory
Which network architecture enhancement would provide the most significant performance improvement by reducing latency and CPU overhead?

A. Upgrade the network switches to a model with a larger packet buffer.
B. Add more 100GbE network ports to the storage controllers.
C. Isolate the storage traffic on a separate VLAN from the management traffic.
D. Implement RDMA over Converged Ethernet (RoCE) and configure GPUDirect Storage.

정답：D

질문 # 53
......

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