AI-Driven Omnichannel Support for Capacity Planning in Global Data Centers

Abstract

The operation of global data centers as interconnected systems requires capacity planning that considers activity across all centers and supports across all channels. An omnichannel approach incorporates AI to support capacity planning in an integrated way, utilizing telemetry signals from the physical infrastructure and operational signals from the support systems that cover edge, on-premises, and cloud footprints. Anomalies in observed behavior are detected and analyzed using machine learning techniques. Elastic demand forecast models take into account external market influences and demand-shaping initiatives, while simulations support what-if analysis for capacity planning. Cross-channel support for capacity planning considers catastrophe preparedness and outage readiness, optimizes resource scheduling and queuing across centers, and leverages automation with a human-in-the-loop governance model. Bandwidth, power, and cooling are planned using sustainability metrics and renewable integration to contribute to business operations while enabling the organization’s net-zero commitment.