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:
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
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):
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