Observability-Driven Operations Using Predictive Intelligence across Cloud Infrastructure for Resilient Enterprise Management Response
DOI:
https://doi.org/10.15662/IJEETR.2026.0805002Keywords:
observability, predictive intelligence, cloud infrastructure, machine learning, anomaly detection, predictive analytics, enterprise resilience, cloud operations, AIOps, intelligent automationAbstract
Modern enterprises increasingly depend on distributed cloud infrastructures comprising virtual machines, containers, microservices, serverless applications, databases, networks, and third-party services. This complexity creates significant challenges for maintaining reliability, performance, security, and business continuity. Traditional monitoring approaches that primarily respond to incidents after they occur are insufficient for highly dynamic environments. Observability-driven operations provide a more comprehensive approach by integrating metrics, logs, traces, events, and contextual operational data to understand system behavior. When combined with predictive intelligence, observability can move enterprise operations from reactive incident management toward proactive risk identification and automated intervention. This paper examines how predictive analytics, machine learning, anomaly detection, forecasting, and intelligent event correlation can be integrated with cloud observability platforms to strengthen resilient enterprise management. The proposed approach considers continuous telemetry collection, centralized data processing, feature extraction, predictive modeling, risk assessment, automated response, and feedback mechanisms as interconnected operational capabilities. The methodology emphasizes a multi-layered cloud environment in which predictive models identify emerging performance degradation, resource exhaustion, service anomalies, and potential failures before they affect critical business services. The study also considers challenges involving data quality, model drift, interoperability, explainability, security, and organizational adoption. The resulting framework positions observability as an operational intelligence foundation through which enterprises can improve availability, optimize resources, reduce incident impact, and develop adaptive cloud management practices
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