Which of the following environmental changes is most likely to resolve a memory constraint error when running a complex model using distributed computing?

Question

Options

• AConverting an on-premises deployment to a containerized deployment
• BMigrating to a cloud deployment
• CMoving model processing to an edge deployment
• DAdding nodes to a cluster deployment

• A
  12% (6)
• B
  8% (4)
• C
  4% (2)
• D
  76% (39)

Explanation

Increasing the number of nodes in your cluster directly expands the total available memory across the distributed system, alleviating memory-constraint errors without changing your code or deployment paradigm. Containerization or edge deployments don't inherently provide more memory, and migrating to the cloud alone doesn't guarantee additional nodes unless you explicitly scale out.

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