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Network Appliance NS0-901 Exam Syllabus Topics:

Network Appliance NetApp Certified AI Expert Sample Questions:

Question 1

In the data pipeline, which NetApp technology is used to create an efficient, block-level, incremental replication of the anonymized datasets from the on-premises ASA to the Cloud Volumes ONTAP instance in Azure?

A. NetApp BlueXP copy and sync
B. NetApp FabricPool
C. NetApp XCP
D. NetApp SnapMirror

Question 2

An architect is explaining different data storage paradigms to a new data engineering team. The team needs to understand where to store different types of data for their AI projects. Which statement accurately describes a key difference between a data lake and a data warehouse?

A. A data lake stores structured, processed data for fast querying, while a data warehouse stores raw, unstructured data in its native format.
B. A data lake is only for on-premises deployments, while a data warehouse is only for cloud deployments.
C. A data lake uses a schema-on-write approach, while a data warehouse uses a schema-on-read approach.
D. A data lake is designed to store vast quantities of raw, multi-format data (structured, semi- structured, and unstructured), while a data warehouse is typically used for storing structured and filtered data that has already been processed for a specific purpose.

Question 3

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?

A. A NAS filer cannot be deployed on-premises.
B. A traditional scale-up NAS system will face scalability and cost-effectiveness challenges at the petabyte scale compared to an object storage system.
C. The S3 API cannot be used to access data stored on an NFS file system.
D. NFS is incapable of storing image or video files.

Question 4

Given the company's goal of combining physics-based simulations with AI-driven analytics on a shared data foundation, which industry trend does this project best represent?

A. The replacement of all physical testing with digital simulations.
B. The convergence of AI, High-Performance Computing (HPC), and analytics on a unified data infrastructure.
C. The exclusive use of public cloud resources for all computational tasks.
D. The separation of AI and HPC into dedicated, air-gapped environments.

Question 5

Due to the success of the "Advisor Assistant," the number of concurrent users is expected to double in the next quarter. The existing Kubernetes cluster is running at 80% of its GPU capacity during peak hours. The architect must propose a plan to scale the compute infrastructure to handle the increased load.
Which two strategies represent the most effective and scalable solutions? (Choose 2.)

A. Manually deploy all new application replicas to a single, new, very large "super-node".
B. Horizontally scale the cluster by adding new GPU-equipped nodes.
C. Replace all existing GPUs with the next-generation model to increase the performance of each node.
D. Configure the Kubernetes Cluster Autoscaler to automatically add new nodes to the cluster from a predefined node pool when GPU demand exceeds current capacity.
E. Vertically scale the existing nodes by adding more RAM and CPU cores to each one.

Solutions: