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In this session, we will present an open-source stream processing architecture, based on Spark Structured Streaming, for automating model monitoring with some experiment results. We use Kafka to log model predictions, KFServing for model serving and a Kubernetes operator for the deployment and configuration of the different components. As for the analysis of inference data, we implemented an extendable monitoring framework on top of Spark Structured Streaming to detect outliers and data drift.
