How can Kubernetes infrastructure enhance the functionality of SAP AI Core? There are 3 correct answers to this question.

Question

Options

• ABy automatically developing Al models without human intervention
• BBy ensuring high availability and fault tolerance for applications
• CBy supporting autoscaling of containers based on demand
• DBy eliminating the requirement for Docker containers
• EBy enabling the allocation of GPU resources for Al models

• A
  5% (1)
• B
  80% (16)
• D
  15% (3)

Explanation

Kubernetes enhances SAP AI Core by providing high availability and fault tolerance (B) through automatic pod rescheduling and replication, autoscaling (C) via Horizontal Pod Autoscaler which dynamically adjusts container counts based on workload demand, and GPU resource allocation (E) through node selectors and resource limits that direct AI training/inference workloads to GPU-equipped nodes.

Why the distractors fail: Option A is wrong because Kubernetes is an orchestration platform - it manages where and how workloads run, not what AI models learn or produce; model development still requires human-defined training pipelines. Option D is the opposite of true - Kubernetes depends on container images (Docker or OCI-compatible), so it reinforces the need for containers rather than eliminating it.

Memory tip: Think of Kubernetes as a smart traffic controller for containers - it keeps services alive (B), scales lanes during rush hour (C), and routes heavy loads to the right hardware (E). It controls how things run, never what they think.

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