Stability windowing

A windowing policy of type stability discards temporal intervals in which a given metric is not stable, and selects, among the remaining intervals, the ones in which another target metric is maximized or minimized. Stability windowing can be sample-based or time-frame based.

The stability windowing has the following structure:

Field	Type	Value restrictions	Is required	Default value	Description
type	string	{stability}	TRUE		The type of windowing.
stability->metric	string	It should match the name of an existing metric monitored by AKAMAS	TRUE		The metric whose stability is going to be verified to exclude some temporal intervals over the duration of a trial.
stability->labels	set of key-value pairs		FALSE		A set of key-value pairs that represent filtering conditions for retrieving the value of the metric. This conditions can be used to consider the right metric of the right component, you can in fact filter by componentName or by other custom properties defined in the components of the system of the study.
stability->resolution	string	Valid values are in the form 30s 40m 2h where s refers to seconds, m to minutes, h to hours	FALSE	0s	The temporal resolution at which Akamas aggregate data points to determine feasible windows.
stability->width	integer string	stability->width > 1 Valid values are in the form 30s 40m 2h as specified in stability->resolution	TRUE		The width of temporal intervals over the duration trial which are checked for the stability of the metric. Width can be sample-based (integer) or time frame-based (string).
stability->maxStdDev	double		TRUE		The stability condition, i.e, the maximum amount of standard deviation among the value of the data point of the metric tolerated for a temporal interval of size width, otherwise, the temporal interval will be discarded

and for the comparison metric section

Field	Type	Value restrictions	Is required	Default value	Description
metric	string	It should match the name of an existing metric monitored by Akamas	TRUE		The metric whose value is analyzed to include or exclude temporal intervals over the duration of a trial, when another reference metric is stable.
labels	set of key-value pairs		FALSE		A set of key-value pairs that represent filtering conditions for retrieving the value of the metric. This conditions can be used to consider the right metric of the right component, you can in fact filter by componentName or by other custom properties defined in the components of the system of the study.
is	string	{min,max}	TRUE		If the value of the metric should be maximum or minimum to include or exclude temporal intervals over the duration of a trial when another reference metric is stable.

Example

The following fragment is an example of stability windowing (time-frame based):

type: stability
stability:
  metric: throughput
  labels:
    componentName: DB
  resolution: "30s"
  width: 10
  maxStdDev: .6
  # Comparison metric section
  when:
    metric: response_time
    labels:
      componentName: FE
    is: min