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Network Appliance NS0-901 Exam Syllabus Topics:

Network Appliance NetApp Certified AI Expert Sample Questions:

1. A training job on one of the NVIDIA DGX servers is running slowly. A performance engineer runs the 'dstat' command on the server and captures the following output during the job execution.
-total-cpu-usage- -dsk/total- -net/total- paging-- system-- usr sys idl wai hiq siq| read writ| recv send| in out | int csw 15 5 70 10 0 0| 1.2G 15.0M| 1.2G 12.0M| 0 0 | 15k 35k
14 6 69 11 0 0| 1.2G 14.3M| 1.2G 11.8M| 0 0 | 14k 33k
16 5 68 11 0 0| 1.2G 16.1M| 1.2G 13.1M| 0 0 | 16k 36k
The server is connected to the NetApp ASA via a 100GbE (12.5 GB/s) network.
What is the most likely performance bottleneck based on this data?

A) The storage system (ASA) is unable to provide sufficient read throughput.
B) The server's network interface is saturated.
C) The server's CPU is overloaded.
D) The application is experiencing excessive memory paging.

2. An AI team is embarking on a project to train a new, large-scale computer vision model from scratch. The lead architect emphasizes that the success of the project depends on four fundamental inputs that must be available and managed throughout the training process. Which of the following are the four essential requirements for model generation?

A) A pre-trained model, a validation set, an inference engine, and a cloud provider.
B) A data lake, a data warehouse, a data pipeline, and a data mart.
C) Data, code, compute, and time.
D) A project manager, a data scientist, a software engineer, and a budget.

3. A data scientist needs to test a new data normalization technique. To do this, they require an isolated, writable copy of a 50 TB curated simulation dataset that resides on the NetApp ASA system. The operation must be completed as quickly as possible and consume minimal additional storage space. Which NetApp technology is the most appropriate solution for this requirement?

A) NetApp FlexClone
B) NetApp FabricPool
C) NetApp SnapMirror
D) NetApp XCP

4. A university is building a shared AI research platform. They have two primary requirements:
1. Performance: A "hot" research area for active model training and development that requires the absolute lowest latency and highest throughput to support multiple, simultaneous GPU- intensive jobs.
The data in this area is around 50 TB.
2. Capacity & Cost: A "cold" data lake to store over 5 PB of raw, unstructured experimental data that is infrequently accessed but must be retained for compliance and future use. This tier must be as costeffective as possible.
Which combination of NetApp hardware and technologies should an architect select to build a complete, optimized, and cost-effective solution? (Select all that apply.)

A) Use a standard 10GbE network for all connectivity to reduce costs.
B) Implement NetApp FabricPool to automatically tier inactive data from the ASA system to the StorageGRID data lake.
C) Use a NetApp All-SAN Array (ASA) system for the 50 TB high-performance "hot" research area.
D) Use NetApp E-Series systems for both the hot tier and the cold data lake to simplify management.
E) Enable GPUDirect Storage on the ASA system to provide the lowest latency data path to the GPUs.
F) Use NetApp StorageGRID to build the 5 PB cost-effective data lake.

5. Which of the following best describes the difference between data lakes, data warehouses, and lakehouses?

A) Data lakes store structured data, data warehouses store unstructured data, and lakehouses store only real-time data.
B) Data lakes store raw, unstructured data, data warehouses store structured data, and lakehouses combine the features of both.
C) Data lakes store data in cloud storage, data warehouses store it in traditional databases, and lakehouses store it in external drives.
D) Data lakes store metadata, data warehouses store transaction data, and lakehouses store archival data.

Solutions: