Prophet

Prophet forecasts time series data using an additive model with non-linear trends. We recommend it for time series that exhibit strong seasonal effects, and contain several cycles of historical data.

Kloudfuse implements the Prophet algorithm as the agile-robust option for Anomaly Detection. It supports hourly, daily, and weekly seasonality.

In Dashboards

To use Prophet operator in a dashboard, apply the following function:

prophet( \
  ${promql}, \ (1)
  ${seasonality} \ (2)
  ${bound}, \ (3)
  ${band} \ (4)
)
none
1 ${promql}: PromQL query to evaluate
2 ${seasonality} 0 = hourly, 1 = daily, 2 = weekly
3 ${bound}: Number of standard deviations (stdv): 1, 2, or 3
4 ${band}: 4 = lower band, 5 = upper band, 6 = both upper and lower bands

Limitations

If the evaluated metrics do not exhibit true seasonality, Prophet may create incorrect (invalid) alerts, or mask valid alerting conditions.

Next steps

For an in-depth discussion of the Prophet approach, see these resources: