def validate(self, data):
data_model = {
"actuator": six.string_types,
"check_interval": int,
"metric_source": six.string_types,
"schedule_strategy": six.string_types
}
for key in data_model:
if (key not in data):
raise ex.BadRequestException(
"Variable \"{}\" is missing".format(key))
if (not isinstance(data[key], data_model[key])):
raise ex.BadRequestException(
"\"{}\" has unexpected variable type: {}. Was expecting {}"
.format(key, type(data[key]), data_model[key]))
def stop_scaling(app_id):
if app_id in scaled_apps:
API_LOG.log("Removing application id: %s" % (app_id))
executor = scaled_apps[app_id]
executor.stop_application_scaling()
scaled_apps.pop(app_id)
else:
raise ex.BadRequestException()
def start_scaling(app_id, data):
if ('control_plugin' not in data or 'control_parameters' not in data):
API_LOG.log("Missing parameters in request")
raise ex.BadRequestException()
plugin = data["control_plugin"]
controller = controller_builder.get_controller(plugin, app_id, data)
executor = Thread(target=controller.start_application_scaling)
executor.start()
scaled_apps[app_id] = controller
def setup_environment(data):
if ('actuator_plugin' not in data or 'instances_cap' not in data):
API_LOG.log("Missing parameters in request")
raise ex.BadRequestException()
plugin = data['actuator_plugin']
instances_cap = data['instances_cap']
actuator = actuator_builder.get_actuator(plugin)
try:
actuator.adjust_resources(instances_cap)
except Exception as e:
API_LOG.log(str(e))
def validate(self, data):
data_model = {"actuation_size": int, "max_rep": int, "min_rep": int}
for key in data_model:
if (key not in data):
raise ex.BadRequestException(
"Variable \"{}\" is missing".format(key))
if (not isinstance(data[key], data_model[key])):
raise ex.BadRequestException(
"\"{}\" has unexpected variable type: {}. Was expecting {}"
.format(key, type(data[key]), data_model[key]))
if 'trigger_up' not in data:
raise ex.BadRequestException(
"Variable \"{}\" is missing".format(key))
if not (isinstance(data['trigger_up'], int)
or isinstance(data['trigger_up'], float)):
raise ex.BadRequestException(
"\"trigger_up\" has unexpected variable type: {}. Was"
" expecting float or int".format(type(data['trigger_up'])))
if 'trigger_down' not in data:
raise ex.BadRequestException(
"Variable \"{}\" is missing".format(key))
if not (isinstance(data['trigger_down'], int)
or isinstance(data['trigger_down'], float)):
raise ex.BadRequestException(
"\"trigger_down\" has unexpected variable type: {}. Was"
" expecting float or int".format(type(data['trigger_down'])))
if (data["min_rep"] < 1):
raise ex.BadRequestException(
"Variable \"min_rep\" must be greater than 0")
if (data["min_rep"] > data["max_rep"]):
raise ex.BadRequestException("Variable \"max_rep\" must be greater\
or equal than \"min_rep\"")
def validate(self, data):
data_model = {
"max_rep": int,
"min_rep": int,
"heuristic_options": dict
}
for key in data_model:
if (key not in data):
raise ex.BadRequestException(
"Variable \"{}\" is missing".format(key))
if (not isinstance(data[key], data_model[key])):
raise ex.BadRequestException(
"\"{}\" has unexpected variable type: {}. Was expecting {}"
.format(key, type(data[key]), data_model[key]))
if (data["min_rep"] < 1):
raise ex.BadRequestException(
"Variable \"min_rep\" must be greater than 0")
if (data["min_rep"] > data["max_rep"]):
raise ex.BadRequestException("Variable \"max_rep\" must be greater\
or equal than \"min_rep\"")
key = "heuristic_options"
heuristics = \
["proportional_gain", "derivative_gain", "integral_gain"]
types = [float, int]
data = data.get(key)
for key in heuristics:
if (key not in data):
raise ex.BadRequestException(
"Variable \"{}\" is missing".format(key))
if (type(data[key]) not in types):
raise ex.BadRequestException(
"\"{}\" has unexpected variable type: {}. Was expecting {}"
.format(key, type(data[key]), types))
