Linear Regression

Linear regression predicts the value of a dependent variable from the value of an independent variable. It models the relationship between the variables as a linear equation, and fits a line that minimizes the differences between the predicted and actual values.

Sampling interval

Sampling intervals are 1m, 2m, 3m, 5m, 10m, 15m, 30m, 1h, and 2h.

Numeric parameter

Has the possible values of 1, 2, or 3.

In Dashboards

To use linear regression in a dashboard, apply the following function:

predict_linear( \
  ${promql} \ (1)
  ${prediction_in_seconds} \(2)
)

Limitations

• Use only with Gauge metric types.
• Makes assumptions regarding the linearity of the data. Exhibits problems with outliers as it attempts to "overfit" the data, making the detection inconsistent.
• Do not use with anomaly detection functions that manipulate the underlying data, as it makes anomaly detection unreliable.

Next steps

For an in-depth discussion of linear-regression, see these external resources:

• predict_linear() from the Prometheus documentation
• Linear Regression in Wikipedia