HPE CloudPhysics is a SaaS-based analytics platform that collects high-resolution metadata (at 20-second intervals) from a customer's virtualized infrastructure to drive data-led procurement and optimization decisions. In the context of performance analysis and sizing, it is critical to understand not just the average utilization, but how different resource demands interact over time.

The Peak Details statistic is unique within the CloudPhysics analytics framework because it provides time-correlated values across different resource dimensions (CPU, RAM, and Disk I/O). While standard "Storage Metrics" or "Hardware Performance" summaries often present aggregated averages or 95th percentile figures that lose their temporal context, Peak Details allows an architect to see exactly when a spike occurred.

This correlation is essential for determining if a storage bottleneck is being driven by a simultaneous compute peak or if a specific "noisy neighbor" VM is impacting the entire datastore during a backup or batch processing window. By aligning disk latency peaks with IOPS and throughput peaks on the same timeline, CloudPhysics enables the architect to validate if the existing third-party array is truly under-provisioned or simply misconfigured. This time-correlated insight ensures that the new HPE storage solution is sized not just for total capacity, but for the actual performance "burstiness" observed in the customer's production cycle. Other metrics, while useful for high-level summaries, do not provide the granular, synchronized timeline required to perform a deep-dive root cause analysis or precision sizing for mission-critical workloads.