Network Appliance NetApp Certified AI Expert : NS0-901

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最新的 NetApp Certified AI Expert NS0-901 免費考試真題:

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

2. An architect is designing a comprehensive AI platform for a large enterprise. The platform must support the entire data lifecycle, from ingest at the edge to a central data lake, and finally to a high- performance training cluster.
The requirements are:
- Edge Ingest: Data must be collected at remote sites and efficiently replicated to the core.
- Data Lake: A central, petabyte-scale repository for unstructured data, accessible via the S3 protocol.
- Training Cluster: A high-performance compute cluster that requires low-latency, parallel file access to training datasets.
- Data Traceability: All datasets used for training must be immutably versioned.
Which combination of NetApp technologies and protocols should the architect choose to build this solution? (Select all that apply.)

A) Use NetApp ONTAP systems at the edge and NetApp SnapMirror to replicate data to the core data center.
B) Use NetApp Snapshots on the training dataset volumes to create immutable, point-in-time versions for traceability.
C) Use a NetApp E-Series system with a parallel file system (like BeeGFS) to provide high- performance, parallel file access for the training cluster.
D) Use iSCSI as the primary protocol for the data lake to ensure maximum compatibility.
E) Use NetApp FlexCache to tier cold data from the data lake to the public cloud.
F) Use NetApp StorageGRID to create the petabyte-scale, S3-accessible data lake at the core.

3. Which AI technology is used to generate new, never-before-seen content such as images or text?

A) Generative AI
B) Supervised AI
C) Reinforcement AI
D) Predictive AI

4. 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 NetApp StorageGRID as the primary storage for the high-performance training stage.
B) Use a RAG architecture for the sales forecasting model.
C) Use BlueXP backup and recovery to perform the initial data ingest from the POS systems.
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 NetApp FlexClone to create an instantaneous, space-efficient, writable copy of the daily raw data for the data preparation stage.
F) Use NetApp XCP to efficiently aggregate the raw sales data from POS systems into the central staging area.

5. A company is running its AI training workloads on a NetApp AFF A-Series system. To manage costs, they want to automatically move inactive training datasets and older model checkpoints from the high- performance all-flash tier to a lower-cost object storage tier, such as an on- premises StorageGRID or a public cloud bucket. The process must be transparent to the data scientists and not require changes to their scripts or file paths.
Which two NetApp technologies should be combined to achieve this goal? (Choose 2.)

A) NetApp StorageGRID
B) NetApp SnapMirror
C) NetApp FlexCache
D) NetApp XCP
E) NetApp FabricPool

問題與答案：