Network Appliance NetApp Certified AI Expert Sample Questions:

1. The data science team in Azure reports that training jobs are taking longer than expected. An analysis of the Cloud Volumes ONTAP instance in Azure shows that the instance type is undersized for the I/O demands of the training workload. The architect needs to change the Azure VM instance type for the Cloud Volumes ONTAP system to a more powerful one.
The current configuration is:
Cloud_Provider: Azure
ONTAP_System: Cloud Volumes ONTAP (Single Node)
Current_Instance_Type: Standard_DS3_v2
Target_Instance_Type: Standard_E8s_v4
What is the most direct method to perform this operation using NetApp's management tools?

A) SSH to the Cloud Volumes ONTAP instance and run an ONTAP command to modify the underlying VM.
B) From the BlueXP Canvas, select the Cloud Volumes ONTAP working environment and use the
"Change Instance Type" action in the Features panel.
C) Use the Azure portal to manually change the VM instance type.
D) Terminate the existing Cloud Volumes ONTAP instance and deploy a new one with the target instance type, then restore data from backup.

2. An AI platform is suffering from poor performance during distributed training jobs. The training data resides on a single, large NFS volume. Monitoring shows that while the overall network throughput to the storage system is high, individual GPU nodes experience significant I/O wait times, and the single ONTAP volume is becoming a performance bottleneck. The goal is to re- architect the storage layout to maximize read parallelism and throughput for the training cluster.
Which two actions should the architect take to address this performance bottleneck? (Choose 2.)

A) Replace the NFS protocol with iSCSI for all training data access.
B) Increase the number of network ports connected to the storage controller.
C) Implement a NetApp FlexGroup volume to spread the dataset across multiple constituent volumes and aggregates.
D) Use NetApp FlexCache to create a local cache of the training data on each compute node.
E) Enable QoS maximums on the training volume to limit its IOPS.

3. The "Advisor Assistant" application, running as a pod in Kubernetes, suddenly cannot access its data on the AFF A-Series. The application logs show "connection timed out" errors. The network team provides a firewall log snippet for the traffic between the application pod and the storage system's NFS data LIF.
TIME | SRC_IP | DST_IP | PROTO | DST_PORT | ACTION
-|--||-|-|-
2025-07-11T16:01:10Z | 10.20.5.101 (Pod) | 10.20.10.55 (LIF) | TCP | 111 | BLOCKED 2025-07-
11T16:01:12Z | 10.20.5.101 (Pod) | 10.20.10.55 (LIF) | TCP | 2049 | BLOCKED What is the most likely cause of the connectivity failure?

A) The AFF A-Series does not support the NFS protocol.
B) The application pod has incorrect mount options configured.
C) The ONTAP system's data LIF is offline.
D) A network firewall between the pod's subnet and the storage subnet is blocking the required NFS ports.

4. A national research laboratory is investing in a turnkey AI infrastructure solution. Their primary goal is to eliminate the complexity and risk of designing and integrating the compute, network, and storage components themselves. The solution must be pre-validated by the vendors to deliver predictable, linear performance as they scale from one to multiple compute nodes. Which two options represent this type of pre-validated, converged infrastructure solution for AI? (Choose two)

A) A custom-built server rack with components sourced from various different vendors.
B) A single NetApp FAS system connected directly to a single server.
C) A Cisco and NetApp FlexPod for AI solution.
D) NetApp AIPod, which integrates NVIDIA DGX servers with NetApp storage and networking.
E) A public cloud provider's general-purpose virtual machine instances.

5. A healthcare organization plans to use a large dataset of patient records to train a predictive model. Before training, they must identify and segregate all records containing Personally Identifiable Information (PII) to comply with privacy regulations. The data resides on an on- premises NetApp ONTAP cluster. The organization needs an automated tool to scan the data in- place and tag files containing PII without moving the data.
The project requirements are as follows:
Task: Identify PII in a large dataset.
Data_Location: On-premises ONTAP cluster.
Constraint: Data must not be moved from its source location for scanning.
Output: Tagged files containing PII.
Which NetApp tool is designed for this specific task?

A) NetApp XCP
B) NetApp SnapMirror
C) NetApp BlueXP classification
D) NetApp FlexCache

Solutions: