Mr. GOVINDAIAH SIMUNI

Data process by Batch systems - Monitoring Automation Using Artificial Intelligence

Abstract:

Batch systems are critical for processing large volumes of data in an organized and timely manner, especially in enterprise environments. However, challenges such as error-prone manual monitoring, slow job recovery due to human intervention, and resource-intensive monitoring can hinder operational efficiency. To address these issues, automation through Artificial Intelligence (AI) and Machine Learning (ML) can be leveraged to streamline batch processing. AI/ML-based solutions can autonomously manage job scheduling, monitor system performance, predict job runtimes, and detect errors in real-time. These intelligent systems not only reduce the need for constant human oversight but also enhance processing efficiency, improve reliability, and minimize errors. Over time, the AI system learns from past data, making proactive adjustments and automatically fixing issues, ultimately improving the overall performance of batch processing and reducing operational costs.