An MLOps team uses a variety of platforms to manage their AI workloads. They need to understand the primary function of each tool within their ecosystem. Which statement best describes the role of an MLOps/LLMOps platform like Kubeflow or Run:AI?

• A.They are integrated development environments (IDEs) used exclusively for writing Python code.
• B.They are networking protocols designed to accelerate data transfer between GPUs.
• C.They are orchestration and management platforms that automate and streamline the entire AI/ML lifecycle, from data preparation and model training to deployment and monitoring.
• D.They are specialized storage systems designed to hold large datasets for training.

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Which of the following techniques are used to maximize GPU utilization in AI workloads? (Choose two)

• A.Balancing compute and storage workloads efficiently
• B.Using larger batch sizes
• C.Utilizing CPU-based workloads for all tasks
• D.Scheduling GPU-intensive tasks during off-peak hours

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Which of the following platforms can be used to manage containerized AI workloads on Kubernetes? (Choose two)

• A.TensorFlow Extended
• B.RunAI
• C.KubeFlow
• D.Google VertexAI

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A data science team works primarily at a central data center but needs to run a short-term, burst- compute training job in the public cloud to take advantage of specialized GPUs that are not available on- premises. They need to efficiently and securely move a 20 TB dataset from their on- premises ONTAP cluster to a Cloud Volumes ONTAP instance for the duration of the job.
The data flow requirement is as follows:
Source: On-premises ONTAP cluster
Destination: Cloud Volumes ONTAP in AWS
Requirement: Efficient, secure, block-level data transfer.
Which NetApp technology is the most appropriate tool for this task?

• A.NetApp SnapMirror
• B.NetApp FabricPool
• C.NetApp FlexCache
• D.NetApp XCP

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The data pipeline that updates the vector database from the StorageGRID data lake fails. An MLOps engineer uses the BlueXP API to check the status of the copy and sync job responsible for moving new documents to a staging area for processing.
The API returns the following JSON response:
{
"id": "rel_5f8g7h2k",
"volumeName": "product_docs_source",
"svmName": "svm_datalake",
"relationshipStatus": "FAILED",
"s3Location": "s3://vector-staging-bucket/latest/",
"progress": 87,
"failureMessage": "Sync failed.
Target credentials invalid. Check permissions for data broker 'db-gcp-1' on target bucket 'vector- staging-bucket'."
}
Based on this output, what is the most direct cause of the pipeline failure?

• A.The BlueXP data broker service account or role lacks the necessary IAM permissions to write to the target S3 bucket.
• B.The network connection between the data broker and the StorageGRID system is blocked by a firewall.
• C.The vector database embedding process has crashed.
• D.The source StorageGRID system is offline.

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