`const()`

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Creates a stream of constant-value MTS.

Syntax

const(value=constant_value, key=key_maps, timeseries=timeseries_maps)

Parameter definitions

Parameter	Type	Description
`constant_value`	Number. Default is `None`	The numeric value to use when generating a single MTS
`key_maps`	Python map or list of maps. Default is None	The dimensions and values to insert into the MTS
`timeseries_maps`	List of maps. Default is ``	If specified, generates multiple constant MTS in the output stream. Each map in the list contains a key map and a value constant.

Examples

Using `const()` to create a single timeseries

This SignalFlow expression publishes a single timeseries without any dimensions:

const(value=.5).publish()

To add dimensions to it, add the key parameter:

const(value=.5, key={"host": "host2"}).publish()

Using `const()` to create multiple timeseries

Test distinct static thresholds for a set of dimension values by generating multiple MTS using const(). Specify each MTS in the timeseries parameter. Don’t specify value and key as arguments to const(); instead, specify them in the value of timeseries.

#Define thresholds with two MTS:
#1. 'aws_region:us-east-1' dimension with a value of 75
#2. 'aws_region:us-west-1' dimension with a value of 85
thresholds = const(timeseries=[
    {'key': {'aws_region': 'us-east-1'}, 'value': 75},
    {'key': {'aws_region': 'us-west-1'}, 'value': 85}])

#Use those thresholds in a detector and let correlation do the work
detect(data('cpu.utilization').promote('aws_region') > thresholds).publish('cpu too high')

const()