def main():
'''Main entrypoint for gRPC server.'''
args = setup_arguments()
log = Logger()
if args.file_type == "local":
file_system = FileSystem(fstype=FileSystemType.FSTYPE_LOCAL)
file_system.impl.remote_root_dirpath = tempfile.mkdtemp()
dao = FileDataStore(file_system=file_system)
else:
dao = FileDataStore()
# create a gRPC server
server = grpc.server(futures.ThreadPoolExecutor(max_workers=10))
handler = AlamedaServicer(dao)
# use the generated function `add_CalculatorServicer_to_server`
# to add the defined class to the created server
ai_service_pb2_grpc.add_AlamendaAIServiceServicer_to_server(
handler, server)
# listen on port 50051
log.info('Starting server. Listening on port 50051.')
server.add_insecure_port('[::]:50051')
server.start()
# since server.start() will not block,
# a sleep-loop is added to keep alive
try:
while True:
time.sleep(_ONE_DAY_IN_SECONDS)
except KeyboardInterrupt:
server.stop(0)
class MockMetricDAO(object):
''' Mock DAO '''
def __init__(self):
self.logger = Logger()
def write_container_recommendation_result(self, recommendations):
''' Write the recommendation '''
self.logger.info("Write recommendation result: %s", str(recommendations))
def write_container_prediction_data(self, predictions):
''' Write predictions '''
self.logger.info("Write prediction result: %s", str(predictions))
def get_container_observed_data(self, metric_type, namespace, pod_name, duration):
# pylint: disable=line-too-long
''' Get metrics '''
self.logger.info("Get observed data: metric_type=%s, "
" namespace=%s, pod_name=%s, duration=%s",
str(metric_type), str(namespace),
str(pod_name), str(duration))
return [
{
"data": [{"time": 1540970511, "value": 0.11933598524417476}, {"time": 1540970541, "value": 0.12222222222222222}, {"time": 1540970571, "value": 0.1211138025288804}, {"time": 1540970601, "value": 0.12064253815904132}, {"time": 1540970631, "value": 0.11799999999994824}, {"time": 1540970661, "value": 0.1175581679593074}, {"time": 1540970691, "value": 0.11978842563782154}, {"time": 1540970721, "value": 0.11999733339262363}, {"time": 1540970751, "value": 0.1177777777777616}, {"time": 1540970781, "value": 0.11555812351387203}, {"time": 1540970811, "value": 0.1153358963532232}, {"time": 1540970841, "value": 0.115775204995506}, {"time": 1540970871, "value": 0.11378536346865305}, {"time": 1540970901, "value": 0.11199751116643794}, {"time": 1540970931, "value": 0.11200248894413732}, {"time": 1540970961, "value": 0.11422222222220929}, {"time": 1540970991, "value": 0.11044444444447031}, {"time": 1540971021, "value": 0.11088642474615233}, {"time": 1540971051, "value": 0.11486591570570893}, {"time": 1540971081, "value": 0.12333607413496463}, {"time": 1540971111, "value": 0.12533611858039997}, {"time": 1540971141, "value": 0.12222222222222222}, {"time": 1540971171, "value": 0.12333333333331715}, {"time": 1540971201, "value": 0.12421670147993745}, {"time": 1540971231, "value": 0.1242498332962913}, {"time": 1540971261, "value": 0.12088083016684867}, {"time": 1540971291, "value": 0.12177236567262706}, {"time": 1540971321, "value": 0.12444444444449294}, {"time": 1540971351, "value": 0.12422774345526791}, {"time": 1540971381, "value": 0.12112187750023842}, {"time": 1540971411, "value": 0.11888888888885656}, {"time": 1540971441, "value": 0.11644703215630572}, {"time": 1540971471, "value": 0.1171111111111208}, {"time": 1540971501, "value": 0.12021687924980788}, {"time": 1540971531, "value": 0.12088888888885978}, {"time": 1540971561, "value": 0.11955289882449321}, {"time": 1540971591, "value": 0.11533845948714005}, {"time": 1540971621, "value": 0.11353284898577133}, {"time": 1540971651, "value": 0.11400253338957268}, {"time": 1540971681, "value": 0.1135378941052935}, {"time": 1540971711, "value": 0.1135732225012909}, {"time": 1540971741, "value": 0.11418923422121205}, {"time": 1540971771, "value": 0.11734376389017855}, {"time": 1540971801, "value": 0.1191164051735762}, {"time": 1540971831, "value": 0.11825112805359857}, {"time": 1540971861, "value": 0.11752682677569645}, {"time": 1540971891, "value": 0.1177777777777616}, {"time": 1540971921, "value": 0.11911640517349537}, {"time": 1540971951, "value": 0.11914553093108997}, {"time": 1540971981, "value": 0.12266666666667637}, {"time": 1540972011, "value": 0.123333333333398}, {"time": 1540972041, "value": 0.1213252449837292}, {"time": 1540972071, "value": 0.1168888888888533}, {"time": 1540972101, "value": 0.11799999999994824}, {"time": 1540972131, "value": 0.12133872616558795}, {"time": 1540972161, "value": 0.12422222222222544}, {"time": 1540972191, "value": 0.12510833092600207}, {"time": 1540972221, "value": 0.12311658295926203}, {"time": 1540972251, "value": 0.12266121505711827}, {"time": 1540972281, "value": 0.12288888888886301}, {"time": 1540972311, "value": 0.1226639408012444}, {"time": 1540972341, "value": 0.12044979776883176}, {"time": 1540972371, "value": 0.11755555555557495}, {"time": 1540972401, "value": 0.11776730957254714}, {"time": 1540972431, "value": 0.11821959512010198}, {"time": 1540972461, "value": 0.11955555555557819}, {"time": 1540972491, "value": 0.1144546181882349}, {"time": 1540972521, "value": 0.1135580790684367}, {"time": 1540972551, "value": 0.11133333333329776}, {"time": 1540972581, "value": 0.11666925931687372}, {"time": 1540972611, "value": 0.1191111111110432}, {"time": 1540972641, "value": 0.12042838732617632}, {"time": 1540972671, "value": 0.12177507166506443}, {"time": 1540972701, "value": 0.12218420935708889}, {"time": 1540972731, "value": 0.11912699471041878}, {"time": 1540972761, "value": 0.11464373791907961}, {"time": 1540972791, "value": 0.11247943804742164}, {"time": 1540972821, "value": 0.11578035067444005}, {"time": 1540972851, "value": 0.1169122713432028}, {"time": 1540972881, "value": 0.11510855314326997}, {"time": 1540972911, "value": 0.10976070389047683}, {"time": 1540972941, "value": 0.10822462721391547}, {"time": 1540972971, "value": 0.10778017289269862}, {"time": 1540973001, "value": 0.11223968172825266}, {"time": 1540973031, "value": 0.11221723478954873}, {"time": 1540973061, "value": 0.11421968400700915}, {"time": 1540973091, "value": 0.11333081487082916}, {"time": 1540973121, "value": 0.11089135314121648}, {"time": 1540973151, "value": 0.10466666666672811}, {"time": 1540973181, "value": 0.10732856317492798}, {"time": 1540973211, "value": 0.10955555555556203}],
"labels": {"namespace": "default", "pod_name": "router-2-m7vx8", "container_name": "router1"}
},
{
"data": [{"time": 1540970511, "value": 0.11933598524417476}, {"time": 1540970541, "value": 0.12222222222222222}, {"time": 1540970571, "value": 0.1211138025288804}, {"time": 1540970601, "value": 0.12064253815904132}, {"time": 1540970631, "value": 0.11799999999994824}, {"time": 1540970661, "value": 0.1175581679593074}, {"time": 1540970691, "value": 0.11978842563782154}, {"time": 1540970721, "value": 0.11999733339262363}, {"time": 1540970751, "value": 0.1177777777777616}, {"time": 1540970781, "value": 0.11555812351387203}, {"time": 1540970811, "value": 0.1153358963532232}, {"time": 1540970841, "value": 0.115775204995506}, {"time": 1540970871, "value": 0.11378536346865305}, {"time": 1540970901, "value": 0.11199751116643794}, {"time": 1540970931, "value": 0.11200248894413732}, {"time": 1540970961, "value": 0.11422222222220929}, {"time": 1540970991, "value": 0.11044444444447031}, {"time": 1540971021, "value": 0.11088642474615233}, {"time": 1540971051, "value": 0.11486591570570893}, {"time": 1540971081, "value": 0.12333607413496463}, {"time": 1540971111, "value": 0.12533611858039997}, {"time": 1540971141, "value": 0.12222222222222222}, {"time": 1540971171, "value": 0.12333333333331715}, {"time": 1540971201, "value": 0.12421670147993745}, {"time": 1540971231, "value": 0.1242498332962913}, {"time": 1540971261, "value": 0.12088083016684867}, {"time": 1540971291, "value": 0.12177236567262706}, {"time": 1540971321, "value": 0.12444444444449294}, {"time": 1540971351, "value": 0.12422774345526791}, {"time": 1540971381, "value": 0.12112187750023842}, {"time": 1540971411, "value": 0.11888888888885656}, {"time": 1540971441, "value": 0.11644703215630572}, {"time": 1540971471, "value": 0.1171111111111208}, {"time": 1540971501, "value": 0.12021687924980788}, {"time": 1540971531, "value": 0.12088888888885978}, {"time": 1540971561, "value": 0.11955289882449321}, {"time": 1540971591, "value": 0.11533845948714005}, {"time": 1540971621, "value": 0.11353284898577133}, {"time": 1540971651, "value": 0.11400253338957268}, {"time": 1540971681, "value": 0.1135378941052935}, {"time": 1540971711, "value": 0.1135732225012909}, {"time": 1540971741, "value": 0.11418923422121205}, {"time": 1540971771, "value": 0.11734376389017855}, {"time": 1540971801, "value": 0.1191164051735762}, {"time": 1540971831, "value": 0.11825112805359857}, {"time": 1540971861, "value": 0.11752682677569645}, {"time": 1540971891, "value": 0.1177777777777616}, {"time": 1540971921, "value": 0.11911640517349537}, {"time": 1540971951, "value": 0.11914553093108997}, {"time": 1540971981, "value": 0.12266666666667637}, {"time": 1540972011, "value": 0.123333333333398}, {"time": 1540972041, "value": 0.1213252449837292}, {"time": 1540972071, "value": 0.1168888888888533}, {"time": 1540972101, "value": 0.11799999999994824}, {"time": 1540972131, "value": 0.12133872616558795}, {"time": 1540972161, "value": 0.12422222222222544}, {"time": 1540972191, "value": 0.12510833092600207}, {"time": 1540972221, "value": 0.12311658295926203}, {"time": 1540972251, "value": 0.12266121505711827}, {"time": 1540972281, "value": 0.12288888888886301}, {"time": 1540972311, "value": 0.1226639408012444}, {"time": 1540972341, "value": 0.12044979776883176}, {"time": 1540972371, "value": 0.11755555555557495}, {"time": 1540972401, "value": 0.11776730957254714}, {"time": 1540972431, "value": 0.11821959512010198}, {"time": 1540972461, "value": 0.11955555555557819}, {"time": 1540972491, "value": 0.1144546181882349}, {"time": 1540972521, "value": 0.1135580790684367}, {"time": 1540972551, "value": 0.11133333333329776}, {"time": 1540972581, "value": 0.11666925931687372}, {"time": 1540972611, "value": 0.1191111111110432}, {"time": 1540972641, "value": 0.12042838732617632}, {"time": 1540972671, "value": 0.12177507166506443}, {"time": 1540972701, "value": 0.12218420935708889}, {"time": 1540972731, "value": 0.11912699471041878}, {"time": 1540972761, "value": 0.11464373791907961}, {"time": 1540972791, "value": 0.11247943804742164}, {"time": 1540972821, "value": 0.11578035067444005}, {"time": 1540972851, "value": 0.1169122713432028}, {"time": 1540972881, "value": 0.11510855314326997}, {"time": 1540972911, "value": 0.10976070389047683}, {"time": 1540972941, "value": 0.10822462721391547}, {"time": 1540972971, "value": 0.10778017289269862}, {"time": 1540973001, "value": 0.11223968172825266}, {"time": 1540973031, "value": 0.11221723478954873}, {"time": 1540973061, "value": 0.11421968400700915}, {"time": 1540973091, "value": 0.11333081487082916}, {"time": 1540973121, "value": 0.11089135314121648}, {"time": 1540973151, "value": 0.10466666666672811}, {"time": 1540973181, "value": 0.10732856317492798}, {"time": 1540973211, "value": 0.10955555555556203}],
"labels": {"namespace": "default", "pod_name": "router-2-m7vx8", "container_name": "router2"}
}
]
def main():
'''Main entrypoint for workload prediction.'''
log = Logger()
log.info("Start workload prediction.")
# workload predictor
predictor_log = Logger(name='workload_prediction',
logfile='/var/log/workload_prediction.log',
level=LogLevel.LV_DEBUG)
predictor = WorkloadPredictor(log=predictor_log)
# file datastore to get pod list
dao = FileDataStore()
while True:
pod_list = dao.read_data()
for k, v in pod_list.items():
try:
pod = {
"namespace": k[0],
"uid": k[1],
"pod_name": k[2],
"type": v["type"],
"policy": v["policy"]
}
except (IndexError, KeyError):
log.error(
"Not predicting POD %s:%s, "
"due to wrong format of pod info.", k, v)
continue
predictor.predict(pod)
time.sleep(60)
log.info("Workload prediction is completed.")
def main():
'''Main entrypoint for demo server.'''
svc_rootpath = '/alameda-ai/services/arima'
pyscripts = ['grpc_server.py', 'workload_prediction.py']
log = Logger()
log.info("Start demo server.")
for script in pyscripts:
log.info("Start to run", script)
script_path = os.path.join(svc_rootpath, script)
subprocess.Popen(['python3', script_path])
while True:
time.sleep(60)
log.info("Demo server is completed.")
class MetricDAO(object):
''' Metric DAO '''
def __init__(self, config=None):
''' The construct methdo '''
if not config:
config = {
"metric_server": get_metric_server_address()
}
self.config = config
self.logger = Logger()
self.logger.info("Metric DAO config: %s", str(self.config))
def __get_client(self):
''' Get the grpc client '''
conn_str = self.config["metric_server"]
channel = grpc.insecure_channel(conn_str)
return server_pb2_grpc.OperatorServiceStub(channel)
def __get_metric_type_value(self, metric_type):
''' Get the metric type '''
if metric_type == "cpu":
key = "CONTAINER_CPU_USAGE_TOTAL"
elif metric_type == "cpu_rate":
key = "CONTAINER_CPU_USAGE_TOTAL_RATE"
elif metric_type == "memory":
key = "CONTAINER_MEMORY_USAGE"
else:
key = "CONTAINER_CPU_USAGE_TOTAL"
# default return cpu
return server_pb2.MetricType.Value(key)
def __get_op_type_value(self, op_type):
''' Get the op type '''
if op_type == "equal":
key = "Equal"
else:
key = "NotEqual"
return server_pb2.StrOp.Value(key)
def __parse_prediction(self, data):
''' Parse the prediction data '''
result = server_pb2.PredictData()
result.time.FromSeconds(data["time"])
result.value = data["value"]
return result
def __parse_recommendation(self, data):
''' Parse recommendation '''
result = server_pb2.Recommendation()
result.time.FromSeconds(data["time"])
result.resource.CopyFrom(self.__parse_resource(data["resources"]))
return result
def __parse_time_series(self, data):
''' Parse time series data '''
result = server_pb2.TimeSeriesData()
predict_data = list(map(self.__parse_prediction, data))
result.predict_data.extend(predict_data)
return result
def __parse_container_prediction_data(self, data):
''' Parse the container prediction data '''
if not data:
return []
result = server_pb2.PredictContainer()
if "container_name" in data:
result.name = data["container_name"]
if "raw_predict" in data:
for k, v in data["raw_predict"].items():
time_series = self.__parse_time_series(v)
result.row_predict_data[k].CopyFrom(time_series)
if "recommendations" in data:
result.recommendations.extend(list(
map(self.__parse_recommendation, data["recommendations"])
))
if "init_resource" in data:
result.initial_resource.CopyFrom(
self.__parse_resource(data["init_resource"])
)
return result
def __parse_resource(self, data):
''' Parse the resource data '''
resource = server_pb2.Resource()
for k, v in data["limits"].items():
resource.limit[k] = v
for k, v in data["requests"].items():
resource.request[k] = v
return resource
def __parse_sample(self, data):
''' Parse the sample data '''
return {
"time": data.time.seconds,
"value": data.value
}
def __parse_metrics(self, data):
''' Parse the metrics '''
result = []
if not data:
return result
for d in data:
r = {"labels": {}}
for k, v in d.labels.items():
r["labels"][k] = v
# add the sample data
r["data"] = list(
map(self.__parse_sample, d.samples)
)
result.append(r)
return result
def write_container_prediction_data(self, prediction):
''' Write the prediction result to server. '''
self.logger.info("Write prediction result: %s", str(prediction))
req = server_pb2.CreatePredictResultRequest()
pod = req.predict_pods.add()
pod.uid = prediction["uid"]
pod.namespace = prediction["namespace"]
pod.name = prediction["pod_name"]
pod.predict_containers.extend(list(
map(self.__parse_container_prediction_data,
prediction["containers"]
)
))
try:
client = self.__get_client()
resp = client.CreatePredictResult(req)
if resp.status.code != 0:
msg = "Write prediction error [code={}]".format(resp.status.code)
raise Exception(msg)
except Exception as e:
self.logger.error("Could not get metrics: %s", str(e))
raise e
def write_container_recommendation_result(self, data):
''' Write the container recommendation result '''
self.write_container_prediction_data(data)
def get_container_observed_data(self, metric_type, namespace_name, pod_name, duration):
''' Get the observed metrics '''
self.logger.info("Get observed data: metric_type=%s, "
" namespace=%s, pod_name=%s, duration=%s",
str(metric_type), str(namespace_name),
str(pod_name), str(duration))
req = server_pb2.ListMetricsRequest()
req.metric_type = self.__get_metric_type_value(metric_type)
req.duration.seconds = duration
# setup the query conditions
namespace = req.conditions.add()
namespace.key = u"namespace"
namespace.op = self.__get_op_type_value("equal")
namespace.value = namespace_name
pod = req.conditions.add()
pod.key = u"pod_name"
pod.op = self.__get_op_type_value("equal")
pod.value = pod_name
try:
client = self.__get_client()
resp = client.ListMetrics(req)
if resp.status.code == 0:
return self.__parse_metrics(resp.metrics)
else:
msg = "List metric error [code={}]".format(resp.status.code)
raise Exception(msg)
except Exception as e:
self.logger.error("Could not get metrics: %s", str(e))
raise e