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Network Appliance NS0-901 Exam Syllabus Topics:

Network Appliance NetApp Certified AI Expert Sample Questions:

1. 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 is for smaller-scale AI workloads, while C-Series supports large-scale, high-performance AI applications.
C) C-Series supports both file and object-based storage, while A-Series is optimized for object storage.
D) A-Series provides GPU-based acceleration, while C-Series only supports CPU-based workloads.

2. An organization's AI platform team needs to provide two distinct tiers of storage for their data scientists on a single Kubernetes cluster:
1. 'gold-tier': Extremely low-latency storage for active model training, using an all-flash NetApp ASA system.
2. 'bronze-tier': Cost-effective, high-capacity storage for data staging and archiving, using a NetApp StorageGRID system.
How should the platform team configure NetApp Trident to meet these requirements? (Select all that apply.)

A) Create two separate Trident backend configurations, one for the ASA ('backend-asa.yaml') and one for StorageGRID ('backend-sgrid.yaml').
B) Create a single StorageClass named 'multi-tier-storage' that references both backends.
C) Create two distinct StorageClasses, 'gold-tier' and 'bronze-tier'.
D) Create a single Trident backend that points to both the ASA and StorageGRID systems simultaneously.
E) Configure the 'gold-tier' StorageClass to reference the ASA backend.
F) Configure the 'bronze-tier' StorageClass to reference the StorageGRID backend.

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

4. The data anonymization job, running in a Kubernetes pod, fails. The pod logs show a "Permission Denied" error when trying to access the source volume on the on-premises ASA. An administrator checks the export policy rule for the volume.
The active rule is as follows:
Rule_Index: 1
Client_Match: 10.50.0.0/16
Protocols: nfs4
Read_Only_Access: sys
Read_Write_Access: -
Superuser_Access: none
The Kubernetes pod that failed has an IP address of '10.60.5.10'.
What is the cause of the "Permission Denied" error?

A) The pod's IP address ('10.60.5.10') is not within the allowed client match range ('10.50.0.0/16').
B) The 'Superuser_Access' setting is too restrictive.
C) The export policy only allows access via the NFSv4 protocol.
D) The export policy does not grant read-write access, which is required by the anonymization job.

5. 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) Deploy a single, global NetApp StorageGRID across all three locations to act as a unified data plane.
B) Use Cloud Volumes ONTAP at the edge, NetApp StorageGRID at the core, and on-premises ONTAP for cloud archive.
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 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.

Solutions: