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Network Appliance NS0-901 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Industry Use Cases | - AI applications across industries
|
| AI and Machine Learning Fundamentals | - Algorithm types
|
| AI Infrastructure and NetApp Solutions | - AI-ready data infrastructure
|
| AI Lifecycle and Deployment | - End-to-end AI lifecycle
|
Network Appliance NetApp Certified AI Expert Sample Questions:
1. The company's compliance officer mandates that all raw simulation data in the StorageGRID data lake must be protected from modification or deletion for a period of seven years. Which two StorageGRID features should be implemented to meet this strict, long-term data immutability requirement? (Choose 2.)
A) Create a new S3 bucket with Object Lock enabled in Compliance mode.
B) Configure an Information Lifecycle Management (ILM) rule that applies to the bucket and sets a retention period of seven years.
C) Enable Autonomous Ransomware Protection (ARP) on the StorageGRID system.
D) Encrypt all objects in the bucket using server-side encryption (SSE).
E) Use NetApp SnapMirror to replicate the data to a second StorageGRID system.
2. An organization wants to provide its data science team with a secure, on-demand method for using a powerful generative AI model with their private, sensitive corporate data. The solution must ensure that the private data is never exposed to the public internet or the public LLM API endpoint.
The architect is designing a solution using BlueXP.
Which two components are essential for building this secure solution? (Choose 2.)
A) A BlueXP Connector deployed in a public subnet with a public IP address to allow access to the LLM.
B) The BlueXP GenAI Toolkit, which acts as a proxy to intercept user prompts and enrich them with data from a local vector database.
C) A private vector database hosted on an on-premises NetApp ONTAP system to store embeddings of the sensitive corporate data.
D) A policy in BlueXP classification to copy all sensitive data to a public cloud bucket for easier access.
E) A direct VPN connection from each data scientist's laptop to the public LLM provider.
3. An online retail company's recommendation engine, which provides real-time product suggestions to users, is experiencing unacceptable latency. The inference application is running on a correctly-sized edge server, but user requests are taking over 500ms to process. An architect reviews the data access pattern and infrastructure diagram.
Application_Location: Edge Server (In-store)
Data_Source_Location: Core Data Center (On-premises ONTAP)
Data_Required_for_Inference: User profile data, product catalog vectors Network_Path: Edge -> WAN -> Core Data Center Observed_Latency: 550ms What is the most likely cause of the high inference latency?
A) The on-premises ONTAP system is not configured for high-throughput.
B) The model is too large to fit into the edge server's memory.
C) Every inference request requires a high-latency round trip over the WAN to fetch data from the core data center.
D) The edge server has insufficient CPU resources to run the model.
4. An AI architect needs to design a complete, end-to-end data pipeline for a new generative AI application at a financial services firm. The application will allow internal analysts to query a massive, 500 TB archive of historical market data and reports to generate summaries. The firm has the following environment and requirements:
Data_Sources: A mix of on-premises ONTAP filers and StorageGRID S3 buckets.
Requirement_1: All queries must be answered using only the private data archive.
Requirement_2: All generated summaries must provide citations to the source reports.
Requirement_3: All data containing client PII must be identified and excluded from the LLM context.
Requirement_4: The solution must be cost-effective for the large, mostly-read data archive.
Which set of actions and technologies constitutes the most robust and compliant solution?
(Select all that apply.)
A) Implement a Retrieval-Augmented Generation (RAG) architecture to meet the requirements for private data usage and source citation.
B) Use SnapMirror to replicate the StorageGRID data lake to a high-performance NetApp ASA system for faster query performance.
C) Use NetApp XCP to perform a one-time migration of all data from the ONTAP filers to the StorageGRID data lake.
D) During the RAG retrieval step, filter out any documents tagged as containing PII by BlueXP classification before sending them to the LLM.
E) Deploy BlueXP classification to scan the entire StorageGRID data lake to identify and tag all files containing PII.
F) Fine-tune a foundation model on the entire 500 TB dataset to ensure it understands the financial context.
5. 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
Solutions:
| Question # 1 Answer: A,B | Question # 2 Answer: B,C | Question # 3 Answer: C | Question # 4 Answer: A,C,D,E | Question # 5 Answer: D |








