Trace Sampling

In this study, we introduce TraStrainer, an online sampler that takes into account both system runtime state and trace diversity. TraStrainer employs an interpretable and automated encoding method to represent traces as vectors. Simultaneously, it adaptively determines sampling preferences by analyzing system runtime metrics. When sampling, it combines the results of system-bias and diversity-bias through a dynamic voting mechanism.