最も有効な NS0-901 試験参考書

An organization is planning to deploy a large AI infrastructure but wants to avoid a large, upfront capital expenditure. They prefer an operational expenditure (OpEx) model where they pay for storage and compute resources as they are consumed. They also need the flexibility to scale resources up or down based on project demands.
Which NetApp consumption model is specifically designed to meet these financial and operational requirements?

• A. A standard capital purchase of AFF and ASA systems.
• B. NetApp Cloud Volumes ONTAP PAYGO licensing only.
• C. NetApp Keystone, which provides a subscription-based, pay-as-you-go service for on-premises and cloud storage.
• D. A perpetual licensing model for all ONTAP software features.

A network administrator, attempting to harden the security of the data center, modifies a firewall access control list (ACL). Immediately afterward, the "Advisor Assistant" application pods can no longer mount their required NFS volumes from the AFF A-Series. The MLOps team confirms the pods are stuck in a 'ContainerCreating' state with a 'MountVolume.SetUp failed... connection timed out' error. The administrator provides the new, active firewall rule:
RULE | ACTION | PROTOCOL | SOURCE_IP_RANGE | DEST_IP_RANGE | DEST_PORT --|--|-
|--||--51 | ALLOW | TCP | 10.20.5.0/24 | 10.20.10.0/24 | 2049
What is the most likely reason for the mount failures?

• A. The 'SOURCE_IP_RANGE' is incorrect and does not include the Kubernetes pod IP addresses.
• B. The firewall rule is blocking the NFSv4 protocol, which requires TCP port 2050.
• C. The firewall rule is blocking the NFS lock manager (NLM) protocol, which is required for file locking.
• D. The firewall rule is blocking the Portmapper/RPCbind service (TCP/UDP port 111), which is necessary for the initial NFS mount negotiation.

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

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 E-Series system running a parallel file system like BeeGFS.
• C. A NetApp Cloud Volumes ONTAP instance in a different region.
• D. A NetApp StorageGRID object storage system.

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 NetApp ONTAP systems at the edge and NetApp SnapMirror to replicate data to the core data center.
• B. Use NetApp Snapshots on the training dataset volumes to create immutable, point-in-time versions for traceability.
• C. Use a NetApp E-Series system with a parallel file system (like BeeGFS) to provide high- performance, parallel file access for the training cluster.
• D. Use NetApp StorageGRID to create the petabyte-scale, S3-accessible data lake at the core.
• E. Use NetApp FlexCache to tier cold data from the data lake to the public cloud.
• F. Use iSCSI as the primary protocol for the data lake to ensure maximum compatibility.