Data analysis and processing framework for the CHD

The Compact Helical Device (CHD) experiment is scheduled to begin early in 2027 as the successor to the Large Helical Device (LHD). To support efficient experimental operation, a robust and maintainable data analysis framework must be established before experimental operation begins. Based on operational experience gained from LHD, we analyzed the limitations of the existing LHD workflow and identified requirements for the next-generation analysis system. After evaluating several existing workflow management systems, we designed a lightweight event-driven framework centered on a custom job management system. The proposed framework integrates Python, a database, and Kubernetes to provide centralized workflow management, improved maintainability, and scalable execution. This paper describes the system requirements, design concept, and current implementation status.