SMOCS: A Streaming Framework for Simplified Deployment, Monitoring, and Optimization of ML Systems in Production
Machine learning has demonstrated significant potential for real-time monitoring, optimization, and control of scientific facilities. However, deploying and maintaining ML models in operational environments remains a substantial engineering challenge. Each facility presents unique data protocols, non-standard formats, and infrastructure constraints, forcing teams to rebuild integration pipelines for every new application. We present SMOCS (Streaming Monitoring Optimization and Control System), a Kafka-based containerized framework that addresses this challenge through three contributions: 1) a layered abstraction over Apache Kafka that separates infrastructure from application logic, 2) a...
| Authors | Armen Kasparian, Kishansingh Rajput, Malachi Schram et al. |
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| Primary category | cs.SE |
| Published | 2 July 2026 |
| Last updated at source | 2 July 2026 |
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