# » 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

## » Policy Configuration Options

`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 valus 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.