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# Copyright 2022-2023 ETSI TeraFlowSDN - TFS OSG (https://tfs.etsi.org/)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

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from typing import Tuple, Any
from confluent_kafka import Consumer as KafkaConsumer
from common.proto.context_pb2 import Empty
from monitoring.service.NameMapping import NameMapping
from confluent_kafka import Producer as KafkaProducer
from confluent_kafka import KafkaException
from common.proto.telemetry_frontend_pb2 import CollectorId, Collector, CollectorFilter, CollectorList
from common.method_wrappers.Decorator import MetricsPool, safe_and_metered_rpc_method
from common.proto.telemetry_frontend_pb2_grpc import TelemetryFrontendServiceServicer

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LOGGER = logging.getLogger(__name__)
METRICS_POOL = MetricsPool('Monitoring', 'TelemetryFrontend')
KAFKA_SERVER_IP = '127.0.0.1:9092'
ACTIVE_COLLECTORS = []
KAFKA_TOPICS = {'request' : 'topic_request',
'response': 'topic_response'}
class TelemetryFrontendServiceServicerImpl(TelemetryFrontendServiceServicer):
def __init__(self, name_mapping : NameMapping):
LOGGER.info('Init TelemetryFrontendService')
# @safe_and_metered_rpc_method(METRICS_POOL, LOGGER)
def StartCollector(self,
request : Collector, grpc_context: grpc.ServicerContext # type: ignore
) -> CollectorId: # type: ignore
# push info to frontend db
_collector_id = str(request.collector_id.collector_id.uuid)
_collector_kpi_id = str(request.kpi_id.kpi_id.uuid)
_collector_duration = int(request.duration_s)
_collector_interval = int(request.interval_s)
self.generate_kafka_request(_collector_id, _collector_kpi_id, _collector_duration, _collector_interval)
# self.run_generate_kafka_request(_collector_id, _collector_kpi_id, _collector_duration, _collector_interval)
response.collector_id.uuid = request.collector_id.collector_id.uuid # type: ignore
return response
def run_generate_kafka_request(self, msg_key: str, kpi: str, duration : int, interval: int):
threading.Thread(target=self.generate_kafka_request, args=(msg_key, kpi, duration, interval)).start()
# @safe_and_metered_rpc_method(METRICS_POOL, LOGGER)
def generate_kafka_request(self,
msg_key: str, kpi: str, duration : int, interval: int
) -> KafkaProducer:
"""
Method to generate collector request to Kafka topic.
"""
producer_configs = {
'bootstrap.servers': KAFKA_SERVER_IP,
}
# topic_request = "topic_request"
msg_value = Tuple [str, int, int]
msg_value = (kpi, duration, interval)
print ("Request generated: ", "Colletcor Id: ", msg_key, \
", \nKPI: ", kpi, ", Duration: ", duration, ", Interval: ", interval)
producerObj = KafkaProducer(producer_configs)
producerObj.produce(KAFKA_TOPICS['request'], key=msg_key, value= str(msg_value), callback=self.delivery_callback)
# producerObj.produce(topic_request, key=msg_key, value= str(msg_value), callback=self.delivery_callback)

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ACTIVE_COLLECTORS.append(msg_key)
producerObj.flush()
return producerObj
def run_kafka_listener(self):
# print ("--- STARTED: run_kafka_listener ---")
threading.Thread(target=self.kafka_listener).start()
return True
def kafka_listener(self):
"""
listener for response on Kafka topic.
"""
# print ("--- STARTED: kafka_listener ---")
conusmer_configs = {
'bootstrap.servers' : KAFKA_SERVER_IP,
'group.id' : 'frontend',
'auto.offset.reset' : 'latest'
}
# topic_response = "topic_response"
consumerObj.subscribe([KAFKA_TOPICS['response']])
# print (time.time())
while True:
receive_msg = consumerObj.poll(2.0)
if receive_msg is None:
print (" - Telemetry frontend listening on Kafka Topic: ", KAFKA_TOPICS['response']) # added for debugging purposes
continue
elif receive_msg.error():
if receive_msg.error().code() == KafkaError._PARTITION_EOF:
continue
else:
print("Consumer error: {}".format(receive_msg.error()))
break

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try:
collector_id = receive_msg.key().decode('utf-8')
if collector_id in ACTIVE_COLLECTORS:
(kpi_id, kpi_value) = ast.literal_eval(receive_msg.value().decode('utf-8'))
self.process_response(kpi_id, kpi_value)
else:
print(f"collector id does not match.\nRespone ID: '{collector_id}' --- Active IDs: '{ACTIVE_COLLECTORS}' ")
except Exception as e:
print(f"No message key found: {str(e)}")
continue
# return None

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def process_response(self, kpi_id: str, kpi_value: Any):
print ("Frontend - KPI: ", kpi_id, ", VALUE: ", kpi_value)
@safe_and_metered_rpc_method(METRICS_POOL, LOGGER)
def delivery_callback(self, err, msg):
"""
Callback function to handle message delivery status.
Args:
err (KafkaError): Kafka error object.
msg (Message): Kafka message object.
"""
if err:
print(f'Message delivery failed: {err}')
else:
print(f'Message delivered to topic {msg.topic()}')
@safe_and_metered_rpc_method(METRICS_POOL, LOGGER)
def StopCollector(self,
request : CollectorId, grpc_context: grpc.ServicerContext # type: ignore
) -> Empty: # type: ignore
request.collector_id.uuid = ""
return Empty()
@safe_and_metered_rpc_method(METRICS_POOL, LOGGER)
def SelectCollectors(self,
request : CollectorFilter, contextgrpc_context: grpc.ServicerContext # type: ignore
) -> CollectorList: # type: ignore
response = CollectorList()
return response