def __init__(self, application_id, parameters):
self.logger = ScalingLog(
"diff.controller.log", "controller.log", application_id)
scaling_parameters = parameters["control_parameters"]
self.application_id = application_id
parameters.update({"app_id": application_id})
# read scaling parameters
self.check_interval = scaling_parameters["check_interval"]
self.trigger_down = scaling_parameters["trigger_down"]
self.trigger_up = scaling_parameters["trigger_up"]
self.min_cap = scaling_parameters["min_rep"]
self.max_cap = scaling_parameters["max_rep"]
self.actuation_size = scaling_parameters["actuation_size"]
# The actuator plugin name
self.actuator_type = scaling_parameters["actuator"]
# The metric source plugin name
self.metric_source_type = scaling_parameters["metric_source"]
# We use a lock here to prevent race conditions when stopping the
# controller
self.running = True
self.running_lock = threading.RLock()
# Gets a new metric source plugin using the given name
metric_source = MetricSourceBuilder().get_metric_source(
self.metric_source_type, parameters)
# Gets a new actuator plugin using the given name
actuator = ActuatorBuilder().get_actuator(self.actuator_type,
parameters=parameters)
# The alarm here is responsible for deciding whether to scale up or
# down, or even do nothing
self.alarm = KubeJobs(actuator, metric_source,
self.trigger_down, self.trigger_up,
self.min_cap, self.max_cap, self.actuation_size,
application_id)
class KubejobsController(Controller):
def __init__(self, application_id, parameters):
self.validate(parameters["control_parameters"])
self.logger = ScalingLog(
"diff.controller.log", "controller.log", application_id)
self.application_id = application_id
parameters.update({"app_id": application_id})
# read scaling parameters
self.check_interval = \
parameters["control_parameters"]["check_interval"]
# We use a lock here to prevent race conditions when stopping the
# controller
self.running = True
self.running_lock = threading.RLock()
# The alarm here is responsible for deciding whether to scale up or
# down, or even do nothing
self.alarm = KubeJobs(parameters)
def start_application_scaling(self):
run = True
self.logger.log("Start to control resources")
while run:
self.logger.log("Monitoring application: %s" %
self.application_id)
# Call the alarm to check the application
self.alarm.check_application_state()
# Wait some time
time.sleep(float(self.check_interval))
with self.running_lock:
run = self.running
def stop_application_scaling(self):
with self.running_lock:
self.running = False
def status(self):
return self.alarm.status()
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]))
class KubejobsController(Controller):
def __init__(self, application_id, parameters):
self.logger = ScalingLog(
"diff.controller.log", "controller.log", application_id)
scaling_parameters = parameters["control_parameters"]
self.application_id = application_id
parameters.update({"app_id": application_id})
# read scaling parameters
self.check_interval = scaling_parameters["check_interval"]
self.trigger_down = scaling_parameters["trigger_down"]
self.trigger_up = scaling_parameters["trigger_up"]
self.min_cap = scaling_parameters["min_rep"]
self.max_cap = scaling_parameters["max_rep"]
self.actuation_size = scaling_parameters["actuation_size"]
# The actuator plugin name
self.actuator_type = scaling_parameters["actuator"]
# The metric source plugin name
self.metric_source_type = scaling_parameters["metric_source"]
# We use a lock here to prevent race conditions when stopping the controller
self.running = True
self.running_lock = threading.RLock()
# Gets a new metric source plugin using the given name
metric_source = MetricSourceBuilder().get_metric_source(
self.metric_source_type, parameters)
# Gets a new actuator plugin using the given name
actuator = ActuatorBuilder().get_actuator(self.actuator_type,
parameters=parameters)
# The alarm here is responsible for deciding whether to scale up or down, or even do nothing
self.alarm = KubeJobs(actuator, metric_source,
self.trigger_down, self.trigger_up,
self.min_cap, self.max_cap, self.actuation_size,
application_id)
def start_application_scaling(self):
run = True
print "Start to control resources"
while run:
self.logger.log("Monitoring application: %s" %
self.application_id)
# Call the alarm to check the application
self.alarm.check_application_state()
# Wait some time
time.sleep(float(self.check_interval))
with self.running_lock:
run = self.running
def stop_application_scaling(self):
with self.running_lock:
self.running = False
def status(self):
return self.alarm.status()
def setUp(self):
application_id = "000001"
self.parameters = {
"control_parameters": {
"metric_source": "redis",
"schedule_strategy": "default",
"actuator": 'nop',
"trigger_down": 1,
"trigger_up": 1,
"min_rep": 2,
"max_rep": 10,
"check_interval": 1,
"actuation_size": 3},
"redis_ip": "192.168.0.0",
"redis_port": "5000",
"application_id": application_id
}
self.kubejobs1 = KubeJobs(self.parameters)
self.kubejobs1.metric_source = \
MetricSourceMock("2018-11-26T15:00:00.000Z", -2)
self.kubejobs1.actuator = ActuatorMock()
self.controller = KubejobsController(application_id, self.parameters)
self.controller.alarm = self.kubejobs1
def setUp(self):
parameters = {
"control_parameters": {
"check_interval": 2,
"trigger_down": 1,
"trigger_up": 1,
"min_rep": 2,
"max_rep": 10,
"actuation_size": 3,
"actuator": "nop",
"metric_source": "redis",
"redis_ip": "192.168.0.0",
"redis_port": "5000"
},
"redis_ip": "192.168.0.0",
"redis_port": "5000"
}
application_id = "000001"
metric_source_1 = MetricSourceMock("2018-11-26T15:00:00.000Z", -2)
actuator = ActuatorMock()
trigger_down = 1
trigger_up = 1
min_cap = 2
max_cap = 10
actuation_size = 3
alarm = self.kubejobs1 = KubeJobs(actuator, metric_source_1,
trigger_down, trigger_up, min_cap,
max_cap, actuation_size,
application_id)
self.controller = KubejobsController(application_id, parameters)
self.controller.alarm = alarm
def __init__(self, application_id, parameters):
self.validate(parameters["control_parameters"])
self.logger = ScalingLog(
"diff.controller.log", "controller.log", application_id)
self.application_id = application_id
parameters.update({"app_id": application_id})
# read scaling parameters
self.check_interval = \
parameters["control_parameters"]["check_interval"]
# We use a lock here to prevent race conditions when stopping the
# controller
self.running = True
self.running_lock = threading.RLock()
# The alarm here is responsible for deciding whether to scale up or
# down, or even do nothing
self.alarm = KubeJobs(parameters)
def setUp(self):
metric_source_1 = MetricSourceMock("2018-11-26T15:00:00.000Z", -2)
actuator = ActuatorMock()
trigger_down = 1
trigger_up = 1
min_cap = 2
max_cap = 10
actuation_size = 3
application_id_1 = "00001"
application_id_2 = "00002"
metric_source_2 = MetricSourceMock("2017-08-06T07:00:00.000Z", 0.0002)
self.kubejobs1 = KubeJobs(actuator, metric_source_1, trigger_down,
trigger_up, min_cap, max_cap, actuation_size,
application_id_1)
self.kubejobs2 = KubeJobs(actuator, metric_source_2, trigger_down,
trigger_up, min_cap, max_cap, actuation_size,
application_id_2)
def setUp(self):
data1 = {"metric_source": "redis",
"schedule_strategy": "default",
"actuator": 'nop',
"trigger_down": 0,
"trigger_up": 0,
"min_rep": 1,
"max_rep": 10,
"actuation_size": 1}
data2 = {"metric_source": 'redis',
"schedule_strategy": "default",
"actuator": "nop",
"trigger_down": 0,
"trigger_up": 0,
"min_rep": 1,
"max_rep": 10,
"actuation_size": 1}
self.kubejobs1 = KubeJobs({"redis_ip": "0.0.0.0",
"redis_port": "2352",
"application_id": "00001",
"control_parameters": data1})
self.kubejobs2 = KubeJobs({"redis_ip": "0.0.0.0",
"redis_port": "2352",
"application_id": "00002",
"control_parameters": data2})
self.kubejobs1.metric_source = \
MetricSourceMock("2017-08-06T07:00:00.000Z", -2)
self.kubejobs1.actuator = ActuatorMock()
# self.kubejobs1.scheduler = SchedulerMock()
self.kubejobs2.metric_source = \
MetricSourceMock("2018-11-26T15:00:00.000Z", 0.0002)
self.kubejobs2.actuator = ActuatorMock()
class TestKubeJobs(unittest.TestCase):
"""
Set up KubeJobs alarm objects
"""
def setUp(self):
data1 = {"metric_source": "redis",
"schedule_strategy": "default",
"actuator": 'nop',
"trigger_down": 0,
"trigger_up": 0,
"min_rep": 1,
"max_rep": 10,
"actuation_size": 1}
data2 = {"metric_source": 'redis',
"schedule_strategy": "default",
"actuator": "nop",
"trigger_down": 0,
"trigger_up": 0,
"min_rep": 1,
"max_rep": 10,
"actuation_size": 1}
self.kubejobs1 = KubeJobs({"redis_ip": "0.0.0.0",
"redis_port": "2352",
"application_id": "00001",
"control_parameters": data1})
self.kubejobs2 = KubeJobs({"redis_ip": "0.0.0.0",
"redis_port": "2352",
"application_id": "00002",
"control_parameters": data2})
self.kubejobs1.metric_source = \
MetricSourceMock("2017-08-06T07:00:00.000Z", -2)
self.kubejobs1.actuator = ActuatorMock()
# self.kubejobs1.scheduler = SchedulerMock()
self.kubejobs2.metric_source = \
MetricSourceMock("2018-11-26T15:00:00.000Z", 0.0002)
self.kubejobs2.actuator = ActuatorMock()
# self.kubejobs2.scheduler = SchedulerMock()
"""
"""
def tearDown(self):
pass
"""
Test that if necessary, the number of replicas is increased, or not.
"""
def test_check_application_state(self):
initial_replicas1 = self.kubejobs1.actuator.get_number_of_replicas()
self.kubejobs1.check_application_state()
final_replicas1 = self.kubejobs1.actuator.get_number_of_replicas()
self.assertTrue(final_replicas1 > initial_replicas1)
initial_replicas2 = self.kubejobs2.actuator.get_number_of_replicas()
self.kubejobs2.check_application_state()
final_replicas2 = self.kubejobs2.actuator.get_number_of_replicas()
self.assertTrue(final_replicas2 == initial_replicas2)
def test_scale(self):
self.kubejobs1.actuator.adjust_resources(4)
self.assertEqual(self.kubejobs1.actuator.get_number_of_replicas(), 4)
self.kubejobs1.actuator.\
adjust_resources(self.kubejobs1.actuator.
get_number_of_replicas() - 2)
self.assertEqual(self.kubejobs1.actuator.get_number_of_replicas(), 2)
self.kubejobs1.actuator.\
adjust_resources(self.kubejobs1.actuator.
get_number_of_replicas() + 8)
self.assertEqual(self.kubejobs1.actuator.get_number_of_replicas(), 10)
"""
Test that the function _get_progress_error returns the progress
error correct.
"""
def test_get_progress_error(self):
self.assertEqual(self.kubejobs2._get_progress_error("00001"),
(datetime.strptime("2018-11-26T15:00:00.000Z",
'%Y-%m-%dT%H:%M:%S.%fZ'), 0.0002))
self.assertEqual(self.kubejobs1._get_progress_error("00002"),
(datetime.strptime("2017-08-06T07:00:00.000Z",
'%Y-%m-%dT%H:%M:%S.%fZ'), -2))
"""
Test that the function _check_measurements_are_new works correctly.
"""
def test_check_measurements_are_new(self):
self.assertFalse(self.kubejobs1._check_measurements_are_new(
datetime.strptime("0001-01-01T00:00:00.0Z",
'%Y-%m-%dT%H:%M:%S.%fZ')))
self.assertTrue(self.kubejobs1._check_measurements_are_new(
datetime.strptime("2017-08-06T07:00:00.000Z",
'%Y-%m-%dT%H:%M:%S.%fZ')))
"""
Test that the status returned is correct.
"""
def test_status(self):
self.kubejobs1.metric_source = MetricSourceMock(
"2018-11-26T15:00:00.000Z", 0.0001)
initial_state1 = ""
self.assertEqual(self.kubejobs1.status(), initial_state1)
final_state1 = "Progress error-[%s]-%f" % \
self.kubejobs1._get_progress_error("00001")
self.kubejobs1.check_application_state()
self.assertEqual(self.kubejobs1.status(), final_state1)
self.kubejobs2.metric_source = MetricSourceMock(
"0001-01-01T00:00:00.0Z", 0.0002)
initial_state2 = ""
self.assertEqual(self.kubejobs2.status(), initial_state2)
final_state2 = "Progress error-[%s]-%f" % \
self.kubejobs2._get_progress_error("00002") \
+ " Could not acquire more recent metrics"
self.kubejobs2.check_application_state()
self.assertEqual(self.kubejobs2.status(), final_state2)
class TestKubeJobs(unittest.TestCase):
"""
Set up KubeJobs alarm objects
"""
def setUp(self):
metric_source_1 = MetricSourceMock("2018-11-26T15:00:00.000Z", -2)
actuator = ActuatorMock()
trigger_down = 1
trigger_up = 1
min_cap = 2
max_cap = 10
actuation_size = 3
application_id_1 = "00001"
application_id_2 = "00002"
metric_source_2 = MetricSourceMock("2017-08-06T07:00:00.000Z", 0.0002)
self.kubejobs1 = KubeJobs(actuator, metric_source_1, trigger_down,
trigger_up, min_cap, max_cap, actuation_size,
application_id_1)
self.kubejobs2 = KubeJobs(actuator, metric_source_2, trigger_down,
trigger_up, min_cap, max_cap, actuation_size,
application_id_2)
"""
"""
def tearDown(self):
pass
"""
Test that if necessary, the number of replicas is increased, or not.
"""
def test_check_application_state(self):
initial_replicas1 = self.kubejobs1.actuator.get_number_of_replicas()
self.kubejobs1.check_application_state()
final_replicas1 = self.kubejobs1.actuator.get_number_of_replicas()
self.assertTrue(final_replicas1 > initial_replicas1)
initial_replicas2 = self.kubejobs2.actuator.get_number_of_replicas()
self.kubejobs2.check_application_state()
final_replicas2 = self.kubejobs2.actuator.get_number_of_replicas()
self.assertTrue(final_replicas2 == initial_replicas2)
"""
Test that the scale down works, decreasing the number of replicas.
"""
def test_scale_down(self):
self.kubejobs1.actuator.replicas = 10
self.kubejobs1._scale_down(2)
self.assertEqual(self.kubejobs1.actuator.get_number_of_replicas(), 7)
self.kubejobs1._scale_down(2)
self.assertEqual(self.kubejobs1.actuator.get_number_of_replicas(), 4)
self.kubejobs1._scale_down(2)
self.assertEqual(self.kubejobs1.actuator.get_number_of_replicas(), 2)
"""
Test that the scale down works, increasing the number of replicas.
"""
def test_scale_up(self):
self.kubejobs1._scale_up(-2)
self.assertEqual(self.kubejobs1.actuator.get_number_of_replicas(), 4)
self.kubejobs1._scale_up(-2)
self.assertEqual(self.kubejobs1.actuator.get_number_of_replicas(), 7)
self.kubejobs1._scale_up(-2)
self.assertEqual(self.kubejobs1.actuator.get_number_of_replicas(), 10)
"""
Test that the function _get_progress_error returns the progress
error correct.
"""
def test_get_progress_error(self):
self.assertEqual(self.kubejobs1._get_progress_error("00001"),
(datetime.strptime("2018-11-26T15:00:00.000Z",
'%Y-%m-%dT%H:%M:%S.%fZ'), -2))
self.assertEqual(self.kubejobs2._get_progress_error("00002"),
(datetime.strptime("2017-08-06T07:00:00.000Z",
'%Y-%m-%dT%H:%M:%S.%fZ'), 0.0002))
"""
Test that the function _check_measurements_are_new works correctly.
"""
def test_check_measurements_are_new(self):
self.assertFalse(
self.kubejobs1._check_measurements_are_new(
datetime.strptime("0001-01-01T00:00:00.0Z",
'%Y-%m-%dT%H:%M:%S.%fZ')))
self.assertTrue(
self.kubejobs1._check_measurements_are_new(
datetime.strptime("2017-08-06T07:00:00.000Z",
'%Y-%m-%dT%H:%M:%S.%fZ')))
"""
Test that the status returned is correct.
"""
def test_status(self):
self.kubejobs1.metric_source = MetricSourceMock(
"2018-11-26T15:00:00.000Z", 0.0001)
initial_state1 = ""
final_state1 = "Progress error-[%s]-%f" % \
self.kubejobs1._get_progress_error("00001")
self.assertEqual(self.kubejobs1.status(), initial_state1)
self.kubejobs1.check_application_state()
self.assertEqual(self.kubejobs1.status(), final_state1)
self.kubejobs2.metric_source = MetricSourceMock(
"0001-01-01T00:00:00.0Z", 0.0002)
initial_state2 = ""
final_state2 = "Progress error-[%s]-%f" % \
self.kubejobs2._get_progress_error("00002") \
+ " Could not acquire more recent metrics"
self.assertEqual(self.kubejobs2.status(), initial_state2)
self.kubejobs2.check_application_state()
self.assertEqual(self.kubejobs2.status(), final_state2)