MUMBAI, India, July 13 -- Intellectual Property India has published a patent application (202621059356 A) filed by Anurag Thantharate; and Raghavender Puchhakayala on May 10, 2026, for A System And Method For Ai-Driven Cost-Aware Scheduling Of Cloud Etl And Big Data Pipelines.
Inventors include Raghavender Puchhakayala; Faiz Gouri; Kuber Jain; and Akshay Aggarwal.
The application for the patent was published on July 10, 2026, under issue no. 28/2026.
Abstract: A cloud data pipeline orchestration system and method are disclosed for executing ETL and big data workloads across one or more cloud environments. Historical workload data and runtime utilization metrics are processed to generate workload demand forecasts. Current workload observations are further analyzed to compute anomaly scores. Pricing and availability data are obtained from multiple cloud providers. A scheduler generates an allocation map for pipeline tasks based on forecasted demand, anomaly conditions, and provider pricing, and issues scaling commands to provision or deallocate resources. A workflow automation module manages task dependencies, retry handling, and clustered execution, while a monitoring interface exports runtime metrics and scaling events. The system further supports dynamic task reassignment, dependency-aware execution control, and adaptive resource selection across heterogeneous cloud infrastructures to improve utilization, reduce execution latency, and maintain continuity of ETL processing under changing workload and infrastructure conditions. The invention provides proactive resource control, anomaly-aware scaling, and cost- aware multi-cloud task placement for distributed ETL execution.
Disclaimer: Curated by HT Syndication.
