The nopayloaddb project works as an implementation of the Conditions Database reference for the HSF. It provides a RESTful API for managing payloads, global tags, payload types, and associated data.
Our current system, composed of Nginx, Django, and database (link to helm chart), lacks a centralized logging solution making it difficult to effectively monitor and troubleshoot issues. This task will address this deficiency by implementing a centralized logging system aggregating logs from multiple components, and develop a machine learning model to perform intelligent log analysis. The model will identify unusual log entries indicative of software bugs, database bottlenecks, or other performance issues, allowing us to address problems before they escalate. Additionally, by analyzing system metrics, the model will provide insights for an optimal adjustment of parameters during periods of increased request rates.