[D] Training time-series data from IoT fleets on the fly

A little bit of context: we have a few hundred thousand IoT devices that push timeseries data that gets consumed by our users. We'd like to implement some anomaly detection models, and maybe some predictive models in the future.

My question specific comes because just this morning I noticed in AWS CloudWatch that an anomaly detection alarm noted that it had finished training on limited metric data for my specific metric. Does this mean that for our data, we need …

anomaly anomaly detection context data detection devices future iot machinelearning predictive predictive models series timeseries training