MUMBAI, India, Nov. 2 -- Intellectual Property India has published a patent application (202641125688 A) filed by Sohail Sayed on October 22, 2026, for Ai-Driven Anomaly Detection And Predictive Performance Optimization In Microservices-Based Distributed Applications.
Inventor includes Sohail Sayed.
The application for the patent was published on October 30, 2026, under issue no. 44/2026.
Abstract: AI-DRIVEN ANOMALY DETECTION AND PREDICTIVE PERFORMANCE OPTIMIZATION IN MICROSERVICES-BASED DISTRIBUTED APPLICATIONS ABSTRACT The invention relates to anomaly detection and predictive performance optimization in microservices based distributed applications. A telemetry collector obtains metrics, logs, traces, and deployment events from services. A topology builder produces a versioned service dependency graph, while a context processor aligns observations with graph relationships and records data quality indicators. An anomaly inference module generates context dependent anomaly scores. A performance predictor estimates future latency, errors, queue conditions, or resource demand using the graph, aligned features, and anomaly scores. A candidate evaluator compares permissible corrective actions with a no action baseline and estimates their effects on connected services. A policy gate checks authorization, capacity, uncertainty, and cooldown constraints before an actuator issues an approved adjustment or recommendation. A feedback recorder compares observations with predicted effects and supplies qualified outcomes for model maintenance. The coordinated arrangement supports dependency aware performance decisions while constraining intervention when available evidence is incomplete or uncertain.
Disclaimer: Curated by HT Syndication.
