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Network Appliance NS0-901 Exam Syllabus Topics:

Network Appliance NetApp Certified AI Expert Sample Questions:

1. The Chief Information Security Officer (CISO) is concerned about the risk of a ransomware attack encrypting the critical vector database hosted on the NetApp AFF A-Series. The CISO wants a solution that can proactively detect and block a live attack in real-time, not just recover from a backup after the fact.
Which NetApp security feature should the architect enable on the vector database volume to meet this requirement?

A) Autonomous Ransomware Protection (ARP)
B) NetApp Volume Encryption (NVE)
C) Multi-Admin Verification (MAV)
D) NetApp SnapLock (Compliance Mode)

2. The firm's data science team needs to run a high-priority, interactive model analysis job that requires immediate access to two GPUs. However, all GPUs in the cluster are currently allocated to long-running, lower-priority batch training jobs.
The MLOps platform, Run:AI, shows the following queue status:
JOB_ID | PROJECT | STATUS | PRIORITY | GPU_ALLOCATED
||--|-|
batch_job_1 | team_a | Running | Low | 2
batch_job_2 | team_a | Running | Low | 2
batch_job_3 | team_b | Running | Low | 4
interactive_1| team_c | Pending | High | 2 (requested)
How does the Run:AI platform address this resource contention to allow the high-priority job to run?

A) It automatically pauses one of the low-priority jobs, saves its state, and allocates its GPUs to the high- priority job, placing the paused job back in the queue.
B) It sends an email notification to the administrator to manually reallocate the GPUs.
C) It automatically terminates all low-priority jobs to free up the entire cluster.
D) It keeps the high-priority job in a pending state until the low-priority jobs complete naturally.

3. A research lab uses a fleet of autonomous drones to collect high-resolution aerial imagery for agricultural analysis. The drones land at a remote edge location and offload their data. The AI models for image analysis are trained at a central data center. The team is using NetApp SnapMirror to replicate the data from the edge to the core. However, the data scientists are complaining that the datasets arriving at the data center are often incomplete or corrupted.
An administrator reviews the SnapMirror configuration and status via the BlueXP API:
{
"source": { "workingEnvironmentId": "OnPrem-Edge-Filer-1", "volumeName": "drone_data_raw" },
"destination": { "workingEnvironmentId": "Core-Datacenter-A800", "volumeName":
"drone_data_replicated" },
"mirrorState": "broken-off",
"relationshipStatus": "idle",
"unhealthyReason": "Transfer failed. Destination volume is out of space.", "lastTransferInfo": {
"transferError": "No space left on device"
}
}
What is the direct cause of the incomplete datasets at the data center?

A) The source volume at the edge location has become corrupted.
B) The SnapMirror relationship is broken because the destination volume at the core data center has run out of capacity.
C) The network connection between the edge and the core is unreliable.
D) The BlueXP Connector does not have the correct permissions to manage the SnapMirror relationship.

4. Which of the following are typical requirements for inferencing in AI models? (Choose two)

A) Extensive training data
B) Cloud-based inference only
C) Loading the model into memory
D) Pre-trained models

5. An MLOps team is using the BlueXP Workload Factory to automate the deployment of a Jupyter notebook environment for a new data scientist. The deployment job fails. The team reviews the job details in the BlueXP UI.
Job ID: 78a1c-2b3d-4e5f
Service: BlueXP Workload Factory
Action: Deploy JupyterHub on Kubernetes
Status: FAILED
Error Message: "Failed to create PersistentVolumeClaim 'jupyter-pvc-user01'.
User 'service-account- bluexp' does not have permission to 'create' resource
'persistentvolumeclaims' in cluster 'k8s-prod- cluster-01'."
What is the most direct way to resolve this issue?

A) Modify the Kubernetes RBAC (Role-Based Access Control) configuration to grant the 'service- account-bluexp' the necessary permissions to create PVCs in the target cluster.
B) Increase the storage quota for the 'jupyter-pvc-user01' PVC.
C) Restart the BlueXP Connector to refresh its permissions.
D) Manually create the PersistentVolumeClaim using 'kubectl'.

Solutions: