Server workload analysis for power minimization using consolidation

TLDR

Server consolidation reduces data center energy costs, but risks arise when application correlations are ignored. This study provides the first detailed analysis of enterprise server workloads to identify characteristics for consolidation and examines utilization stability for low‑risk consolidation. Based on workload insights, the authors design two consolidation methods that achieve significant power savings while mitigating performance risk, and implement them in a planning tool evaluated comprehensively. The authors find substantial power‑saving potential when consolidation uses off‑peak application demand, and the evaluation confirms the effectiveness of the proposed methods.

Abstract

Server consolidation has emerged as a promising technique to reduce the energy costs of a data center. In this work, we present the first detailed analysis of an enterprise server workload from the perspective of finding characteristics for consolidation. We observe significant potential for power savings if consolidation is performed using off-peak values for application demand. However, these savings come up with associated risks due to consolidation, particularly when the correlation between applications is not considered. We also investigate the stability in utilization trends for low-risk consolidation. Using the insights from the workload analysis, two new consolidation methods are designed that achieve significant power savings, while containing the performance risk of consolidation. We present an implementation of the methodologies in a consolidation planning tool and provide a comprehensive evaluation study of the proposed methodologies.