P.S. NewDumps在Google Drive上分享了免費的、最新的NS0-901考試題庫：https://drive.google.com/open?id=1r6B4caP4RYqkUJZbls0jnL1EN9mdAp2h
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| Section | Weight | Objectives |
|---|---|---|
| AI Overview | 15% | - Convergence of AI, high-performance computing, and analytics - AI, machine learning, and deep learning concepts - AI deployment models: on-premises, cloud, edge - AI industry use cases and applications - Algorithm types: supervised, unsupervised, reinforcement learning |
| Cloud and Hybrid Cloud AI Deployment | 18% | - Hybrid and multi-cloud AI architectures - Data mobility and consistency across environments - NetApp cloud data services for AI - Cloud-native AI solutions and integration |
| Security, Reliability, and Operations | 15% | - Monitoring, logging, and troubleshooting AI environments - High availability and data protection - Data security and access control for AI - Cost management and efficiency |
| AI Lifecycle | 27% | - AI governance, ethics, and compliance - Predictive vs generative AI - Data preparation and management for AI - Model training, inference, and optimization - AI lifecycle stages: design, training, deployment, monitoring |
| NetApp AI Solutions and Architecture | 25% | - Data management and data pipeline design - NetApp AI-ready infrastructure components - ONTAP integration with AI frameworks - Scalability and performance optimization for AI - Storage architectures for AI workloads |
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問題 #43
An AI architect is reviewing the design for a new data lake. The primary requirement is to store petabytes of unstructured data (images, video, sensor logs) in a highly durable, scalable, and cost- effective manner. The data will be accessed via S3 API by various data processing and analytics applications.
The initial design proposes using a traditional Network Attached Storage (NAS) filer with a large number of disks. The architect reviews the proposal:
Proposed_System: Traditional NAS Filer
Protocol: NFSv4
Scalability_Model: Scale-up
Metadata_Handling: Centralized in filer head
Cost_per_GB: Moderate
Why is this proposed system a poor choice for a petabyte-scale data lake?
答案：D
問題 #44
An AI team is planning two separate projects. The architect needs to provision the appropriate infrastructure for each.
| | Project A | Project B|
| -- | | - |
| Goal | Build a novel image recognition model from scratch.
| Adapt an existing, pre- trained LLM to understand company-specific jargon. |
| Input Data | 10 million new, unlabeled images. | A 50 GB text corpus of internal documents. |
| Required Compute | Very High (Weeks of multi-GPU training) | Moderate (Hours of single-GPU training) | Which two statements accurately describe the infrastructure requirements for these projects?
(Choose two.)
答案：A,B
問題 #45
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?
答案：B
問題 #46
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?
答案：A
問題 #47
The data science team in Azure reports that training jobs are taking longer than expected. An analysis of the Cloud Volumes ONTAP instance in Azure shows that the instance type is undersized for the I/O demands of the training workload. The architect needs to change the Azure VM instance type for the Cloud Volumes ONTAP system to a more powerful one.
The current configuration is:
Cloud_Provider: Azure
ONTAP_System: Cloud Volumes ONTAP (Single Node)
Current_Instance_Type: Standard_DS3_v2
Target_Instance_Type: Standard_E8s_v4
What is the most direct method to perform this operation using NetApp's management tools?
答案：A
問題 #48
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