Questions: About FIXME in Scaler.py

[cmasmas]

Please, could you explain about this FIXME note:

FIXME: Size is 5 due to an excessive number of items to be predicted, please repair this part.

, as we want to store the monitoring data during 60min, considering 5min between iterations

self.predictorScaler_cpu_usage_1h = Queue( [] , 5) self.predictorScaler_req_rate_1h = Queue( [] , 5)

Then, how many values does list_data_cpu contain (lines 503-511)?

self.optimal_scaling.calculate_error_prediction_cpu(list_data_cpu)

[hectorj2f]

@cmasmas Probably, the message is not clear enough. The prediction models were implemented to calculate the future values from a number of data points. In this implementation, we gather the data points from all the backend nodes during approx last 30min and store them in a circular queue size=5. This operation gives us an important amount of data points. For instance, 5 backends with 50 data points for the CPU values will provide 5 * 50 * 5 = 1250 points

Unfortunately, I was not able to extend the implementation of the predictor models to process a larger amount of data points in a reasonable amount of time (possible extension). Another alternative would be to get less data points per backend but to collect data for a longer period of time.

[gpierre42]

Hello, It looks like we can now close this issue. Do not hesitate to reopen it if necessary! Guillaume