2026 Updated Verified Pass NS0-901 Exam - Real Questions and Answers
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NEW QUESTION # 46
What is the primary difference between C-Series and A-Series storage for AI workloads?
- A. C-Series supports both file and object-based storage, while A-Series is optimized for object storage.
- B. A-Series is for smaller-scale AI workloads, while C-Series supports large-scale, high-performance AI applications.
- C. C-Series is designed for high-performance workloads, while A-Series focuses on cost-efficiency for general storage.
- D. A-Series provides GPU-based acceleration, while C-Series only supports CPU-based workloads.
Answer: C
NEW QUESTION # 47
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 StorageGRID to provide a scalable, S3-native object store that integrates directly with modern analytics platforms like Spark.
- C. NetApp Autonomous Ransomware Protection to secure the data from modification.
- D. NetApp Keystone to provide a flexible, pay-as-you-go consumption model for the infrastructure.
- E. NetApp ONTAP with FlexGroup volumes to provide high-throughput, parallel NFS access for the HPC and AI training workloads.
Answer: B,E
NEW QUESTION # 48
An architect is designing a fully automated, end-to-end MLOps pipeline on Kubernetes for a computer vision use case. The pipeline must handle everything from data versioning to model deployment.
The required pipeline stages are:
1. Data Versioning: Create a new, immutable version of the master dataset for the pipeline run.
2. Data Preparation: Launch a pod to run a preprocessing script on the versioned data.
3. Model Training: Launch a distributed training job that reads the prepared data from a highperformance volume.
4. Model Deployment: Push the trained model to a production inference service.
Which combination of NetApp and Kubernetes technologies provides the most effective and automated solution for this entire pipeline?
- A. Use NetApp XCP to copy the data for each stage and configure static PersistentVolumes for each pod.
- B. Use the NetApp DataOps Toolkit to create a Snapshot of the source data volume (for versioning), then create a FlexClone PVC from the snapshot for the preparation stage, and finally create a FlexGroup PVC for the training stage.
- C. Use NetApp SnapMirror for data versioning and manually create hostPath volumes for each pipeline stage.
- D. Manually create a NetApp Snapshot via System Manager before each pipeline run, and use the NetApp DataOps Toolkit only for the training stage.
- E. Use a single, large ReadWriteMany PVC for all stages to simplify the pipeline configuration.
Answer: B
NEW QUESTION # 49
Which storage protocols are commonly used for handling large-scale AI data? (Choose two)
- A. POSIX-based file systems
- B. Parallel file systems
- C. File-based systems
- D. Object-based storage
Answer: B,D
NEW QUESTION # 50
Which of the following platforms can be used to manage containerized AI workloads on Kubernetes? (Choose two)
- A. RunAI
- B. Google VertexAI
- C. TensorFlow Extended
- D. KubeFlow
Answer: A,D
NEW QUESTION # 51
A data scientist needs to test a new data normalization technique. To do this, they require an isolated, writable copy of a 50 TB curated simulation dataset that resides on the NetApp ASA system. The operation must be completed as quickly as possible and consume minimal additional storage space. Which NetApp technology is the most appropriate solution for this requirement?
- A. NetApp FlexClone
- B. NetApp SnapMirror
- C. NetApp FabricPool
- D. NetApp XCP
Answer: A
NEW QUESTION # 52
An MLOps engineer is deploying a training pod that requires a high-performance volume. After applying the pod and PVC manifests, the pod remains in a 'Pending' state. The engineer runs
'kubectl describe pod training-pod-7d8c' and sees the following event:
Events:
Type Reason Age From Message
- - - -
Warning FailedScheduling 2m15s
default-scheduler 0/4 nodes are available: 1 node(s) had volume node affinity conflict, 3 node(s) didn't find available persistent volume to bind.
The engineer then inspects the associated PVC and sees its status is also 'Pending'.
What is the most likely cause of this issue?
- A. The Kubernetes scheduler is malfunctioning and cannot assign pods to nodes.
- B. The Trident controller pod has crashed and needs to be restarted.
- C. The ONTAP backend is out of available capacity to provision a new volume.
- D. The 'storageClassName' specified in the PVC does not match any existing StorageClass managed by Trident.
Answer: D
NEW QUESTION # 53
An AI platform administrator is trying to deploy a new GenAI toolkit using the BlueXP Workload Factory. The deployment fails, and the administrator examines the API response from BlueXP.
{
"jobId": "we-deploy-genai-987zy",
"status": "FAILED",
"statusCode": 403,
"message":
"Forbidden: The service principal or user account used by the Connector does not have the required permissions on the target subscription to create a new resource group.
Required permission: 'Microsoft.Resources/subscriptions/resourcegroups/write'." } Based on this API response, what is the root cause of the deployment failure?
- A. The BlueXP Connector is offline and cannot communicate with the cloud provider.
- B. The GenAI toolkit requires a specific license that has not been added to the BlueXP digital wallet.
- C. The selected ONTAP version does not support the GenAI toolkit.
- D. The Azure service principal associated with the BlueXP Connector lacks the necessary IAM role to create resource groups.
Answer: D
NEW QUESTION # 54
An AI infrastructure architect is tasked with designing a solution to address two critical challenges in a large, multi-petabyte AI environment:
1. Cost: A significant portion of the data on the high-performance all-flash storage is inactive but must remain online. The cost of storing this cold data on the performance tier is prohibitive.
2. Traceability: Data scientists need a simple, space-efficient way to version their datasets at key points in their workflow to ensure reproducibility.
The environment consists of NetApp AFF A-Series and NetApp StorageGRID systems.
Which combination of NetApp technologies should the architect implement to solve both challenges simultaneously? (Select all that apply.)
- A. Implement NetApp FlexClone to create full, writable copies of datasets for each experiment.
- B. Use NetApp SnapMirror to replicate volumes from the AFF systems to StorageGRID for archival.
- C. Use NetApp XCP to periodically move cold data from the AFF systems to StorageGRID.
- D. Train data scientists to use NetApp Snapshots to create point-in-time, read-only versions of their data volumes.
- E. Use BlueXP backup and recovery to create backups on StorageGRID, then delete the original volumes from the AFF systems.
- F. Implement NetApp FabricPool to automatically tier cold data blocks from the AFF systems to StorageGRID.
Answer: D,F
NEW QUESTION # 55
A junior administrator is attempting to delete an old, unused Snapshot copy from a production volume to reclaim space but receives an error. The administrator is certain they are using the correct command and have the appropriate 'vsadmin' role.
The command and error are shown below:
cluster-1::> volume snapshot delete -vserver svm_prod -volume app_data -snapshot nightly.2025- 06-15_0015 Error: command failed: This operation is not permitted. Deletion of Snapshot copy "nightly.2025-
06-15_0015" on volume "app_data" in Vserver "svm_prod" requires approval.
Use the "security multi-admin-verify approval show" command to view pending approvals.
What is the most likely reason the administrator cannot delete the Snapshot?
- A. The 'vsadmin' role does not have permission to delete Snapshots.
- B. The volume is protected by SnapLock, and the Snapshot has not reached its expiry date.
- C. The Snapshot is locked by a SnapMirror relationship.
- D. Multi-Admin Verification (MAV) is enabled, and the destructive operation requires approval from another designated administrator.
Answer: D
NEW QUESTION # 56
The HPC cluster generates simulation data at an extremely high rate, requiring a storage system that can handle massively parallel writes from hundreds of compute nodes simultaneously. Which storage system and file protocol combination is the most appropriate choice for the HPC cluster's high-performance scratch space?
- A. A Cloud Volumes ONTAP instance with a standard file system.
- B. A NetApp E-Series system serving a BeeGFS parallel file system.
- C. A NetApp StorageGRID system accessed via the S3 protocol.
- D. A NetApp ASA system serving a single, large NFS volume.
Answer: B
NEW QUESTION # 57
An architect is designing a global infrastructure for a company that develops AI for autonomous vehicles.
The design must accommodate three distinct locations and functions:
1. Edge (Test Tracks): Fleets of test cars generate 100s of TBs of sensor data per day. This data must be ingested locally with high performance.
2. Core (Primary Data Center): The raw data from all edge sites must be aggregated here. This location houses the primary data lake and the main GPU cluster for large-scale model training.
3. Cloud (Public Cloud Provider): Data scientists want to use cloud-native tools for experimental data processing and model development. They also need a cost-effective location for long-term archiving of raw data.
Which combination of deployment locations and NetApp technologies creates the most logical and efficient end-to-end solution?
- A. Use NetApp E-Series at the edge, NetApp ASA at the core, and NetApp StorageGRID in the cloud.
Use SnapMirror to move data between all three tiers. - B. Use NetApp ONTAP systems at the edge and core, and Cloud Volumes ONTAP in the public cloud.
Use SnapMirror to replicate data from edge to core, and FabricPool to tier data from the core to the cloud. - C. Use Cloud Volumes ONTAP at the edge, NetApp StorageGRID at the core, and on-premises ONTAP for cloud archive.
- D. Deploy a single, global NetApp StorageGRID across all three locations to act as a unified data plane.
Answer: B
NEW QUESTION # 58
To meet HIPAA compliance, the first step in the data pipeline is to identify all medical scans that contain embedded PII. The solution must be automated and capable of scanning data in-place on the on-premises ASA system.
Which two technologies should be used to accomplish this identification and tagging task?
(Choose 2.)
- A. NetApp BlueXP classification, configured to scan the on-premises ASA working environment.
- B. A custom Python script that uses regular expressions to search file contents.
- C. A custom "PII" category within BlueXP classification to identify specific medical record number formats.
- D. A manual review process where technicians visually inspect each scan for PII.
- E. NetApp SnapLock to make the source data immutable before scanning.
Answer: A,C
NEW QUESTION # 59
An architect is designing a comprehensive AI platform for a large enterprise. The platform must support the entire data lifecycle, from ingest at the edge to a central data lake, and finally to a high- performance training cluster.
The requirements are:
- Edge Ingest: Data must be collected at remote sites and efficiently replicated to the core.
- Data Lake: A central, petabyte-scale repository for unstructured data, accessible via the S3 protocol.
- Training Cluster: A high-performance compute cluster that requires low-latency, parallel file access to training datasets.
- Data Traceability: All datasets used for training must be immutably versioned.
Which combination of NetApp technologies and protocols should the architect choose to build this solution? (Select all that apply.)
- A. Use iSCSI as the primary protocol for the data lake to ensure maximum compatibility.
- B. Use NetApp Snapshots on the training dataset volumes to create immutable, point-in-time versions for traceability.
- C. Use NetApp ONTAP systems at the edge and NetApp SnapMirror to replicate data to the core data center.
- D. Use NetApp StorageGRID to create the petabyte-scale, S3-accessible data lake at the core.
- E. Use a NetApp E-Series system with a parallel file system (like BeeGFS) to provide high- performance, parallel file access for the training cluster.
- F. Use NetApp FlexCache to tier cold data from the data lake to the public cloud.
Answer: B,C,D,E
NEW QUESTION # 60
Which of the following applications use AI in the healthcare industry? (Choose two)
- A. Managing hospital supply chains
- B. Predicting patient outcomes
- C. Diagnosing diseases
- D. Automating financial reporting
Answer: B,C
NEW QUESTION # 61
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. Use NetApp FlexCache to create a local cache of the training data on each compute node.
- B. Increase the number of network ports connected to the storage controller.
- C. Replace the NFS protocol with iSCSI for all training data access.
- D. Implement a NetApp FlexGroup volume to spread the dataset across multiple constituent volumes and aggregates.
- E. Enable QoS maximums on the training volume to limit its IOPS.
Answer: A,D
NEW QUESTION # 62
An AI architect is planning the resource allocation for a new project. The primary task is to process millions of unlabeled customer reviews to identify naturally occurring groups or themes without any prior guidance.
The project requirements are summarized below:
Task: Discover hidden patterns in text data
Input_Data: 10 million unlabeled text reviews
Output: Clustered groups of related reviews
Supervision: None
Which type of machine learning algorithm is required for this task?
- A. Reinforcement learning
- B. Supervised learning
- C. Unsupervised learning
- D. Predictive learning
Answer: C
NEW QUESTION # 63
An architect is designing a cost-optimized storage solution for a large AI environment that has two distinct data temperature profiles:
1. Hot Data (200 TB): Actively used training sets and models requiring all-flash performance.
2. Cold Data (2 PB): Inactive, archived datasets and old model versions that must remain online but are infrequently accessed.
The solution must automatically manage data placement based on activity, without requiring manual intervention or changes to file paths. The environment consists of an on-premises data center and a public cloud account.
Which combination of NetApp technologies provides the most complete and cost-effective solution? (Select all that apply.)
- A. Deploy a single, large Cloud Volumes ONTAP instance to hold both the hot and cold data tiers.
- B. Deploy NetApp StorageGRID on-premises to serve as a cost-effective capacity tier for the cold data.
- C. Use NetApp SnapMirror to create a full copy of the 2 PB of cold data on the AFF A-Series for faster access if needed.
- D. Deploy a NetApp AFF A-Series system on-premises to serve as the high-performance tier for the hot data.
- E. Use NetApp FabricPool to automatically and transparently tier cold data blocks from the AFF A- Series to the StorageGRID system.
- F. Use NetApp XCP to manually script the daily movement of cold files from the AFF system to StorageGRID.
Answer: B,D,E
NEW QUESTION # 64
A data scientist is working on a new model and needs a flexible environment for interactive data exploration, code development, and quick visualizations. A DevOps engineer is responsible for deploying the finalized model into a production pipeline that must run automatically every night without manual intervention.
Which tools are best suited for each of these roles?
- A. Both the data scientist and the DevOps engineer should use automated production pipelines.
- B. Both the data scientist and the DevOps engineer should use Jupyter Notebooks.
- C. The data scientist should use a Jupyter Notebook, and the DevOps engineer should use an automated production pipeline (e.g., Kubeflow Pipelines, Airflow).
- D. The data scientist should use a production pipeline, and the DevOps engineer should use a Jupyter Notebook.
Answer: C
NEW QUESTION # 65
Which of the following techniques are used to maximize GPU utilization in AI workloads? (Choose two)
- A. Balancing compute and storage workloads efficiently
- B. Utilizing CPU-based workloads for all tasks
- C. Using larger batch sizes
- D. Scheduling GPU-intensive tasks during off-peak hours
Answer: A,D
NEW QUESTION # 66
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 volume is not part of any Snapshot schedule.
- B. The learning mode is set to "normal," which may not detect zero-day attacks.
- C. The action on detection is set only to "notify," which will not block the attack.
- D. The volume is vulnerable to ransomware because Autonomous Ransomware Protection is not enabled.
Answer: D
NEW QUESTION # 67
A financial services company is required by regulators to be able to trace any version of their deployed fraud detection model back to the exact dataset and source code commit used to train it.
The current MLOps workflow is as follows:
Code_Repository: Git (commit hash: a1b2c3d4)
Dataset_Location: /vol/prod_data/fraud_dataset_v3
Storage_System: NetApp ONTAP 9
Model_Output: /vol/models/fraud_model_v3.2
Which NetApp technology should be used to create an immutable, point-in-time, and space- efficient copy of the dataset that can be linked to the specific code commit and model version?
- A. NetApp FlexClone
- B. NetApp SnapMirror
- C. NetApp FabricPool
- D. NetApp Snapshots
Answer: D
NEW QUESTION # 68
A financial services company has deployed a real-time fraud detection model at the edge. The model is designed for low-latency inference. However, monitoring reports indicate that the infrastructure costs are excessively high, and GPU utilization is consistently low. The architect reviews the deployment configuration.
Instance_Type: NVIDIA DGX A100 (8 GPUs)
Storage_Tier: High-Performance All-Flash (NetApp ASA)
Network: 100GbE RoCE
GPU_Utilization_Avg: 5%
Monthly_Cost: $15,000
Workload_Profile: Low-volume, sporadic, real-time predictions
What is the most likely cause of the high costs and low utilization?
- A. The compute and storage infrastructure is sized for a large-scale training workload, not a lightweight inference workload.
- B. The storage tier is too slow, causing the GPUs to wait for data.
- C. The network latency is too high for an edge deployment.
- D. The model was trained using supervised learning, which is inefficient for fraud detection.
Answer: A
NEW QUESTION # 69
What is the primary architectural advantage of using a NetApp AIPod with NVIDIA DGX servers for the AI training cluster, as described in the scenario?
- A. It prioritizes CPU performance over GPU performance for traditional machine learning algorithms.
- B. It exclusively uses object storage, which simplifies access for data scientists using S3-native tools.
- C. It is a reference architecture that is pre-validated by NetApp and NVIDIA to eliminate design complexity and ensure predictable performance for AI workloads.
- D. It is designed for small-scale, departmental AI projects and cannot be scaled.
Answer: C
NEW QUESTION # 70
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 BlueXP Connector does not have the correct permissions to manage the SnapMirror relationship.
- C. The network connection between the edge and the core is unreliable.
- D. The SnapMirror relationship is broken because the destination volume at the core data center has run out of capacity.
Answer: D
NEW QUESTION # 71
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