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TelemetryFrontendServiceServicerImpl.py
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TelemetryFrontendServiceServicerImpl.py 8.39 KiB
# Copyright 2022-2024 ETSI OSG/SDG TeraFlowSDN (TFS) (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.
import json
import threading
from typing import Any, Dict
import grpc
import logging
from common.method_wrappers.Decorator import MetricsPool, safe_and_metered_rpc_method
from common.tools.kafka.Variables import KafkaConfig, KafkaTopic
from common.proto.context_pb2 import Empty
from common.proto.telemetry_frontend_pb2 import CollectorId, Collector, CollectorFilter, CollectorList
from common.proto.telemetry_frontend_pb2_grpc import TelemetryFrontendServiceServicer
from telemetry.database.TelemetryModel import Collector as CollectorModel
# from telemetry.database.Telemetry_DB import TelemetryDB
from ...database.new_Telemetry_DB import TelemetryDB
from confluent_kafka import Consumer as KafkaConsumer
from confluent_kafka import Producer as KafkaProducer
from confluent_kafka import KafkaError
LOGGER = logging.getLogger(__name__)
METRICS_POOL = MetricsPool('TelemetryFrontend', 'NBIgRPC')
ACTIVE_COLLECTORS = [] # keep and can be populated from DB
class TelemetryFrontendServiceServicerImpl(TelemetryFrontendServiceServicer):
def __init__(self):
LOGGER.info('Init TelemetryFrontendService')
self.tele_db_obj = TelemetryDB()
self.kafka_producer = KafkaProducer({'bootstrap.servers' : KafkaConfig.get_kafka_address()})
self.kafka_consumer = KafkaConsumer({'bootstrap.servers' : KafkaConfig.get_kafka_address(),
'group.id' : 'frontend',
'auto.offset.reset' : 'latest'})
@safe_and_metered_rpc_method(METRICS_POOL, LOGGER)
def StartCollector(self,
request : Collector, grpc_context: grpc.ServicerContext # type: ignore
) -> CollectorId: # type: ignore
LOGGER.info ("gRPC message: {:}".format(request))
response = CollectorId()
# TODO: Verify the presence of Kpi ID in KpiDB or assume that KPI ID already exists?
self.tele_db_obj.add_row_to_db(
CollectorModel.ConvertCollectorToRow(request)
)
self.PublishStartRequestOnKafka(request)
response.collector_id.uuid = request.collector_id.collector_id.uuid
return response
def PublishStartRequestOnKafka(self, collector_obj):
"""
Method to generate collector request on Kafka.
"""
collector_uuid = collector_obj.collector_id.collector_id.uuid
collector_to_generate : Dict = {
"kpi_id" : collector_obj.kpi_id.kpi_id.uuid,
"duration": collector_obj.duration_s,
"interval": collector_obj.interval_s
}
self.kafka_producer.produce(
KafkaTopic.REQUEST.value,
key = collector_uuid,
value = json.dumps(collector_to_generate),
callback = self.delivery_callback
)
LOGGER.info("Collector Request Generated: Collector Id: {:}, Value: {:}".format(collector_uuid, collector_to_generate))
ACTIVE_COLLECTORS.append(collector_uuid)
self.kafka_producer.flush()
@safe_and_metered_rpc_method(METRICS_POOL, LOGGER)
def StopCollector(self,
request : CollectorId, grpc_context: grpc.ServicerContext # type: ignore
) -> Empty: # type: ignore
LOGGER.info ("gRPC message: {:}".format(request))
try:
collector_to_delete = request.collector_id.uuid
self.tele_db_obj.delete_db_row_by_id(
CollectorModel, "collector_id", collector_to_delete
)
self.PublishStopRequestOnKafka(request)
except Exception as e:
LOGGER.error('Unable to delete collector. Error: {:}'.format(e))
return Empty()
def PublishStopRequestOnKafka(self, collector_id):
"""
Method to generate stop collector request on Kafka.
"""
collector_uuid = collector_id.collector_id.uuid
collector_to_stop : Dict = {
"kpi_id" : collector_uuid,
"duration": -1,
"interval": -1
}
self.kafka_producer.produce(
KafkaTopic.REQUEST.value,
key = collector_uuid,
value = json.dumps(collector_to_stop),
callback = self.delivery_callback
)
LOGGER.info("Collector Stop Request Generated: Collector Id: {:}, Value: {:}".format(collector_uuid, collector_to_stop))
try:
ACTIVE_COLLECTORS.remove(collector_uuid)
except ValueError:
LOGGER.warning('Collector ID {:} not found in active collector list'.format(collector_uuid))
self.kafka_producer.flush()
@safe_and_metered_rpc_method(METRICS_POOL, LOGGER)
def SelectCollectors(self,
request : CollectorFilter, contextgrpc_context: grpc.ServicerContext # type: ignore
) -> CollectorList: # type: ignore
LOGGER.info("gRPC message: {:}".format(request))
response = CollectorList()
try:
rows = self.tele_db_obj.select_with_filter(CollectorModel, request)
except Exception as e:
LOGGER.info('Unable to apply filter on kpi descriptor. {:}'.format(e))
try:
for row in rows:
collector_obj = CollectorModel.ConvertRowToCollector(row)
response.collector_list.append(collector_obj)
return response
except Exception as e:
LOGGER.info('Unable to process filter response {:}'.format(e))
@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:
LOGGER.debug('Message delivery failed: {:}'.format(err))
print('Message delivery failed: {:}'.format(err))
# else:
# LOGGER.debug('Message delivered to topic {:}'.format(msg.topic()))
# print('Message delivered to topic {:}'.format(msg.topic()))
# ---------- Independent Method ---------------
# Listener method is independent of any method (same lifetime as service)
# continously listens for responses
def RunResponseListener(self):
threading.Thread(target=self.ResponseListener).start()
return True
def ResponseListener(self):
"""
listener for response on Kafka topic.
"""
self.kafka_consumer.subscribe([KafkaTopic.RESPONSE.value])
while True:
receive_msg = self.kafka_consumer.poll(2.0)
if receive_msg is None:
continue
elif receive_msg.error():
if receive_msg.error().code() == KafkaError._PARTITION_EOF:
continue
else:
print("Consumer error: {}".format(receive_msg.error()))
break
try:
collector_id = receive_msg.key().decode('utf-8')
if collector_id in ACTIVE_COLLECTORS:
kpi_value = json.loads(receive_msg.value().decode('utf-8'))
self.process_response(collector_id, kpi_value['kpi_id'], kpi_value['kpi_value'])
else:
print(f"collector id does not match.\nRespone ID: '{collector_id}' --- Active IDs: '{ACTIVE_COLLECTORS}' ")
except Exception as e:
print(f"Error extarcting msg key or value: {str(e)}")
continue
def process_response(self, collector_id: str, kpi_id: str, kpi_value: Any):
if kpi_id == "-1" and kpi_value == -1:
print ("Backend termination confirmation for collector id: ", collector_id)
else:
print ("KPI Value: Collector Id:", collector_id, ", Kpi Id:", kpi_id, ", Value:", kpi_value)