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| Section | Weight | Objectives |
|---|
| AI Overview | 15% | - AI deployment models: on-premises, cloud, edge - AI, machine learning, and deep learning concepts - AI industry use cases and applications - Convergence of AI, high-performance computing, and analytics - Algorithm types: supervised, unsupervised, reinforcement learning
|
| AI Lifecycle | 27% | - Model training, inference, and optimization - Predictive vs generative AI - AI governance, ethics, and compliance - Data preparation and management for AI - AI lifecycle stages: design, training, deployment, monitoring
|
| Security, Reliability, and Operations | 15% | - Data security and access control for AI - Cost management and efficiency - Monitoring, logging, and troubleshooting AI environments - High availability and data protection
|
| Cloud and Hybrid Cloud AI Deployment | 18% | - Cloud-native AI solutions and integration - Data mobility and consistency across environments - Hybrid and multi-cloud AI architectures - NetApp cloud data services for AI
|
| NetApp AI Solutions and Architecture | 25% | - Storage architectures for AI workloads - Scalability and performance optimization for AI - ONTAP integration with AI frameworks - Data management and data pipeline design - NetApp AI-ready infrastructure components
|
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Network Appliance NetApp Certified AI Expert Exam Sample Questions (Q64-Q69):
NEW QUESTION # 64
An MLOps engineer is troubleshooting a failed Kubeflow pipeline step. The step was designed to create a clone of a dataset for a training job using the NetApp DataOps Toolkit. The pod logs for the failed pipeline step show the following:
Traceback (most recent call last):
File "create_clone.py", line 15, in <module>
clone_pvc(source_pvc_name="training-data-v2", new_pvc_name="train-job-34a-data") NameError: name 'clone_pvc' is not defined The engineer reviews the Python script for the pipeline step:
# create_clone.py
import os
from netapp_dataops.k8s import create_pvc
# Other code
print("Cloning source dataset for training run...")
clone_pvc(
source_pvc_name="training-data-v2",
new_pvc_name="train-job-34a-data"
)
print("Clone created successfully.")
What is the cause of the error?
- A. The Python script is attempting to use the 'clone_pvc' function, but it was not imported from the
'netapp_dataops.k8s' library. - B. The source PVC 'training-data-v2' does not exist.
- C. The NetApp DataOps Toolkit is not installed in the container image used for this pipeline step.
- D. The Kubernetes cluster is not running NetApp Trident.
Answer: A
NEW QUESTION # 65
An AI platform team is investigating poor I/O performance for a specific workload that involves processing hundreds of thousands of small metadata files. The application is running on a Kubernetes cluster with storage provided by a NetApp ONTAP system over NFS. Performance metrics show acceptable network throughput but very high latency for metadata operations (e.g., open, stat, close).
The current storage configuration is as follows:
Storage_System: NetApp AFF A-Series
Protocol: NFSv4.1
Workload_Profile: Metadata-intensive, many small file lookups
Observed_Issue: High latency on metadata operations, slow job completion Which storage architecture would be better suited to handle this specific metadata-intensive workload?
- A. A NetApp SnapLock-enabled volume for data protection.
- B. A NetApp Cloud Volumes ONTAP instance in a different region.
- C. A NetApp E-Series system running a parallel file system like BeeGFS.
- D. A NetApp StorageGRID object storage system.
Answer: C
NEW QUESTION # 66
An organization recently suffered a ransomware attack that encrypted several volumes on their primary ONTAP storage system, including a critical volume containing curated training data. The security team needs to implement a solution that can proactively detect and block ransomware- like file I/O patterns and automatically create a secure Snapshot copy before any damage is done.
The current ONTAP configuration is as follows:
ONTAP_Version: 9.12.1
Security_Features: SnapLock (Compliance Mode) on archive volumes
Anti-Virus_Scan: Enabled (Vscan)
Ransomware_Detection: Not configured
Which ONTAP feature should be enabled to provide this proactive, automated protection?
- A. Increase the frequency of scheduled Snapshots.
- B. Enable Autonomous Ransomware Protection (ARP).
- C. Use BlueXP backup and recovery to back up the volumes to the cloud more frequently.
- D. Enable Multi-Admin Verification (MAV) on all volumes.
Answer: B
NEW QUESTION # 67
A pharmaceutical company is creating a "digital twin" of its manufacturing process. This involves running complex simulations (an HPC workload) that generate massive datasets.
The company wants to use this data immediately for two other purposes:
1. Analytics: Business analysts need to run complex queries on the simulation output using tools like Spark.
2. AI Training: Data scientists need to use the same output as a training set for a predictive maintenance model.
The company wants to avoid creating separate data silos for each workload.
Which two NetApp technologies are best suited for building a unified data lake that can efficiently serve all three workloads (HPC, Analytics, AI)? (Choose 2.)
- A. NetApp SnapCenter to create application-consistent backups of the data.
- B. NetApp Autonomous Ransomware Protection to secure the data from modification.
- C. NetApp Keystone to provide a flexible, pay-as-you-go consumption model for the infrastructure.
- D. NetApp StorageGRID to provide a scalable, S3-native object store that integrates directly with modern analytics platforms like Spark.
- E. NetApp ONTAP with FlexGroup volumes to provide high-throughput, parallel NFS access for the HPC and AI training workloads.
Answer: D,E
NEW QUESTION # 68
A security administrator is reviewing the configuration of a production ONTAP cluster after a compliance audit. The audit requires that all volumes containing financial data must be protected against ransomware. The administrator runs a command to check the status of Autonomous Ransomware Protection (ARP) on a critical volume.
The command and its output are as follows:
cluster-1::> security ransomware anti-ransomware show -vserver svm_finance -volume finance_q1_data Vserver: svm_finance Volume: finance_q1_data Autonomous Ransomware Protection Status: disabled Learning Mode: normal Dry Run Mode: false Action on Detection: notify Based on this output, what is the primary security risk for the 'finance_q1_data' volume?
- A. The learning mode is set to "normal," which may not detect zero-day attacks.
- B. The volume is vulnerable to ransomware because Autonomous Ransomware Protection is not enabled.
- C. The volume is not part of any Snapshot schedule.
- D. The action on detection is set only to "notify," which will not block the attack.
Answer: B
NEW QUESTION # 69
......
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