Biography
Kamalakar Reddy Singi is a technology professional and researcher whose work focuses on artificial intelligence, machine learning, cloud-native computing, microservices, and intelligent data analytics. His research explores AI-driven observability, streaming telemetry analytics, predictive system performance, anomaly detection, privacy-preserving cloud environments, and the reliability of distributed systems. He is actively involved in academic research, scholarly publications, and peer-review activities in artificial intelligence and computing.
Abstract
Title: AI-Driven Predictive Analytics for Intelligent and Resilient Cloud-Native Systems
Abstract: Modern cloud-native applications generate massive volumes of telemetry through metrics, logs, and distributed traces, creating both opportunities and challenges for maintaining system reliability and performance. Traditional monitoring approaches are often reactive and may not identify emerging performance issues before they affect users. This presentation explores how artificial intelligence and machine learning can transform cloud observability from reactive monitoring into proactive and predictive intelligence.
The talk will discuss AI-driven approaches for analyzing streaming telemetry, identifying anomalous system behavior, predicting performance degradation, and supporting intelligent operational decisions in large-scale microservices environments. It will also highlight the role of temporal behavior, service interdependencies, and multidimensional telemetry in improving anomaly detection and system performance prediction. Finally, the presentation will discuss how these capabilities can contribute to the evolution of more autonomous and resilient cloud-native systems.
