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NCP-MCI-6.10 · Question #93

Within Intelligent Operations, Capacity Configurations have been set to Auto Detect for Reserve Capacity For Failure. For an RF2 cluster with 10 nodes, what effect does this have on Capacity Runway?

The correct answer is C. Reserves CPU, RAM and storage from the largest node to account for a single node failure. When 'Auto Detect' is selected for Reserve Capacity For Failure in Nutanix Intelligent Operations, Prism automatically determines how much capacity to reserve based on the cluster's resilience factor. For an RF2 cluster (which tolerates one node failure), Auto Detect reserves…

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Question

Within Intelligent Operations, Capacity Configurations have been set to Auto Detect for Reserve Capacity For Failure. For an RF2 cluster with 10 nodes, what effect does this have on Capacity Runway?

Options

  • AReserves storage and memory from the largest node to account for a single node failure.
  • BReserves RAM and CPU from the fastest node to account for a single node failure.
  • CReserves CPU, RAM and storage from the largest node to account for a single node failure.
  • DReserves 10% of CPU, memory and storage to account for a single node failure.

How the community answered

(60 responses)
  • A
    7% (4)
  • B
    2% (1)
  • C
    88% (53)
  • D
    3% (2)

Explanation

When 'Auto Detect' is selected for Reserve Capacity For Failure in Nutanix Intelligent Operations, Prism automatically determines how much capacity to reserve based on the cluster's resilience factor. For an RF2 cluster (which tolerates one node failure), Auto Detect reserves CPU, RAM, and storage equivalent to the resources provided by the single largest node in the cluster. This ensures the capacity runway accurately reflects what would remain available if the most resource-rich node failed. Option A omits CPU. Option B uses an incorrect criterion ('fastest node') and omits storage. Option D (reserving a flat 10%) is not how Auto Detect works - it is node-specific, not percentage-based.

Topics

#Intelligent Operations#Capacity Planning#High Availability#Resource Reservation

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