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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) A-Series provides GPU-based acceleration, while C-Series only supports CPU-based workloads.
D) C-Series supports both file and object-based storage, while A-Series is optimized for object storage.
2. 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 FlexClone to create an instantaneous, space-efficient, writable copy of the daily raw data for the data preparation stage.
B) Use NetApp StorageGRID as the primary storage for the high-performance training stage.
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 a RAG architecture for the sales forecasting model.
F) Use NetApp XCP to efficiently aggregate the raw sales data from POS systems into the central staging area.
3. A data science team works primarily at a central data center but needs to run a short-term, burst- compute training job in the public cloud to take advantage of specialized GPUs that are not available on- premises. They need to efficiently and securely move a 20 TB dataset from their on- premises ONTAP cluster to a Cloud Volumes ONTAP instance for the duration of the job.
The data flow requirement is as follows:
Source: On-premises ONTAP cluster
Destination: Cloud Volumes ONTAP in AWS
Requirement: Efficient, secure, block-level data transfer.
Which NetApp technology is the most appropriate tool for this task?
A) NetApp SnapMirror
B) NetApp FlexCache
C) NetApp FabricPool
D) NetApp XCP
4. The firm decides to expand the "Advisor Assistant" project to a new team in a different department. This team needs its own isolated environment. An MLOps engineer attempts to submit a new GPU- intensive job for the new team, but it remains pending. The engineer checks the Run:AI scheduler logs and finds the following entry:
time="2025-07-11T16:45:00Z" level=info msg="Job ds-new-team-job1 cannot be scheduled.
Project 'new-team-project' has exceeded its GPU quota. Quota: 0, Requested: 1, Used: 0." What is the root cause of the scheduling failure?
A) The job is requesting a specific type of GPU that is not available in the cluster.
B) A Run:AI project quota has been configured for the new team, but it has been set to zero, effectively blocking them from using any GPU resources.
C) The Run:AI scheduler is offline and cannot process new jobs.
D) The Kubernetes cluster has no available GPUs.
5. 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 private vector database hosted on an on-premises NetApp ONTAP system to store embeddings of the sensitive corporate data.
B) A policy in BlueXP classification to copy all sensitive data to a public cloud bucket for easier access.
C) The BlueXP GenAI Toolkit, which acts as a proxy to intercept user prompts and enrich them with data from a local vector database.
D) A direct VPN connection from each data scientist's laptop to the public LLM provider.
E) A BlueXP Connector deployed in a public subnet with a public IP address to allow access to the LLM.
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: A,D,F | Question # 3 Answer: A | Question # 4 Answer: B | Question # 5 Answer: A,C |
