def vs_abs_perc():
return CascadingDropdown(
orientation="horizontal",
choices=[
(
"perc",
_("Percentual levels (in relation to port speed)"),
Tuple(
orientation="float",
show_titles=False,
elements=[
Percentage(label=_("Warning at")),
Percentage(label=_("Critical at")),
],
),
),
(
"abs",
_("Absolute levels in bits or bytes per second"),
Tuple(
orientation="float",
show_titles=False,
elements=[
Integer(label=_("Warning at")),
Integer(label=_("Critical at")),
],
),
),
("predictive", _("Predictive Levels (only on CMC)"),
PredictiveLevels()),
],
)
def test_load_levels_wato():
# when scaling the preditvie levels we make certain asumptions about the
# wato structure of predictive levels here we try to make sure that these
# asumptions are still correct. if this test fails, fix it and adapt
# _scale_levels_predictive to handle the changed values
from cmk.gui.plugins.wato import PredictiveLevels
pl = PredictiveLevels()
pl.validate_value(LEVELS, "")
pl.validate_datatype(LEVELS, "")
def _parameter_valuespec_memory_pagefile_win():
return Dictionary(
elements=[
(
"memory",
Alternative(
title=_("Memory Levels"),
elements=[
Tuple(
title=_("Memory usage in percent"),
elements=[
Percentage(title=_("Warning at")),
Percentage(title=_("Critical at")),
],
),
Transform(
Tuple(
title=_("Absolute free memory"),
elements=[
Filesize(title=_("Warning if less than")),
Filesize(title=_("Critical if less than")),
],
),
# Note: Filesize values lesser 1MB will not work
# -> need hide option in filesize valuespec
back=lambda x:
(x[0] // 1024 // 1024, x[1] // 1024 // 1024),
forth=lambda x:
(x[0] * 1024 * 1024, x[1] * 1024 * 1024)),
PredictiveLevels(unit=_("GB"),
default_difference=(0.5, 1.0))
],
default_value=(80.0, 90.0))),
(
"pagefile",
Alternative(
title=_("Commit charge Levels"),
elements=[
Tuple(
title=
_("Commit charge in percent (relative to commit limit)"
),
elements=[
Percentage(title=_("Warning at")),
Percentage(title=_("Critical at")),
],
),
Transform(
Tuple(
title=_("Absolute commitable memory"),
elements=[
Filesize(title=_("Warning if less than")),
Filesize(title=_("Critical if less than")),
],
),
# Note: Filesize values lesser 1MB will not work
# -> need hide option in filesize valuespec
back=lambda x:
(x[0] // 1024 // 1024, x[1] // 1024 // 1024),
forth=lambda x:
(x[0] * 1024 * 1024, x[1] * 1024 * 1024)),
PredictiveLevels(unit=_("GB"),
default_difference=(0.5, 1.0))
],
default_value=(80.0, 90.0))),
("average",
Integer(
title=_("Averaging"),
help=
_("If this parameter is set, all measured values will be averaged "
"over the specified time interval before levels are being applied. Per "
"default, averaging is turned off. "),
unit=_("minutes"),
minvalue=1,
default_value=60,
)),
], )
