Describe the Uses of BlueXP Software Tools to Build AI Solutions CERTIFIED-AI-EXPERT Practice Questions (Page 5)

Questions 21–25

1. 21foundation · easy

   Which statement best describes the primary role of BlueXP in an AI solution environment?

   • AIt is a model training framework that runs deep learning algorithms on GPU clusters.
   • BIt is a unified control plane for managing and orchestrating data storage services across on-premises and cloud environments.
   • CIt is a monitoring agent that tracks GPU utilization and model accuracy during training.
   • DIt is a data labeling tool that automatically annotates training datasets for supervised learning.
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2. 22expert · hard

   A company is deploying an AI solution that requires storage in both on-premises and multiple cloud providers. They want to use BlueXP to manage storage consistently across all environments, but they also need to ensure that data can be moved between environments without manual intervention. Which BlueXP feature should they use to automate data movement?

   • ABlueXP backup to manually copy data between environments.
   • BBlueXP data replication and sync capabilities to automate data movement between environments.
   • CBlueXP compliance to ensure data is compliant during movement.
   • DBlueXP cost optimizer to reduce costs during data movement.
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4. 23expert · hard

   A company uses BlueXP to manage AI training data that is stored on-premises. They want to use cloud compute for training but are concerned about the cost of egressing data to the cloud. They also need to ensure that data is encrypted during transfer. Which BlueXP feature should they use to minimize egress costs while ensuring secure transfer?

   • AUse BlueXP compliance to ensure data is encrypted before transfer.
   • BUse BlueXP backup to transfer data to the cloud for training.
   • CUse BlueXP tiering to move all data to the cloud permanently.
   • DUse BlueXP Cloud Cache to cache data in the cloud, reducing the need to transfer the entire dataset.
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5. 24expert · hard

   A data science team uses a Kubernetes-based AI pipeline that requires dynamic storage provisioning. They want to use BlueXP to manage storage for their pipeline, but they also need to ensure that storage can scale automatically as training jobs increase. Which BlueXP integration should they use to meet this requirement?

   • AUse BlueXP's Kubernetes integration to provision storage dynamically via CSI drivers.
   • BUse BlueXP backup to create storage snapshots for each job.
   • CManually create storage volumes for each training job.
   • DUse BlueXP tiering to move data to object storage for each job.
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6. 25foundation · easy

   Which BlueXP data management capability is most useful for ensuring that an AI training dataset is available in multiple locations for low-latency access?

   • AReplication
   • BTiering
   • CSnapshotting
   • DDeduplication
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