diff --git a/src/kpi_value_api/Dockerfile b/src/kpi_value_api/Dockerfile
index 7dd8d307b8338c4a29e97c742ca12a49c4611e0a..25b8da931f88000dd229c536456a3eb1fa7f56db 100644
--- a/src/kpi_value_api/Dockerfile
+++ b/src/kpi_value_api/Dockerfile
@@ -63,6 +63,8 @@ RUN python3 -m pip install -r requirements.txt
# Add component files into working directory
WORKDIR /var/teraflow
COPY src/kpi_value_api/. kpi_value_api/
+COPY src/kpi_manager/__init__.py kpi_manager/__init__.py
+COPY src/kpi_manager/client/. kpi_manager/client/
# Start the service
ENTRYPOINT ["python", "-m", "kpi_value_api.service"]
diff --git a/src/kpi_value_api/requirements.in b/src/kpi_value_api/requirements.in
index 7e4694109dc4e1d31b86abfc03162494faafcdaf..f5695906a8d02d55e15960a76986b8d03f02dba1 100644
--- a/src/kpi_value_api/requirements.in
+++ b/src/kpi_value_api/requirements.in
@@ -14,3 +14,4 @@
confluent-kafka==2.3.*
requests==2.27.*
+prometheus-api-client==0.5.3
\ No newline at end of file
diff --git a/src/kpi_value_api/service/KpiValueApiServiceServicerImpl.py b/src/kpi_value_api/service/KpiValueApiServiceServicerImpl.py
index 1559457d7fc80c3e9718c182f736b3f44abdeaea..b2ebecad00e65ac63f3681d43c317585f5dbe7ed 100644
--- a/src/kpi_value_api/service/KpiValueApiServiceServicerImpl.py
+++ b/src/kpi_value_api/service/KpiValueApiServiceServicerImpl.py
@@ -12,18 +12,23 @@
# See the License for the specific language governing permissions and
# limitations under the License.
-import logging, grpc, requests
+import logging, grpc
from typing import Tuple, Any
-from datetime import datetime
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.kpi_sample_types_pb2 import KpiSampleType
+from common.proto.kpi_manager_pb2 import KpiDescriptor, KpiId
from common.proto.kpi_value_api_pb2_grpc import KpiValueAPIServiceServicer
from common.proto.kpi_value_api_pb2 import KpiValueList, KpiValueFilter, KpiValue, KpiValueType
from confluent_kafka import Producer as KafkaProducer
+from prometheus_api_client import PrometheusConnect
+from prometheus_api_client.utils import parse_datetime
+
+from kpi_manager.client.KpiManagerClient import KpiManagerClient
LOGGER = logging.getLogger(__name__)
METRICS_POOL = MetricsPool('KpiValueAPI', 'NBIgRPC')
@@ -63,40 +68,67 @@ class KpiValueApiServiceServicerImpl(KpiValueAPIServiceServicer):
) -> KpiValueList:
LOGGER.debug('StoreKpiValues: Received gRPC message object: {:}'.format(request))
response = KpiValueList()
- metrics = [kpi.kpi_id for kpi in request.kpi_id]
- start_timestamps = [timestamp for timestamp in request.start_timestamp]
- end_timestamps = [timestamp for timestamp in request.end_timestamp]
- results = []
+
+ kpi_manager_client = KpiManagerClient()
+ prom_connect = PrometheusConnect(url=PROM_URL)
- for start, end in zip(start_timestamps, end_timestamps):
- start_str = datetime.fromtimestamp(start.seconds).isoformat() + "Z"
- end_str = datetime.fromtimestamp(end.seconds).isoformat() + "Z"
+ metrics = [self.GetKpiSampleType(kpi, kpi_manager_client) for kpi in request.kpi_id]
+ start_timestamps = [parse_datetime(timestamp) for timestamp in request.start_timestamp]
+ end_timestamps = [parse_datetime(timestamp) for timestamp in request.end_timestamp]
+ prom_response = []
+ for start_time, end_time in zip(start_timestamps, end_timestamps):
for metric in metrics:
- url = f'{PROM_URL}/api/v1/query_range'
- params = {
- 'query': metric,
- 'start': start_str,
- 'end' : end_str,
- 'step' : '30s' # or any other step you need
- }
- response = requests.get(url, params=params)
- if response.status_code == 200:
- data = response.json()
- for result in data['data']['result']:
- for value in result['values']:
- kpi_value = KpiValue(
- kpi_id=metric,
- timestamp=str(seconds=value[0]),
- kpi_value_type=self._convert_value_to_kpi_value_type(value[1])
- )
- results.append(kpi_value)
+ # print(start_time, end_time, metric)
+ prom_response.append(
+ prom_connect.custom_query_range(
+ query = metric, # this is the metric name and label config
+ start_time = start_time,
+ end_time = end_time,
+ step = 30, # or any other step value (missing in gRPC Filter request)
+ )
+ )
+
+ for single_resposne in prom_response:
+ # print ("{:}".format(single_resposne))
+ for record in single_resposne:
+ # print("Record >>> kpi: {:} >>> time & values set: {:}".format(record['metric']['__name__'], record['values']))
+ for value in record['values']:
+ # print("{:} - {:}".format(record['metric']['__name__'], value))
+ kpi_value = KpiValue()
+ kpi_value.kpi_id.kpi_id = record['metric']['__name__'],
+ kpi_value.timestamp = value[0],
+ kpi_value.kpi_value_type = self.ConverValueToKpiValueType(value[1])
+ response.kpi_value_list.append(kpi_value)
+ return response
+
+ def GetKpiSampleType(self, kpi_value: str, kpi_manager_client):
+ print("--- START -----")
- def _convert_value_to_kpi_value_type(self, value):
+ kpi_id = KpiId()
+ kpi_id.kpi_id.uuid = kpi_value.kpi_id.kpi_id.uuid
+ # print("KpiId generated: {:}".format(kpi_id))
+
+ try:
+ kpi_descriptor_object = KpiDescriptor()
+ kpi_descriptor_object = kpi_manager_client.GetKpiDescriptor(kpi_id)
+ # TODO: why kpi_descriptor_object recevies a KpiDescriptor type object not Empty type object???
+ if kpi_descriptor_object.kpi_id.kpi_id.uuid == kpi_id.kpi_id.uuid:
+ LOGGER.info("Extracted KpiDescriptor: {:}".format(kpi_descriptor_object))
+ print("Extracted KpiDescriptor: {:}".format(kpi_descriptor_object))
+ return KpiSampleType.Name(kpi_descriptor_object.kpi_sample_type) # extract and return the name of KpiSampleType
+ else:
+ LOGGER.info("No KPI Descriptor found in DB for Kpi ID: {:}".format(kpi_id))
+ print("No KPI Descriptor found in DB for Kpi ID: {:}".format(kpi_id))
+ except Exception as e:
+ LOGGER.info("Unable to get KpiDescriptor. Error: {:}".format(e))
+ print ("Unable to get KpiDescriptor. Error: {:}".format(e))
+
+ def ConverValueToKpiValueType(self, value):
# Check if the value is an integer (int64)
try:
- int64_value = int(value)
- return KpiValueType(int64Val=int64_value)
+ int_value = int(value)
+ return KpiValueType(int64Val=int_value)
except ValueError:
pass
# Check if the value is a float
@@ -112,7 +144,6 @@ class KpiValueApiServiceServicerImpl(KpiValueAPIServiceServicer):
# If none of the above, treat it as a string
return KpiValueType(stringVal=value)
-
def delivery_callback(self, err, msg):
if err: LOGGER.debug('Message delivery failed: {:}'.format(err))
else: LOGGER.debug('Message delivered to topic {:}'.format(msg.topic()))
diff --git a/src/kpi_value_writer/service/MetricWriterToPrometheus.py b/src/kpi_value_writer/service/MetricWriterToPrometheus.py
index b681164786bd310d457998bae55b836522888b94..40bffa06ef162abdc55e2d4171dfe287ce8febb7 100644
--- a/src/kpi_value_writer/service/MetricWriterToPrometheus.py
+++ b/src/kpi_value_writer/service/MetricWriterToPrometheus.py
@@ -93,4 +93,4 @@ class MetricWriterToPrometheus:
print("Metric {:} is already registered. Skipping.".format(metric_name))
else:
LOGGER.error("Error while pushing metric: {}".format(e))
- raise
\ No newline at end of file
+ raise