The rapid adoption of cloud infrastructure has transformed identity management from a predominantly human-centric security function into a broader governance problem involving applications, services, workloads, automation pipelines, containers, machine accounts, and other non-human identities (NHIs). Unlike human identities, NHIs frequently operate continuously, interact programmatically, inherit permissions through infrastructure configurations, and may remain active beyond their intended operational lifetime. Consequently, ineffective lifecycle management can create excessive privileges, unmanaged credentials, stale service identities, and difficult-to-audit access relationships. This paper develops an intelligent lifecycle management and security governance framework for NHIs in cloud infrastructure by synthesizing concepts from the provided literature on time-series representation, dimensionality reduction, symbolic representation, segmentation, event reasoning, and predictive maintenance. The central proposition is that NHI governance can be improved by treating identity activity as a continuously evolving operational data stream rather than as a static inventory. The proposed framework combines identity discovery, behavioral representation, temporal segmentation, risk assessment, lifecycle state determination, policy enforcement, and continuous governance. The literature indicates that compact representations of temporal behavior can support scalable analysis, while event-driven and knowledge-oriented approaches can improve interpretation of evolving identity activity. The framework therefore integrates temporal analytics with policy-based security controls to support adaptive decisions concerning identity creation, authorization, rotation, suspension, and retirement. The paper concludes that intelligent NHI governance should move from periodic credential administration toward continuous, evidence-based lifecycle control.