<![CDATA[The rapid growth of historical data in the class booking information system can significantly degrade performance, impacting system scalability and reliability. This research addresses the issue by designing and implementing an automated Data Lifecycle Management (DLM) framework. The primary objectives are: (1) to develop a functional automated DLM prototype using the Laravel framework and its task scheduler, and (2) to analyze how this implementation enhances system scalability and reliability. This study adopts a system implementation method by applying the seven stages of DLM, supported by a Dual Connection database architecture that separates operational data (Hot Storage) from historical archives (Cold Storage). The results demonstrate the successful implementation of all DLM stages, from data creation to automated deletion. The system automatically archives weekly transactional data and permanently deletes them after a retention period of one semester plus a 30-day grace period. Furthermore, a secure public API was developed to facilitate data sharing for academic purposes. The implementation of automated DLM proves effective in managing data lifecycle, reducing the burden on the primary database, and maintaining system performance, thereby ensuring better scalability and reliability.]]>
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