Dynamically adjusting sample rates based on performance of a machine-learning based model for performing a network assurance function in a network assurance system
Abstract:
In one embodiment, a network assurance service receives data regarding a monitored network. The service analyzes the received data using a machine learning-based model, to perform a network assurance function for the monitored network. The service detects a lowered performance of the machine learning-based model when a performance metric of the machine learning-based model is below a threshold for the performance metric. When it is determined that the lowered performance of the machine-learning based model is correlated with the sample rate of the received data, the service adjusts the sample rate of the data.
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