Threshold Strategy Plugin

The threshold strategy defines a range of metric values with a lower and an upper bound, and an action to take when the current metric value is considered to be within bounds.

Multiple tiers can be defined by declaring more than one check in the same scaling policy. If there is any overlap between the bounds, the safest check will be used.

Agent Configuration Options

strategy "threshold" {
  driver = "threshold"
}

Policy Configuration Options

policy {
  # ...
  check "high-memory-usage" {
    # ...
    group = "memory-usage"

    strategy "threshold" {
      upper_bound = 100
      lower_bound = 70
      delta       = 1
    }
  }

  check "low-memory-usage" {
    # ...
    group = "memory-usage"

    strategy "threshold" {
      upper_bound = 30
      lower_bound = 0
      delta       = -1
    }
  }
  # ...
}

• lower_bound (float: <optional>) - The minimum value a metric must have to be considered with bounds.

• upper_bound (float: <optional>) - The maximum value a metric must have to be considered within bounds.

• delta (int: <optional>) - Specifies the relative amount to add (positive value) or remove (negative value) from the current target count. Conflicts with percentage and value.

• percentage (float: <optional>) - Specifies a percentage value by which the current count should be increased (positive value) or decreased (negative value). Conflicts with delta and value.

• value (int: <optional>) - Specifies an absolute value that should be set as the new target count. Conflicts with delta and percentage.

• within_bounds_trigger (int: 5) - The number of data points in the query result time series that must be within the bound values to trigger the action.

At least one of lower_bound or upper_bound must be defined. If lower_bound is not defined, any value below upper_bound is considered within bounds. Similarly, if upper_bound is not defined, any value above lower_bound will be considered within bounds.

One, and only one, of delta, percentage, or value must be defined.