The primary goal of resource allocation is to ensure application performance. While the average CPU usage is low, the frequent, high-utilization spikes (85%) represent critical processing periods for the workload. Ignoring these peaks by relying on the average would lead to CPU contention and severe performance degradation. The correct strategy is to size the resource allocation, including a buffer, to accommodate these peak demands. This ensures the workload has sufficient CPU resources when it needs them most, maintaining responsiveness without impacting other workloads by borrowing from a shared reserve.

A. Relying on averages ignores critical peak demand, which is a common cause of performance bottlenecks for spiky workloads.

C. The issue is with CPU utilization, not data storage. Switching storage tiers is an irrelevant action for this problem.

D. Lowering the vCPU count would worsen the problem, causing the CPU to hit 100% during spikes and severely throttle the application.

1. HPE GreenLake Central User Guide: In the "Capacity" section, the guide explains the concept of buffer capacity. It states, "Buffer capacity is the amount of capacity that is available for use above your reserved capacity." This buffer is designed to handle growth and temporary spikes in demand, which directly aligns with the scenario in the question. (Reference: HPE GreenLake Central Documentation, "Viewing Capacity" section).

2. HPE White Paper: "HPE Right Sizing: A practical approach to optimizing your hybrid cloud": This document emphasizes the importance of analyzing workload characteristics beyond simple averages. It discusses analyzing peak utilization data to "right-size" infrastructure, stating that proper sizing must account for performance peaks to avoid service degradation, which supports sizing a buffer to cover spikes. (Reference: HPE White Paper, "Workload Analysis" and "Sizing for Performance" sections).

3. HPE GreenLake for Private Cloud Enterprise - Service Description: This document details the capacity management model, which includes a locally installed buffer of capacity. It notes that this buffer is "available for immediate use when business demand spikes," confirming that the intended use of a buffer is to handle the exact situation described in the question. (Reference: HPE Service Description document for HPE GreenLake for Private Cloud Enterprise, "Capacity Management" section).