Simulated Banking Server Data For PM

This dataset is a simulated representation of banking server log data. It is specifically designed for predictive maintenance use cases, with a focus on identifying banking server downtime based on various system performance metrics. The data mimics real-world conditions and has been adjusted to reflect the unique demands of banking applications, including managing high transaction volumes and ensuring system reliability.

The dataset can be used to train machine learning models for classification tasks that predict server downtime. It includes multiple server performance indicators, such as CPU usage, memory usage, disk I/O, network latency, and error rate.