SIENTIAPDE-1199

Update tests in Gates and OpcRepository to enhance logging and include metadata - Removed unnecessary debug assertion in the Gates activity test for format prediction. - Updated the test for last timestamp with no data to include a metadata dictionary. - Modified OpcRepository tests to utilize custom_error logging with metadata for improved error context.
Merge branch 'main' into SIENTIAPDE-1199-revisar-e-testar-observabilidade
2025-08-21 08:56:22 -03:00 · 2025-08-21 08:51:41 -03:00 · 2025-08-21 08:09:20 -03:00 · 2025-08-20 12:50:07 -03:00 · 2025-08-20 11:35:42 -03:00 · 2025-08-20 10:51:38 -03:00
21 changed files with 682 additions and 131 deletions
--- a/laborious/activities/activities.py
+++ b/laborious/activities/activities.py
@@ -3,7 +3,7 @@ from temporalio import activity, workflow
 with workflow.unsafe.imports_passed_through():
    from sientia_do.temporal.activities.postgres import Postgres
    from sientia_do.notifications.handlers import CoreNotificationHandler as NotificationHandler
-    from sientia_do.temporal.utils.logger import Logger
+    from sientia_do.observability.logger import Logger
    from laborious.activities.mlflow import MLFlow
    from laborious.activities.gates import Gates
    from laborious.activities.opc import OPC
--- a/laborious/activities/gates.py
+++ b/laborious/activities/gates.py
@@ -6,7 +6,7 @@ with workflow.unsafe.imports_passed_through():
    from sientia_do.notifications.handlers import CoreNotificationHandler as NotificationHandler
    from sientia_do.notifications.models import NotificationLevel
    from sientia_do.temporal.activities.base import BaseActivity
-    from sientia_do.temporal.utils.logger import Logger
+    from sientia_do.observability.logger import Logger
    from laborious.utils.filters.mlflow_filters import nan_values_filter, api_error_filter
    from typing import Any
    from laborious.utils.filters.conditional_filters import (
@@ -15,6 +15,7 @@ with workflow.unsafe.imports_passed_through():
    )
    from pandas import DataFrame
    from datetime import datetime
+    from laborious import metrics

 input_filter_functions = {
    'SPECIFIC_VARIABLES_NULL_VALUES': filter_specific_variables_null_values,
@@ -47,7 +48,8 @@ mlflow_content_filter_functions = {

 class Gates(BaseActivity):
    def __init__(self, logger: Logger, notification_handler: NotificationHandler):
-        BaseActivity.__init__(self, logger, notification_handler)
+        BaseActivity.__init__(
+            self, logger, notification_handler, set_error_counter=True)

    @activity.defn(name="input_gate")
    async def input_gate(self, input_data: dict[str, Any]) -> tuple[str | None, int, str]:
@@ -66,7 +68,7 @@ class Gates(BaseActivity):
        """
        metadata = input_data['metadata']

-        self.debug("Performing input gate...", metadata)
+        self.info("Performing input gate...", metadata)

        self.debug(f"Input data: {input_data}", metadata)

@@ -101,11 +103,11 @@ class Gates(BaseActivity):

        for path_flag in path_priority:
            if path_flag in filter_output:
-                self.debug(f"Input gate result: {path_flag}", metadata)
+                self.info(f"Input gate result: {path_flag}", metadata)
                return path_flag, input_filter_functions['path_confidence'][path_flag], \
                    "Input data with bad quality"

-        self.debug("Nothing was filtered by the input gate", metadata)
+        self.info("Nothing was filtered by the input gate", metadata)
        return None, 0, ""

    @activity.defn(name="mlflow_response_gate")
@@ -126,7 +128,7 @@ class Gates(BaseActivity):
        """

        metadata = input_data['metadata']
-        self.debug("Performing mlflow response gate...", metadata)
+        self.info("Performing mlflow response gate...", metadata)

        filters = input_data['filters']
        data = input_data['data']
@@ -151,7 +153,7 @@ class Gates(BaseActivity):
                        notification_id=f"{gate_type.upper()}_GATE_RESPONSE_FILTER__{fil}",
                        message=data['content']['message'],
                        block="mlflow_gate",
-                        level=NotificationLevel.WARNING,
+                        level=NotificationLevel.ERROR,
                        attachment_content=data['content']['traceback']
                    )
            except Exception as e:
@@ -167,12 +169,12 @@ class Gates(BaseActivity):

        for path_flag in path_priority:
            if path_flag in filter_output:
-                self.debug(
+                self.info(
                    f"Mlflow response gate result: {path_flag}", metadata)
                return path_flag, mlflow_response_filter_functions['path_confidence'][path_flag], \
                    ", ".join(comments)

-        self.debug("Nothing was filtered by the mlflow response gate", metadata)
+        self.info("Nothing was filtered by the mlflow response gate", metadata)
        return None, 0, ""

    @activity.defn(name="mlflow_content_gate")
@@ -193,7 +195,7 @@ class Gates(BaseActivity):
        """

        metadata = input_data['metadata']
-        self.debug("Performing mlflow content gate...", metadata)
+        self.info("Performing mlflow content gate...", metadata)

        filters = input_data['filters']
        data = DataFrame(input_data['data'])
@@ -232,12 +234,12 @@ class Gates(BaseActivity):

        for path_flag in path_priority:
            if path_flag in filter_output:
-                self.debug(
+                self.info(
                    f"Mlflow content gate result: {path_flag}", metadata)
                return path_flag, mlflow_content_filter_functions['path_confidence'][path_flag], \
                    "Transformed data not passed the content filter"

-        self.debug("Nothing was filtered by the mlflow content gate", metadata)
+        self.info("Nothing was filtered by the mlflow content gate", metadata)
        return None, 0, ""

    @activity.defn(name="format_prediction")
@@ -254,7 +256,7 @@ class Gates(BaseActivity):
            dict: The formatted data.
        """
        metadata = input_data['metadata']
-        self.debug("Formatting prediction...", metadata)
+        self.info("Formatting prediction...", metadata)

        data = DataFrame(input_data['data'])
        data['timestamp'] = input_data['timestamp']
@@ -264,6 +266,8 @@ class Gates(BaseActivity):
        data['comments'] = ""
        data = data.sort_values(by='timestamp')

+        self.info(f"Prediction formatted: {data.size} rows", metadata)
+
        return data.to_dict()

    @activity.defn(name="format_default_prediction")
@@ -285,7 +289,7 @@ class Gates(BaseActivity):
        metadata = input_data['metadata']
        self.debug("Formatting default prediction...", metadata)

-        return DataFrame({
+        data = DataFrame({
            'prediction': [0],
            'response_time': [0],
            'timestamp': [input_data['timestamp']],
@@ -293,7 +297,10 @@ class Gates(BaseActivity):
            'prediction_confidence': [input_data['prediction_confidence']],
            'prediction_status': ['Bad'],
            'comments': [input_data['comment']]
-        }).to_dict()
+        })
+
+        self.info(f"Default prediction formatted: {data.size} rows", metadata)
+        return data.to_dict()

    @activity.defn(name="get_last_timestamp")
    async def get_last_timestamp(self, input_data: dict[str, Any]) -> str:
@@ -305,7 +312,53 @@ class Gates(BaseActivity):
        Returns:
            str: The last timestamp of the data.
        """
+        metadata = input_data['metadata']
+
+        self.info("Getting last timestamp...", metadata)
+
        data = DataFrame(input_data['data'])
+
        if data.empty:
            return datetime.now().strftime('%Y-%m-%d %H:%M:%S')
+
+        self.info(
+            f"Last timestamp: {max(data['timestamp'].values.tolist())}", metadata)
+
        return max(data['timestamp'].values.tolist())
+
+    @activity.defn(name="write_metrics")
+    async def write_metrics(self, input_data: dict[str, Any]):
+        """
+        Write metrics to the database.
+        input_data:
+            metadata: dict[str, Any]
+            prediction: dict[str, Any]
+        """
+        metadata = input_data['metadata']
+        prediction = DataFrame(input_data['prediction'])
+        prediction_confidence = prediction['prediction_confidence'].values[0]
+        response_time = prediction['response_time'].values[0]
+
+        self.info(
+            f"Writing metrics for model {metadata['model_name']}", metadata)
+
+        metrics.PREDICTIONS_WRITTEN_COUNT.labels(
+            pod_id=self.pod_id,
+            model_name=metadata['model_name'],
+            pipeline_name=metadata['workflow_name']
+        ).inc()
+
+        metrics.PREDICTION_CONFIDENCE_MONITOR.labels(
+            pod_id=self.pod_id,
+            model_name=metadata['model_name'],
+            pipeline_name=metadata['workflow_name']
+        ).set(prediction_confidence)
+
+        metrics.PREDICTION_RESPONSE_TIME_MONITOR.labels(
+            pod_id=self.pod_id,
+            model_name=metadata['model_name'],
+            pipeline_name=metadata['workflow_name']
+        ).observe(response_time)
+
+        self.info(
+            f"Metrics written for model {metadata['model_name']}", metadata)
--- a/laborious/activities/mlflow.py
+++ b/laborious/activities/mlflow.py
@@ -1,3 +1,4 @@
+import json
 from temporalio import activity, workflow


@@ -5,7 +6,7 @@ with workflow.unsafe.imports_passed_through():
    from sientia_do.temporal.activities.base import BaseActivity
    from sientia_do.notifications.handlers import CoreNotificationHandler as NotificationHandler
    from sientia_do.notifications.models import NotificationLevel
-    from sientia_do.temporal.utils.logger import Logger
+    from sientia_do.observability.logger import Logger
    from laborious.utils.repository.model_repository import MLFlowRepository
    from typing import Any
    import numpy as np
@@ -16,14 +17,15 @@ with workflow.unsafe.imports_passed_through():
 class MLFlow(BaseActivity):
    def __init__(self, mlflow_host: str, mlflow_port: int, mlflow_username: str,
                 mlflow_password: str, logger: Logger, notification_handler: NotificationHandler):
-        BaseActivity.__init__(self, logger, notification_handler)
+        BaseActivity.__init__(
+            self, logger, notification_handler, set_error_counter=True)
        self.mlflow_host = mlflow_host
        self.mlflow_port = mlflow_port
        self.mlflow_username = mlflow_username
        self.mlflow_password = mlflow_password

        self.model_monitoring_repository = MLFlowRepository(
-            f"{mlflow_host}:{mlflow_port}", mlflow_username, mlflow_password
+            f"{mlflow_host}:{mlflow_port}", mlflow_username, mlflow_password, logger.base_logger
        )

    @activity.defn(name="request_transform")
@@ -39,7 +41,7 @@ class MLFlow(BaseActivity):
            dict[str, Any]: The transformed data.
        """
        metadata = input_data['metadata']
-        self.debug('Transforming data...', metadata)
+        self.info('Transforming data...', metadata)
        data = DataFrame(input_data['data'])
        model_name = input_data['model_name']
        model_retention = input_data['model_retention']
@@ -65,8 +67,10 @@ class MLFlow(BaseActivity):
        response_data = self.model_monitoring_repository.transform(
            model_name, data, model_retention)

-        self.debug("Response data:", metadata)
-        self.debug(response_data, metadata)
+        self.debug("Transform response data:", metadata)
+        self.debug(json.dumps(response_data, indent=4), metadata)
+
+        self.info("Data transformed successfully", metadata)

        return response_data

@@ -83,7 +87,7 @@ class MLFlow(BaseActivity):
            dict[str, Any]: The predicted data.
        """
        metadata = input_data['metadata']
-        self.debug('Predicting data...', metadata)
+        self.info('Predicting data...', metadata)
        data = DataFrame(input_data['data'])
        model_name = input_data['model_name']
        model_retention = input_data['model_retention']
@@ -95,7 +99,10 @@ class MLFlow(BaseActivity):
        response_data = self.model_monitoring_repository.predict(
            model_name, data, model_retention)

-        self.debug(response_data, metadata)
+        self.debug("Prediction response data:", metadata)
+        self.debug(json.dumps(response_data, indent=4), metadata)
+
+        self.info("Prediction completed successfully", metadata)

        return response_data

--- a/laborious/activities/opc.py
+++ b/laborious/activities/opc.py
@@ -5,7 +5,7 @@ with workflow.unsafe.imports_passed_through():
    from sientia_do.notifications.handlers import CoreNotificationHandler as NotificationHandler
    from sientia_do.notifications.models import NotificationLevel
    from sientia_do.temporal.activities.base import BaseActivity
-    from sientia_do.temporal.utils.logger import Logger
+    from sientia_do.observability.logger import Logger
    from laborious.utils.repository.opc_repository import OpcRepository
    from typing import Any
    import traceback
@@ -22,6 +22,9 @@ class OPC(BaseActivity):
        self.notification_handler = notification_handler
        self.opc_servers = opc_servers

+        BaseActivity.__init__(
+            self, logger, notification_handler, set_error_counter=True)
+
        self.opc_repository: dict[str, OpcRepository] = {}
        for id, server in opc_servers.items():
            self.opc_repository[id] = OpcRepository(
@@ -34,6 +37,7 @@ class OPC(BaseActivity):
                server_cert_path=server['server_cert_path'],
                notification_handler=self.notification_handler,
                reconnection_interval=server['reconnection_interval'],
+                pod_id=self.pod_id
            )
            is_connected, error_data = self.opc_repository[id].connect()
            if not is_connected:
@@ -51,7 +55,6 @@ class OPC(BaseActivity):
                    attachment_content=error_data.get(
                        'attachment_content', None)
                )
-        BaseActivity.__init__(self, logger, notification_handler)

    def write_data(self, server_id: str, tag: str, data: Any,
                   data_type: str, tag_type: str, metadata: dict[str, Any]) -> bool:
@@ -96,6 +99,59 @@ class OPC(BaseActivity):
            )
            raise e

+    def validate_server(self, server_id: str, metadata: dict[str, Any]) -> bool:
+        if self.opc_repository.get(server_id) is None:
+            message = f"OPC server {server_id} not found to perform write operation."
+            self.send_notification(
+                metadata=metadata,
+                notification_id="OPC_SERVER_NOT_FOUND",
+                message=message,
+                block="write_opc_data",
+                level=NotificationLevel.ERROR,
+                attachment_content=f"OPC servers: {list(self.opc_repository.keys())}"
+            )
+            return False
+        return True
+
+    def manage_output_tags(
+            self, server_id: str, config: dict[str, Any], data: DataFrame,
+            metadata: dict[str, Any], success: bool) -> tuple[bool, int]:
+
+        count = 0
+        if 'prediction_tags' in config:
+            for tag, tag_config in config['prediction_tags'].items():
+                local_success = self.write_data(
+                    server_id=server_id,
+                    tag=tag,
+                    data=data.head(1)['prediction'].values[0],
+                    data_type=tag_config['data_type'],
+                    tag_type='prediction',
+                    metadata=metadata
+                )
+                if local_success:
+                    self.info(
+                        f"Prediction data written to OPC server {server_id} for tag {tag}.", metadata)
+                    count += 1
+                success = success and local_success
+
+        if 'confidence_tags' in config:
+            for tag, tag_config in config['confidence_tags'].items():
+                local_success = self.write_data(
+                    server_id=server_id,
+                    tag=tag,
+                    data=data.head(1)['prediction_confidence'].values[0],
+                    data_type=tag_config['data_type'],
+                    tag_type='confidence',
+                    metadata=metadata
+                )
+                if local_success:
+                    self.info(
+                        f"Confidence data written to OPC server {server_id} for tag {tag}.", metadata)
+                    count += 1
+                success = success and local_success
+
+        return success, count
+
    @activity.defn(name='write_opc_data')
    async def write_opc_data(self, input_data: dict[str, Any]) -> dict[Any, Any]:
        """
@@ -116,47 +172,28 @@ class OPC(BaseActivity):

        """
        metadata = input_data['metadata']
-        self.debug("Writing data to OPC servers...", metadata)
+        self.info("Writing data to OPC servers...", metadata)
        data = DataFrame(input_data['data'])
        opc_output_config = input_data['opc_output_config']
-        self.debug(data, metadata)
+        self.info(f"Data to write: {data.size} rows", metadata)

        success = True

+        success_count = 0
+
        for server_id, config in opc_output_config.items():
-            if self.opc_repository.get(server_id) is None:
-                message = f"OPC server {server_id} not found to perform write operation."
-                self.send_notification(
-                    metadata=metadata,
-                    notification_id="OPC_SERVER_NOT_FOUND",
-                    message=message,
-                    block="write_opc_data",
-                    level=NotificationLevel.ERROR,
-                    attachment_content=f"OPC servers: {list(self.opc_repository.keys())}"
-                )
+
+            if not self.validate_server(server_id, metadata):
                success = False
+                continue

-            if 'prediction_tags' in config:
-                for tag, tag_config in config['prediction_tags'].items():
-                    success = success and self.write_data(
-                        server_id=server_id,
-                        tag=tag,
-                        data=data.head(1)['prediction'].values[0],
-                        data_type=tag_config['data_type'],
-                        tag_type='prediction',
-                        metadata=metadata
-                    )
+            local_success, local_count = self.manage_output_tags(
+                server_id, config, data, metadata, success)
+            success = success and local_success
+            success_count += local_count

-            if 'confidence_tags' in config:
-                for tag, tag_config in config['confidence_tags'].items():
-                    self.write_data(
-                        server_id=server_id,
-                        tag=tag,
-                        data=data.head(1)['prediction_confidence'].values[0],
-                        data_type=tag_config['data_type'],
-                        tag_type='confidence',
-                        metadata=metadata
-                    )
+            self.info(
+                f"Data written to OPC server {server_id}: {local_count} of {len(config['prediction_tags'])} prediction tags and {len(config['confidence_tags'])} confidence tags", metadata)

        return self.process_confidence(data, success, metadata)

--- a/laborious/metrics.py
+++ b/laborious/metrics.py
@@ -0,0 +1,41 @@
+from prometheus_client import Gauge, Counter, Histogram
+
+APP_UP = Gauge(
+    "app_up",
+    "Indicates if the application is running (1) or shutting down (0)",
+    ["pod_id"],
+)
+
+CORE_LABELS = ["pod_id", "model_name", "pipeline_name"]
+
+PREDICTIONS_WRITTEN_COUNT = Counter(
+    "laborious_predictions_written_count",
+    "Number of predictions written to the database table predictions",
+    CORE_LABELS,
+)
+
+PREDICTION_CONFIDENCE_MONITOR = Gauge(
+    "laborious_prediction_confidence_monitor",
+    "Current confidence of each prediction",
+    CORE_LABELS,
+)
+
+PREDICTION_RESPONSE_TIME_MONITOR = Histogram(
+    "laborious_prediction_response_time_monitor",
+    "Current response time of each prediction",
+    CORE_LABELS,
+    buckets=[0.01, 0.05, 0.1, 0.2, 0.5, 1.0, 2.0, 5.0, 10.0]
+)
+
+PREDICTION_OPC_WRITING_COUNT = Counter(
+    "laborious_prediction_opc_writing_count",
+    "Number of predictions written to the OPC server",
+    [*CORE_LABELS, "opc_server_id"],
+)
+
+PREDICTION_OPC_WRITING_RESPONSE_TIME_MONITOR = Histogram(
+    "laborious_prediction_opc_writing_response_time_monitor",
+    "Current response time of each prediction written to the OPC server",
+    [*CORE_LABELS, "opc_server_id"],
+    buckets=[0.01, 0.05, 0.1, 0.2, 0.5, 1.0, 2.0, 5.0, 10.0]
+)
--- a/laborious/utils/repository/model_repository.py
+++ b/laborious/utils/repository/model_repository.py
@@ -19,10 +19,11 @@ from sientia.ModelServing import ModelServing


 class MLFlowRepository():
-    def __init__(self, host, username, password):
+    def __init__(self, host, username, password, logger):

        self.model_serving = ModelServing(tracking_uri=host,
-                                          username=username, password=password)
+                                          username=username, password=password,
+                                          logger=logger)

    def transform(self, model_name: str, data: pd.DataFrame, model_retention: int):
        """
@@ -68,7 +69,7 @@ class MLFlowRepository():
        try:
            start_time = datetime.now()
            data = self.model_serving.get_cached_predict(
-                model_name, data, model_retention)[-1:]
+                model_name, data, model_retention)

            end_time = datetime.now()
            data = pd.DataFrame(data, columns=['prediction'])
--- a/laborious/utils/repository/opc_repository.py
+++ b/laborious/utils/repository/opc_repository.py
@@ -1,4 +1,5 @@
 import traceback
+import time
 from datetime import datetime
 from pathlib import Path
 from typing import Any
@@ -8,7 +9,8 @@ from asyncua.ua import DataValue, Variant, VariantType, DateTime
 from regex import F
 from sientia_do.notifications.handlers import CoreNotificationHandler as NotificationHandler
 from sientia_do.notifications.models import NotificationLevel
-from sientia_do.temporal.utils.logger import Logger
+from sientia_do.observability.logger import Logger
+from laborious import metrics

 data_type_map = {
    'float': {
@@ -38,7 +40,7 @@ class OpcRepository():
    def __init__(self, id: str, url: str, logger: Logger,
                 notification_handler: NotificationHandler,
                 reconnection_interval: int = 60, server_uri: str = None, cert_path: str = None,
-                 private_key_path: str = None, server_cert_path: str = None):
+                 private_key_path: str = None, server_cert_path: str = None, pod_id: str = None):
        self.url = url
        self.id = id
        self.server_uri = server_uri
@@ -51,6 +53,14 @@ class OpcRepository():
        self.last_reconnection_time = None
        self.notification_handler = notification_handler
        self.client = None
+        self.pod_id = pod_id
+
+        self.metadata = {
+            'model_name': '-',
+            'model_id': '-',
+            'workflow_name': 'opc_repository',
+            'schedule_name': '-'
+        }

    def set_security(self):
        """
@@ -81,7 +91,7 @@ class OpcRepository():
            self.server_cert_path) if self.server_cert_path else None

        self.client.application_uri = self.server_uri
-        self.logger.info('Setting security...')
+        self.logger.custom_info('Setting security...', self.metadata)
        self.client.set_security(
            SecurityPolicyBasic256,
            certificate=str(cert),
@@ -104,7 +114,8 @@ class OpcRepository():
        self.client = Client(self.url)
        if self.cert_path:
            self.set_security()
-        self.logger.info(f'Starting connection to OPC server {self.id}...')
+        self.logger.custom_info(
+            f'Starting connection to OPC server {self.id}...', self.metadata)
        return self.try_connect()

    def try_connect(self) -> tuple[bool, dict[str, Any]]:
@@ -121,7 +132,7 @@ class OpcRepository():
            return True, {}
        except Exception as e:
            trace = traceback.format_exc()
-            self.logger.error(trace)
+            self.logger.custom_error(trace, self.metadata)

            return False, {
                "notification_id": f"OPC_CONNECTION_ERROR_{self.id}",
@@ -139,9 +150,11 @@ class OpcRepository():
            return
        try:
            self.client.disconnect()
-            self.logger.info('Disconnected from OPC server')
+            self.logger.custom_info(
+                'Disconnected from OPC server', self.metadata)
        except Exception as e:
-            self.logger.error(f"Failed to disconnect from OPC server: {e}")
+            self.logger.custom_error(
+                f"Failed to disconnect from OPC server: {e}", self.metadata)
        self.client = None

    def __del__(self):
@@ -151,7 +164,8 @@ class OpcRepository():
        try:
            self.disconnect()
        except Exception as e:
-            self.logger.error(f"Error in destructor: {e}")
+            self.logger.custom_error(
+                f"Error in destructor: {e}", self.metadata)

    def validate_connection(self) -> tuple[bool, dict[str, Any]]:
        """
@@ -168,32 +182,39 @@ class OpcRepository():
            return self.connect()

        if self.error_count > 5:
-            self.logger.warning(
-                f"OPC server {self.id} will be disconnected due to multiple errors")
+            self.logger.custom_warning(
+                f"OPC server {self.id} will be disconnected due to multiple errors", self.metadata)
            try:
                self.disconnect()
            except Exception as e:
                trace = traceback.format_exc()
-                self.logger.error(f"Failed to disconnect from OPC server: {e}")
-                self.logger.error(trace)
-            self.logger.info(
-                f"Attempting to reconnect to OPC server {self.id}...")
+                self.logger.custom_error(
+                    f"Failed to disconnect from OPC server: {e}", self.metadata)
+                self.logger.custom_error(trace, self.metadata)
+            self.logger.custom_info(
+                f"Attempting to reconnect to OPC server {self.id}...", self.metadata)
            return self.connect()

        if hasattr(self.client, 'aio_obj') and self.client.aio_obj.uaclient.protocol is None or \
                (hasattr(self.client.aio_obj.uaclient, 'protocol') and
                 self.client.aio_obj.uaclient.protocol.state == "closed"):

-            self.logger.error(
-                f"OPC server {self.id} is not connected")
+            self.logger.custom_error(
+                f"OPC server {self.id} is not connected", self.metadata)
+
            if self.last_reconnection_time is None or (datetime.now() - self.last_reconnection_time).total_seconds(
            ) > self.reconnection_interval:
                self.disconnect()
-                self.logger.error(
-                    f"Trying to reconnect to OPC server {self.id}...")
+                self.logger.custom_info(
+                    f"Trying to reconnect to OPC server {self.id}...", self.metadata)
                return self.connect()

-            return False, {}
+            return False, {
+                "notification_id": f"OPC_CONNECTION_AWAITING_RECONNECTION_WINDOW_{self.id}",
+                "message": f"OPC server {self.id} is not connected, waiting for next reconnection window...",
+                "block": "opc_repository",
+                "level": NotificationLevel.WARNING
+            }

        return True, {}

@@ -215,6 +236,8 @@ class OpcRepository():
        if not is_connected:
            return False, error

+        start_time = time.time()
+
        try:
            node = self.client.get_node(node)
        except Exception as e:
@@ -239,7 +262,7 @@ class OpcRepository():

        data = data_type_map[data_type]['converter'](value)
        logger.custom_info(
-            f'Writing {data} - {type(data)} to {node}', metadata.get('schedule_name', 'N/A'))
+            f'Writing {data} - {type(data)} to {node}', metadata)
        now = datetime.now()
        ua_data = DataValue(
            Variant(data, data_type_map[data_type]['opc_type']),
@@ -256,9 +279,26 @@ class OpcRepository():

        try:
            node.write_value(ua_data)
+
+            metrics.PREDICTION_OPC_WRITING_COUNT.labels(
+                pod_id=self.pod_id,
+                model_name=metadata['model_name'],
+                pipeline_name=metadata['workflow_name'],
+                opc_server_id=self.id
+            ).inc()
+
+            end_time = time.time()
+            response_time = end_time - start_time
+            metrics.PREDICTION_OPC_WRITING_RESPONSE_TIME_MONITOR.labels(
+                pod_id=self.pod_id,
+                model_name=metadata['model_name'],
+                pipeline_name=metadata['workflow_name'],
+                opc_server_id=self.id
+            ).observe(response_time)
+
        except Exception as e:
            trace = traceback.format_exc()
-            logger.custom_error(trace, metadata.get('schedule_name', 'N/A'))
+            logger.custom_error(trace, metadata)
            self.error_count += 1
            return False, {
                "notification_id": f"OPC_WRITE_DATA_ERROR_{self.id}",
--- a/laborious/worker/worker.py
+++ b/laborious/worker/worker.py
@@ -1,6 +1,6 @@
 from temporalio import workflow, client
-from temporalio.worker import Worker
-
+from temporalio.worker import Worker, PollerBehaviorAutoscaling
+from temporalio.runtime import Runtime, TelemetryConfig, PrometheusConfig

 with workflow.unsafe.imports_passed_through():
    import os
@@ -19,16 +19,32 @@ with workflow.unsafe.imports_passed_through():
        build_mongodb_config
    )
    from sientia_do.notifications.handlers import CoreNotificationHandler as NotificationHandler
-    from sientia_do.temporal.utils.logger import get_logger
+    from sientia_do.observability.logger import get_logger
+    from laborious import metrics
+    from prometheus_client import start_http_server
+
+POD_ID = os.getenv('POD_ID')
+SDK_METRICS_PORT = int(os.getenv('HTTP_SDK_METRICS_PORT', "9091"))


 async def main():
    host = os.getenv('TEMPORAL_HOST', 'localhost:7233')
    logger = get_logger(__name__)

-    logger.info('Starting Worker...')
+    metadata = {
+        'pod_id': POD_ID,
+        'model_name': '-',
+        'model_id': '-',
+        'workflow_name': '-',
+        'schedule_name': '-',
+    }

-    logger.info('Starting Notification Handler...')
+    logger.custom_info(f'Starting Worker with POD_ID: {POD_ID}', metadata)
+
+    logger.custom_info("Starting prometheus client...", metadata)
+    start_prometheus_server()
+
+    logger.custom_info('Starting Notification Handler...', metadata)

    mongo_config = build_mongodb_config()
    notification_handler = NotificationHandler(
@@ -38,7 +54,7 @@ async def main():
        project_name=os.getenv('PROJECT_NAME', 'laborious')
    )

-    logger.info('Starting Activities...')
+    logger.custom_info('Starting Activities...', metadata)

    activities = Activities(
        postgres_config=build_postgres_config(),
@@ -48,14 +64,25 @@ async def main():
        notification_handler=notification_handler
    )

-    logger.info('Starting Temporal Client...')
+    logger.custom_info(
+        f'Starting SDK Metrics Server on port {SDK_METRICS_PORT}...', metadata)
+
+    new_runtime = Runtime(
+        telemetry=TelemetryConfig(
+            metrics=PrometheusConfig(
+                bind_address=f"0.0.0.0:{SDK_METRICS_PORT}")
+        )
+    )
+
+    logger.custom_info('Starting Temporal Client...', metadata)

    temporal_client = await client.Client.connect(
        target_host=host,
-        namespace=os.getenv('TEMPORAL_NAMESPACE', 'laborious')
+        namespace=os.getenv('TEMPORAL_NAMESPACE', 'laborious'),
+        runtime=new_runtime
    )

-    logger.info('Starting Workers...')
+    logger.custom_info('Starting Workers...', metadata)

    workers = [
        Worker(
@@ -68,11 +95,12 @@ async def main():
                activities.update_production_model,
                activities.export_data_to_postgres
            ],
-            max_concurrent_workflow_tasks=100,
-            max_concurrent_activities=100,
-            max_concurrent_local_activities=100,
-            max_concurrent_workflow_task_polls=100,
-            max_cached_workflows=50,
+            max_concurrent_workflow_tasks=50,
+            max_concurrent_activities=50,
+            max_concurrent_local_activities=50,
+            max_cached_workflows=200,
+            workflow_task_poller_behavior=PollerBehaviorAutoscaling(),
+            activity_task_poller_behavior=PollerBehaviorAutoscaling()
        ),
        Worker(
            temporal_client,
@@ -95,13 +123,15 @@ async def main():
                # Postgres
                activities.load_custom_query,
                activities.repeat_last_prediction,
-                activities.export_data_to_postgres
+                activities.export_data_to_postgres,
+                activities.write_metrics
            ],
-            max_concurrent_workflow_tasks=100,
-            max_concurrent_activities=100,
-            max_concurrent_local_activities=100,
-            max_concurrent_workflow_task_polls=100,
-            max_cached_workflows=50,
+            max_concurrent_workflow_tasks=50,
+            max_concurrent_activities=50,
+            max_concurrent_local_activities=50,
+            max_cached_workflows=200,
+            workflow_task_poller_behavior=PollerBehaviorAutoscaling(),
+            activity_task_poller_behavior=PollerBehaviorAutoscaling()
        )
    ]

@@ -109,21 +139,34 @@ async def main():
    for w in workers:
        handlers.append(w.run())

-    logger.info('Workers started successfully')
+    logger.custom_info('Workers started successfully', metadata)

    try:
        # This will run the workers and wait for them to complete.
        # If an exception occurs in any of the worker handlers, it will be propagated here.
        await asyncio.gather(*handlers)
    except BaseException as e:  # NOSONAR
-        logger.error(f"An unhandled exception occurred: {e}")
+        logger.custom_error(f"An unhandled exception occurred: {e}", metadata)
    finally:
        if notification_handler:
            notification_handler.shutdown()
        if activities:
            activities.shutdown()
        # Exit with a non-zero status code to indicate failure to Kubernetes
+        metrics.APP_UP.labels(pod_id=POD_ID).set(0)  # Mark app as DOWN
        sys.exit(1)

+
+def start_prometheus_server():
+    try:
+        port = int(os.getenv("HTTP_METRICS_PORT", 9090))
+        start_http_server(port)
+        print(f"Prometheus server started on port {port}.")
+        metrics.APP_UP.labels(pod_id=POD_ID).set(1)  # Mark app as UP
+    except Exception as e:
+        print(f"Failed to start Prometheus server: {e}")
+        os._exit(1)
+
+
 if __name__ == '__main__':
    asyncio.run(main())
--- a/laborious/workflows/minimal_retrain.py
+++ b/laborious/workflows/minimal_retrain.py
@@ -3,7 +3,7 @@ from temporalio import workflow
 with workflow.unsafe.imports_passed_through():
    from laborious.activities.activities import Activities
    from typing import Any
-    from sientia_do.temporal.utils.policies import retry_policy
+    from sientia_do.temporal.policies import retry_policy
    from datetime import timedelta


--- a/laborious/workflows/predictions_batch.py
+++ b/laborious/workflows/predictions_batch.py
@@ -3,7 +3,7 @@ from temporalio import workflow
 with workflow.unsafe.imports_passed_through():
    from laborious.activities.activities import Activities
    from typing import Any
-    from sientia_do.temporal.utils.policies import retry_policy
+    from sientia_do.temporal.policies import retry_policy
    from datetime import timedelta


--- a/laborious/workflows/sub_workflows/format_and_export_prediction.py
+++ b/laborious/workflows/sub_workflows/format_and_export_prediction.py
@@ -4,7 +4,7 @@ with workflow.unsafe.imports_passed_through():
    from laborious.activities.activities import Activities
    from typing import Any
    from datetime import timedelta
-    from sientia_do.temporal.utils.policies import retry_policy
+    from sientia_do.temporal.policies import retry_policy


@workflow.defn(name="format_and_export_prediction")
@@ -95,3 +95,13 @@ class FormatAndExportPrediction():
            retry_policy=retry_policy,
            start_to_close_timeout=timedelta(seconds=60)
        )
+
+        await workflow.execute_activity_method(
+            Activities.write_metrics,
+            {
+                **metadata,
+                'prediction': prediction
+            },
+            retry_policy=retry_policy,
+            start_to_close_timeout=timedelta(seconds=60)
+        )
--- a/laborious/workflows/sub_workflows/prediction_process.py
+++ b/laborious/workflows/sub_workflows/prediction_process.py
@@ -3,7 +3,7 @@ from temporalio import workflow
 with workflow.unsafe.imports_passed_through():
    from laborious.activities.activities import Activities
    from typing import Any
-    from sientia_do.temporal.utils.policies import retry_policy
+    from sientia_do.temporal.policies import retry_policy
    from datetime import timedelta


--- a/requirements.txt
+++ b/requirements.txt
@@ -3,5 +3,6 @@ psycopg2-binary
 sqlalchemy
 asyncua
 redis
-git+ssh://git@github.com/Aignosi/sientia-dataops-library.git@1.3.5
+git+ssh://git@github.com/Aignosi/sientia-dataops-library.git@1.4.1
 git+ssh://git@github.com/Aignosi/sientia-mlops-library.git@0.38.5
+prometheus-client
--- a/tests.ipynb
+++ b/tests.ipynb
@@ -0,0 +1,218 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b10e5c25",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[ 0.5479121  -0.12224312  0.71719584  0.39473606 -0.8116453   0.9512447\n",
+      "  0.5222794   0.57212861 -0.74377273 -0.09922812 -0.25840395  0.85352998\n",
+      "  0.28773024  0.64552323 -0.1131716  -0.54552256  0.10916957 -0.87236549\n",
+      "  0.65526234  0.2633288   0.51617548 -0.29094806  0.94139605  0.78624224\n",
+      "  0.55676699 -0.61072258 -0.06655799 -0.91239247 -0.69142102  0.36609791\n",
+      "  0.48952431  0.93501946 -0.34834928 -0.25908059 -0.06088838 -0.62105728\n",
+      " -0.74015699 -0.04859015 -0.5461813   0.33962799 -0.12569616  0.66535639\n",
+      "  0.4005302  -0.37526672  0.6645196   0.60952871 -0.22504324 -0.42334379\n",
+      "  0.36499101 -0.72049503 -0.6001836  -0.98527546  0.57384876  0.32970171\n",
+      "  0.41033076  0.56145806 -0.08216845  0.13748239 -0.720406   -0.77093985\n",
+      "  0.33680592 -0.05780759  0.13047221  0.52999771  0.26943664  0.1071588\n",
+      "  0.11841432 -0.3920998  -0.93836433 -0.12656522 -0.57083065 -0.18294271\n",
+      "  0.70680615 -0.53212103 -0.88339452 -0.43723222 -0.41281248  0.32383303\n",
+      "  0.1140643   0.56779642  0.32862708 -0.18722628  0.62804077 -0.66605416\n",
+      " -0.95457585 -0.81990428  0.4447187  -0.07624554 -0.67745644  0.00208955\n",
+      " -0.69537579  0.39264075 -0.10768745 -0.23795755 -0.39697582  0.26056519\n",
+      " -0.27637478 -0.82470016 -0.7639882   0.92379533  0.81716138  0.39941427\n",
+      " -0.46826008  0.93835275  0.55750181  0.43378038 -0.101277   -0.45551688\n",
+      " -0.80721808  0.80520479 -0.08844742 -0.59527327 -0.38808675  0.15843914\n",
+      " -0.64645443  0.71322857  0.51703906  0.43892591 -0.13581392  0.25461768\n",
+      "  0.16819594  0.2996932  -0.83111136 -0.1683852  -0.91677165 -0.01201836\n",
+      " -0.34027758 -0.71095162 -0.79319406  0.17528914 -0.65881406  0.85024024\n",
+      "  0.16212228 -0.30626039  0.18183098 -0.95439226  0.91711843 -0.03539313\n",
+      "  0.56547045 -0.83454    -0.02668334 -0.01858601  0.87565291  0.1434561\n",
+      " -0.0530212  -0.46604867 -0.33686201  0.0413448  -0.12217708 -0.95677584\n",
+      "  0.65258385  0.79232154 -0.71950182  0.10807229 -0.78284852  0.34448019\n",
+      " -0.43753243  0.31884527  0.45398923  0.53729498 -0.78451811  0.83202369\n",
+      " -0.53957202 -0.92517489  0.10970494 -0.25815543  0.65957949  0.61650294\n",
+      " -0.36572221  0.90579879 -0.41816432  0.03011426 -0.48806982  0.87208714\n",
+      " -0.67078436 -0.91017876 -0.12980588  0.98475113  0.78335453  0.49721604\n",
+      "  0.78158498  0.78689328  0.03771672 -0.3681419   0.54402486  0.32332253\n",
+      " -0.25268454 -0.81106666  0.49357922 -0.47507897  0.8736263  -0.51805885\n",
+      " -0.75448414  0.66222534 -0.69343137 -0.64146338  0.19876558  0.74912408\n",
+      " -0.60713067 -0.37935265  0.55480968  0.94365285  0.00148237 -0.71220499\n",
+      " -0.97212742 -0.54068794 -0.73635556  0.35531735 -0.75633499  0.01265986\n",
+      "  0.38852487  0.16223322 -0.6004487   0.60824905  0.43081426  0.47796801\n",
+      " -0.7378845  -0.75249239  0.8551251  -0.20484361 -0.39810262 -0.02283191\n",
+      "  0.32572843  0.91124651 -0.42710755  0.84961686 -0.95028102  0.11039608\n",
+      "  0.26795022 -0.78820519 -0.71932081 -0.16177136  0.93246382  0.19208511\n",
+      "  0.86604644  0.60872183 -0.0652368   0.5695269  -0.96432643 -0.78171201\n",
+      "  0.65885723  0.59363418 -0.53471852  0.06153918  0.21203164  0.73547791\n",
+      "  0.20621431 -0.17485686 -0.25163191 -0.14823583  0.30386205  0.73498126\n",
+      " -0.09220624 -0.50432087 -0.52667527  0.49202856  0.63313753 -0.78944384\n",
+      " -0.86688229  0.18886733 -0.70765351  0.64932838 -0.37933065 -0.71225613\n",
+      "  0.84194094 -0.66893655 -0.43055984 -0.69277321 -0.76901987 -0.95770397\n",
+      " -0.88920918 -0.65071706 -0.89323613  0.18228763  0.36142905 -0.21273909\n",
+      " -0.36401781  0.00905247  0.75000988  0.70226325 -0.91304988 -0.63700318\n",
+      " -0.52651026 -0.50122485  0.1424653  -0.16747515 -0.90149176 -0.25277172\n",
+      "  0.0475059  -0.79665619  0.66691711 -0.89607627  0.84968374 -0.80177372\n",
+      "  0.6871499   0.80530629  0.95914136  0.60405176  0.55895508]\n",
+      "[ 0.28496655  0.55799271 -0.73089558  0.07213607  0.02844574  0.71514429\n",
+      " -0.07440127 -0.22982101  0.27912654 -0.46707336 -0.72046318 -0.04424545\n",
+      " -0.16622126 -0.53486012 -0.26497638 -0.2672151  -0.34500887 -0.24107184\n",
+      "  0.37148669 -0.40624705  0.89771585  0.83269604 -0.03817914 -0.34327759\n",
+      "  0.07086958  0.69712098  0.30517468  0.60878366  0.06544455  0.26583526\n",
+      " -0.42368877  0.46978632 -0.59519081  0.38959626  0.72143814 -0.73579433\n",
+      "  0.22875948 -0.8098085   0.45143126 -0.83101356  0.87187965 -0.72518414\n",
+      "  0.91776049  0.60176835  0.18736401  0.56524821  0.59022968  0.89205413\n",
+      " -0.49323329  0.18015179 -0.8099016   0.2323314  -0.65741739  0.12990122\n",
+      "  0.14486103 -0.06802969  0.04526355  0.52784678  0.59848943 -0.01569357\n",
+      "  0.19918688  0.86247247 -0.76053282 -0.76579287 -0.82458198  0.31572657\n",
+      " -0.1627834   0.54864283  0.34246283 -0.33272448  0.79673309  0.52506429\n",
+      " -0.45893012 -0.27161596 -0.37112004 -0.6847767  -0.70443325  0.87225493\n",
+      " -0.12419193 -0.23336035  0.45937142  0.10598613  0.87227997  0.56060299\n",
+      " -0.04126087 -0.24728105  0.97326309  0.43552047  0.90238932 -0.76304285\n",
+      "  0.70106736  0.27414777 -0.75615664  0.176516    0.37219273 -0.97539463\n",
+      " -0.09136408  0.65079902 -0.40928195 -0.08290384 -0.11537175 -0.39614522\n",
+      "  0.83688379  0.56258807 -0.77882318  0.99406932  0.75840005 -0.43218312\n",
+      "  0.67379316 -0.78716094  0.99820946  0.33136947  0.30025003 -0.81911855\n",
+      "  0.7940668  -0.94200099 -0.51834388 -0.71395625  0.55353588 -0.60359155\n",
+      "  0.82127645  0.31253808 -0.92767458 -0.98914033 -0.89668417  0.21185036\n",
+      "  0.60296362 -0.52289436  0.69881769 -0.88553612  0.60192771  0.85559086\n",
+      "  0.5442168   0.39624157  0.67596044 -0.9196974  -0.59643578 -0.75015264\n",
+      "  0.00906198  0.49037626  0.26002369  0.7022622  -0.68957402  0.46924218\n",
+      " -0.61391702 -0.4584825   0.41980939  0.96040957  0.22308721 -0.89099937\n",
+      "  0.23261794 -0.9152989   0.76829142  0.41915657 -0.65374431 -0.81655799\n",
+      " -0.63293354  0.96005436 -0.08287872  0.5681619   0.27281668  0.1448263\n",
+      " -0.70973949  0.89204891 -0.39731473  0.15603443  0.39955189  0.29846631\n",
+      "  0.88118882 -0.70312202  0.01670548 -0.19193122 -0.05166254 -0.76156495\n",
+      " -0.73181078 -0.44384891 -0.39059079 -0.14419357  0.22197509  0.26925823\n",
+      " -0.17637821 -0.18243378 -0.56474295  0.1766125  -0.36591818 -0.92788033\n",
+      " -0.16319991 -0.05173465 -0.54881426  0.14491587  0.1315438   0.40400436\n",
+      "  0.29589696  0.30486611 -0.3675717   0.57486444  0.09828877 -0.13716361\n",
+      "  0.25202496 -0.27868533  0.02547849  0.47341138  0.77280577  0.84211439\n",
+      "  0.00726585  0.04055023  0.59974082 -0.37109862  0.67476472 -0.01171671\n",
+      " -0.76828655 -0.85588171  0.68398642 -0.88886417 -0.43877713 -0.33173992\n",
+      " -0.65401111 -0.37221326  0.48538513 -0.97063431  0.65434685  0.71309605\n",
+      " -0.25547685 -0.6927742   0.20168082 -0.76065489 -0.27016128  0.91685836\n",
+      "  0.99092895  0.54420978 -0.37807698  0.3753301   0.41081273 -0.22431661\n",
+      "  0.28177727 -0.97854471 -0.58188468  0.05017661 -0.67249739 -0.66818626\n",
+      "  0.67260858  0.97826601  0.11193886  0.67813946  0.98064333 -0.71680822\n",
+      " -0.10350877 -0.21485457 -0.83990143  0.51066035 -0.13244195 -0.06134613\n",
+      " -0.69865405 -0.6381467   0.81420724 -0.91070182 -0.53429543 -0.41588134\n",
+      " -0.01960492  0.17289035 -0.01342005 -0.83176933 -0.51266509  0.68717677\n",
+      "  0.2751774   0.2982981   0.34040651  0.52580604 -0.88378304 -0.26678323\n",
+      "  0.07905487 -0.32308703  0.68895775 -0.03485498  0.53725518  0.70403103\n",
+      "  0.00958297  0.81910449  0.17424788  0.7005486  -0.31881841 -0.00236608\n",
+      "  0.06282208 -0.79004057 -0.20289499  0.83467535  0.26166448 -0.64498684\n",
+      " -0.32228873 -0.61679398 -0.95035374  0.85492092 -0.10358534 -0.38492986\n",
+      "  0.19695438 -0.98537109 -0.44395579  0.40606693  0.26753955]\n",
+      "    Counter   Rollout  CounterPlusRollout           Timestamp\n",
+      "0  0.000000  0.000000            0.000000 2025-01-01 00:00:00\n",
+      "1  0.547912  0.284967            0.832879 2025-01-01 00:00:01\n",
+      "2  0.425669  0.842959            1.268628 2025-01-01 00:00:02\n",
+      "3  1.142865  0.112064            1.254928 2025-01-01 00:00:03\n",
+      "4  1.537601  0.184200            1.721801 2025-01-01 00:00:04\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "\n",
+    "# Set random seed for reproducibility\n",
+    "rng = np.random.default_rng(42)\n",
+    "\n",
+    "# Generate random walks starting at 0\n",
+    "counter = np.zeros(300)\n",
+    "rollout = np.zeros(300)\n",
+    "\n",
+    "# Generate random steps between -1 and 1\n",
+    "counter_steps = rng.uniform(-1, 1, 299)\n",
+    "rollout_steps = rng.uniform(-1, 1, 299)\n",
+    "\n",
+    "print(counter_steps)\n",
+    "print(rollout_steps)\n",
+    "\n",
+    "# Calculate cumulative sum and scale to -100 to 100 range\n",
+    "for i in range(1, 300):\n",
+    "    counter[i] = counter[i-1] + counter_steps[i-1]\n",
+    "    rollout[i] = rollout[i-1] + rollout_steps[i-1]\n",
+    "\n",
+    "# normalize values between -100 and 100, lowest value is -100, highest value is 100\n",
+    "counter = (counter - min(counter)) / (max(counter) - min(counter)) * 200 - 100\n",
+    "rollout = (rollout - min(rollout)) / (max(rollout) - min(rollout)) * 200 - 100\n",
+    "\n",
+    "# Create DataFrame\n",
+    "df = pd.DataFrame({\n",
+    "    'Counter': counter,\n",
+    "    'Rollout': rollout,\n",
+    "    'CounterPlusRollout': counter + rollout\n",
+    "})\n",
+    "\n",
+    "# add a timestamp column\n",
+    "df['Timestamp'] = pd.date_range(start='2025-01-01', periods=300, freq='1s')\n",
+    "\n",
+    "# Save to CSV\n",
+    "df.to_csv('random_walks.csv', index=False)\n",
+    "\n",
+    "# Display first few rows\n",
+    "print(df.head())\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "e7c8eeb1",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "TypeError",
+     "evalue": "MLFlowRepository.__init__() missing 1 required positional argument: 'logger'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
+      "\u001b[31mTypeError\u001b[39m                                 Traceback (most recent call last)",
+      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[2]\u001b[39m\u001b[32m, line 3\u001b[39m\n\u001b[32m      1\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mlaborious\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01mutils\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01mrepository\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01mmodel_repository\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m MLFlowRepository\n\u001b[32m----> \u001b[39m\u001b[32m3\u001b[39m mlflow_repository = \u001b[43mMLFlowRepository\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m      4\u001b[39m \u001b[43m    \u001b[49m\u001b[43mhost\u001b[49m\u001b[43m=\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mhttp://localhost:5080/\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[32m      5\u001b[39m \u001b[43m    \u001b[49m\u001b[43musername\u001b[49m\u001b[43m=\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43maignosi\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[32m      6\u001b[39m \u001b[43m    \u001b[49m\u001b[43mpassword\u001b[49m\u001b[43m=\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43maignosi\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\n\u001b[32m      7\u001b[39m \u001b[43m)\u001b[49m\n\u001b[32m      9\u001b[39m mlflow_repository.get_experiment_by_run_id(\u001b[33m\"\u001b[39m\u001b[33m1\u001b[39m\u001b[33m\"\u001b[39m)\n",
+      "\u001b[31mTypeError\u001b[39m: MLFlowRepository.__init__() missing 1 required positional argument: 'logger'"
+     ]
+    }
+   ],
+   "source": [
+    "from laborious.utils.repository.model_repository import MLFlowRepository\n",
+    "\n",
+    "mlflow_repository = MLFlowRepository(\n",
+    "    host=\"http://localhost:5080/\",\n",
+    "    username=\"aignosi\",\n",
+    "    password=\"aignosi\"\n",
+    ")\n",
+    "\n",
+    "mlflow_repository.get_experiment_by_run_id(\"1\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "venv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
--- a/tests/laborious/activities/test_gates.py
+++ b/tests/laborious/activities/test_gates.py
@@ -344,7 +344,6 @@ async def test_format_prediction(gates_activity):
    assert result['prediction_confidence'] == {0: 0.9}
    assert result['prediction_status'] == {0: 'Good'}
    assert result['comments'] == {0: ""}
-    gates_activity.debug.assert_called()


@mark.asyncio
@@ -393,7 +392,8 @@ async def test_get_last_timestamp_with_data(gates_activity):
 async def test_get_last_timestamp_no_data(gates_activity):
    # Arrange
    input_data = {
-        'data': {}
+        'data': {},
+        **metadata
    }

    # Act
@@ -402,3 +402,42 @@ async def test_get_last_timestamp_no_data(gates_activity):
    # Assert
    assert isinstance(result, str)  # Should be a timestamp string
    assert len(result) > 0
+
+
+@mark.asyncio
+@patch('laborious.activities.gates.metrics')
+async def test_write_metrics(mock_metrics, gates_activity):
+    """Test write_metrics method."""
+    input_data = {
+        **metadata,
+        'prediction': {
+            'prediction': [1, 2, 3],
+            'prediction_confidence': [0.9, 0.8, 0.7],
+            'response_time': [0.1, 0.2, 0.3]
+        }
+    }
+    await gates_activity.write_metrics(input_data)
+    mock_metrics.PREDICTIONS_WRITTEN_COUNT.labels.assert_called_once_with(
+        pod_id=gates_activity.pod_id,
+        model_name=metadata['metadata']['model_name'],
+        pipeline_name=metadata['metadata']['workflow_name']
+    )
+    mock_metrics.PREDICTIONS_WRITTEN_COUNT.labels.return_value.inc.assert_called_once_with()
+
+    mock_metrics.PREDICTION_CONFIDENCE_MONITOR.labels.assert_called_once_with(
+        pod_id=gates_activity.pod_id,
+        model_name=metadata['metadata']['model_name'],
+        pipeline_name=metadata['metadata']['workflow_name']
+    )
+    mock_metrics.PREDICTION_CONFIDENCE_MONITOR.labels.return_value.set.assert_called_once_with(
+        0.9
+    )
+
+    mock_metrics.PREDICTION_RESPONSE_TIME_MONITOR.labels.assert_called_once_with(
+        pod_id=gates_activity.pod_id,
+        model_name=metadata['metadata']['model_name'],
+        pipeline_name=metadata['metadata']['workflow_name']
+    )
+    mock_metrics.PREDICTION_RESPONSE_TIME_MONITOR.labels.return_value.observe.assert_called_once_with(
+        0.1
+    )
--- a/tests/laborious/activities/test_mlflow.py
+++ b/tests/laborious/activities/test_mlflow.py
@@ -24,7 +24,7 @@ def test___init__(mock_mlflow_repository):
    assert mlflow.mlflow_password == "admin"

    mock_mlflow_repository.assert_called_once_with(
-        "http://localhost:5000", "admin", "admin"
+        "http://localhost:5000", "admin", "admin", ANY
    )


--- a/tests/laborious/activities/test_opc.py
+++ b/tests/laborious/activities/test_opc.py
@@ -91,6 +91,7 @@ def test___init__(mock_send_notification, mock_opc_repository):
            server_cert_path="",
            notification_handler=mock_notification_handler,
            reconnection_interval=60,
+            pod_id='localhost'
        ),
    ])
    mock_opc_repository.assert_has_calls([
@@ -104,6 +105,7 @@ def test___init__(mock_send_notification, mock_opc_repository):
            server_cert_path="",
            notification_handler=mock_notification_handler,
            reconnection_interval=60,
+            pod_id='localhost'
        )
    ])

--- a/tests/laborious/utils/repository/test_model_repository.py
+++ b/tests/laborious/utils/repository/test_model_repository.py
@@ -16,7 +16,8 @@ def mlflow_repository():
        repo = MLFlowRepository(
            host='http://localhost:5000',
            username='admin',
-            password='admin'
+            password='admin',
+            logger=MagicMock()
        )
        return repo

@@ -71,7 +72,9 @@ def test_predict_success(mlflow_repository):

    assert output['success'] is True
    assert output['content'] == {'prediction': {
-        0: 3}, 'response_time': ANY}
+        0: 2,
+        1: 3
+    }, 'response_time': ANY}


 def test_predict_error(mlflow_repository):
--- a/tests/laborious/utils/repository/test_opc_repository.py
+++ b/tests/laborious/utils/repository/test_opc_repository.py
@@ -139,8 +139,9 @@ def test_disconnect_error(opc_repository, mock_client):
    mock_client.disconnect.side_effect = Exception("Test error")
    opc_repository.disconnect()

-    opc_repository.logger.error.assert_called_once_with(
-        "Failed to disconnect from OPC server: Test error"
+    opc_repository.logger.custom_error.assert_called_once_with(
+        "Failed to disconnect from OPC server: Test error",
+        ANY
    )
    assert opc_repository.client is None

@@ -163,9 +164,9 @@ def test_validate_connection_error_count_disconnect_error(opc_repository):
    assert response == opc_repository.connect.return_value
    opc_repository.disconnect.assert_called_once()
    opc_repository.connect.assert_called_once()
-    opc_repository.logger.error.assert_has_calls(
+    opc_repository.logger.custom_error.assert_has_calls(
        [
-            call("Failed to disconnect from OPC server: Test error"),
+            call("Failed to disconnect from OPC server: Test error", ANY),
        ]
    )

@@ -182,7 +183,12 @@ def test_validate_connection_lost_not_time_to_reconect(_mock_datetime, opc_repos

    response = opc_repository.validate_connection()
    opc_repository.try_connect.assert_not_called()
-    assert response == (False, {})
+    assert response == (False, {
+        "notification_id": f"OPC_CONNECTION_AWAITING_RECONNECTION_WINDOW_{opc_repository.id}",
+        "message": f"OPC server {opc_repository.id} is not connected, waiting for next reconnection window...",
+        "block": "opc_repository",
+        "level": NotificationLevel.WARNING
+    })


@patch('laborious.utils.repository.opc_repository.hasattr', return_value=True)
@@ -263,18 +269,36 @@ def test_write_data_invalid_data_type(opc_repository, mock_client):
    assert error_data.get('attachment_content') is None


-def test_write_data(opc_repository, mock_client):
+@patch('laborious.utils.repository.opc_repository.metrics')
+def test_write_data(mock_metrics, opc_repository, mock_client):
    opc_repository.validate_connection = MagicMock(return_value=(True, {}))
    opc_repository.client = mock_client
    mock_node = MagicMock()
    mock_client.get_node.return_value = mock_node

    opc_repository.write_data("ns=2;s=TestNode", 42.0,
-                              "float", opc_repository.logger, metadata)
+                              "float", opc_repository.logger, metadata['metadata'])

    mock_client.get_node.assert_called_once_with("ns=2;s=TestNode")
    mock_node.write_value.assert_called_once()

+    mock_metrics.PREDICTION_OPC_WRITING_COUNT.labels.assert_called_once_with(
+        pod_id=opc_repository.pod_id,
+        model_name=metadata['metadata']['model_name'],
+        pipeline_name=metadata['metadata']['workflow_name'],
+        opc_server_id=opc_repository.id
+    )
+    mock_metrics.PREDICTION_OPC_WRITING_COUNT.labels.return_value.inc.assert_called_once_with()
+
+    mock_metrics.PREDICTION_OPC_WRITING_RESPONSE_TIME_MONITOR.labels.assert_called_once_with(
+        pod_id=opc_repository.pod_id,
+        model_name=metadata['metadata']['model_name'],
+        pipeline_name=metadata['metadata']['workflow_name'],
+        opc_server_id=opc_repository.id
+    )
+    mock_metrics.PREDICTION_OPC_WRITING_RESPONSE_TIME_MONITOR.labels.return_value.observe.assert_called_once_with(
+        ANY)
+

 def test_write_data_write_value_failed(opc_repository, mock_client):
    opc_repository.validate_connection = MagicMock(return_value=(True, {}))
--- a/tests/laborious/workflows/subworkflows/test_format_and_export_prediction.py
+++ b/tests/laborious/workflows/subworkflows/test_format_and_export_prediction.py
@@ -79,7 +79,7 @@ async def test_run_none_path_flag(workflow_mock, format_and_export_prediction):
            start_to_close_timeout=ANY
        )])

-    assert workflow_mock.execute_activity_method.call_count == 2
+    assert workflow_mock.execute_activity_method.call_count == 3
    assert workflow_mock.execute_local_activity_method.call_count == 1


@@ -145,5 +145,5 @@ async def test_run_default_path_flag(workflow_mock, format_and_export_prediction
        )
    ])

-    assert workflow_mock.execute_activity_method.call_count == 2
+    assert workflow_mock.execute_activity_method.call_count == 3
    assert workflow_mock.execute_local_activity_method.call_count == 1
--- a/values.yaml
+++ b/values.yaml
@@ -11,7 +11,7 @@ image:
  # This sets the pull policy for images.
  pullPolicy: Always
  # Overrides the image tag whose default is the chart appVersion.
-  tag: "0.2.7"
+  tag: "0.4.2"

 # This is for the secrets for pulling an image from a private repository more information can be found here: https://kubernetes.io/docs/tasks/configure-pod-container/pull-image-private-registry/
 imagePullSecrets:
@@ -111,11 +111,39 @@ tolerations: []

 affinity: {}

-service:
-  enabled: false
-  type: ClusterIP
-  port: 4840
-  targetPort: 4840
+services:
+  sdk-metrics:
+    enabled: true
+    type: ClusterIP
+    port: 9091
+    targetPort: 9091
+    name: sdk-metrics
+
+  metrics:
+    enabled: true
+    type: ClusterIP
+    port: 9090
+    targetPort: 9090
+    name: metrics
+
+# Configuração do ServiceMonitor para o Prometheus Operator
+# ref: https://github.com/prometheus-operator/prometheus-operator
+serviceMonitor:
+  # Se true, um recurso ServiceMonitor será criado.
+  enabled: true
+  # O intervalo no qual as métricas devem ser coletadas (ex: 30s, 1m).
+  endpoints:
+  - port: metrics
+    path: /metrics
+    interval: 30s
+    relabelings: []
+  - port: sdk-metrics
+    path: /metrics
+    interval: 30s
+    relabelings: []
+
+  additionalLabels:
+    release: kube-prometheus-stack
  

 env:
@@ -123,7 +151,7 @@ env:
  - name: GITHUB_REPO_URL
    value: "git@github.com:Aignosi/sientia-dataops-laborious_temporal.git"
  - name: GITHUB_BRANCH
-    value: "SIENTIAPDE-1172-criar-pipeline-de-alertas-orquestrador"
+    value: "SIENTIAPDE-1199-revisar-e-testar-observabilidade"
  - name: PYTHON_APP
    value: "laborious.worker.worker"

@@ -162,6 +190,10 @@ env:

  - name: LOG_LEVEL
    value: "DEBUG"
+  - name: HTTP_METRICS_PORT
+    value: "9090"
+  - name: HTTP_SDK_METRICS_PORT
+    value: "9091"
  - name: PROJECT_NAME
    value: "sientia-laborious"

@@ -189,7 +221,7 @@ ssh:

 # kubectl create secret docker-registry docker-hub-secret --namespace sientia --docker-server=http://aignosi.azurecr.io --docker-username=aignosi --docker-password=5I5zpQ6sRaHqX1hD3dr+2mo647yO3FRc359/wu6gsP+ACRDRz5mp

-# helm upgrade --install sientia-laborious-worker sientia/sientia-module -n sientia --create-namespace -f ./values.yaml --version 0.4.0-uat
+# helm upgrade --install sientia-laborious-worker sientia/sientia-module -n sientia --create-namespace -f ./values.yaml --version 0.5.0

 # kubectl create secret generic git-ssh-key-sientia-laborious-worker \
 #   --namespace sientia \
Author	SHA1	Message	Date
vitor-aignosi	a3b642dbef	SIENTIAPDE-1199 Update tests in Gates and OpcRepository to enhance logging and include metadata - Removed unnecessary debug assertion in the Gates activity test for format prediction. - Updated the test for last timestamp with no data to include a metadata dictionary. - Modified OpcRepository tests to utilize custom_error logging with metadata for improved error context.	2025-08-21 08:56:22 -03:00
vitor-aignosi	39ff7e2625	Merge branch 'main' into SIENTIAPDE-1199-revisar-e-testar-observabilidade	2025-08-21 08:51:41 -03:00
vitor-aignosi	7b5c519cde	SIENTIAPDE-1199 Update replica count in values.yaml from 3 to 5 for increased scalability	2025-08-21 08:09:20 -03:00
Matheus Demoner	93f0e3b100	Merge pull request #15 from Aignosi/SIENTIAPDE-1169-pensar-e-projetar-testes-de-breakdown-e-performance Sientiapde 1169 pensar e projetar testes de breakdown e performance	2025-08-20 12:50:07 -03:00
vitor-aignosi	935a9e9279	SIENTIAPDE-1199 Enhance logging in OpcRepository to include metadata for all log messages - Introduced a metadata dictionary to the OpcRepository class for improved context in logging. - Updated logging statements to utilize custom_info, custom_warning, and custom_error methods, ensuring all key operations and error messages include relevant metadata. - Improved visibility of connection status, disconnection attempts, and error handling, facilitating better monitoring and debugging.	2025-08-20 11:35:42 -03:00
vitor-aignosi	40870b021a	SIENTIAPDE-1199 Refactor logging in worker module to include metadata in custom info and error messages - Updated logging statements in the worker module to utilize custom_info and custom_error methods, incorporating a metadata dictionary for enhanced context. - Improved visibility of key operations such as starting the worker, notification handler, and activities, as well as error handling for unhandled exceptions.	2025-08-20 10:51:38 -03:00
vitor-aignosi	8b9bb8d720	SIENTIAPDE-1199 Refactor logging in Gates and MLFlow activities to use info level for key operations - Updated logging statements in the Gates class to replace debug logs with info logs for input and output gate operations, enhancing visibility. - Modified MLFlow class to use info logs for data transformation and prediction processes, improving clarity in the logging output. - Adjusted OPC class to return the count of successfully written tags, providing better insight into data writing operations.	2025-08-20 10:38:08 -03:00
vitor-aignosi	89384d7783	SIENTIAPDE-1199 Update test for validate_connection method in OpcRepository to include detailed response structure - Modified the test case to assert the response format when the connection is lost, ensuring it includes notification ID, message, block, and level attributes for better clarity in error handling.	2025-08-19 16:42:48 -03:00
vitor-aignosi	ef32167f57	SIENTIAPDE-1199 Update dependencies in requirements.txt and increment image tag in values.yaml - Updated sientia-dataops-library dependency version from 1.4.0 to 1.4.1 in requirements.txt. - Incremented image tag in values.yaml from 0.4.1 to 0.4.2.	2025-08-19 16:05:13 -03:00
vitor-aignosi	46e21c7538	SIENTIAPDE-1199 Enhance logging in MLFlow activity to include formatted JSON response data - Added JSON import for better formatting of response data in debug logs. - Updated logging statements to output transformed and prediction response data as pretty-printed JSON, improving readability and debugging context.	2025-08-19 12:12:15 -03:00
vitor-aignosi	8012ff778c	SIENTIAPDE-1199 Refactor logging in OpcRepository to include full metadata in error and info messages - Updated logging statements in the OpcRepository class to pass the complete metadata object instead of just the schedule name, enhancing the context available for debugging and monitoring.	2025-08-19 11:52:42 -03:00
vitor-aignosi	3a06f0ca39	SIENTIAPDE-1199 Update dependencies and refactor logging imports for observability - Updated the sientia-dataops-library dependency version to 1.4.0 in requirements.txt. - Changed image tag in values.yaml from 0.3.2 to 0.4.1. - Refactored logging imports across multiple files to use the new observability module instead of the temporal.utils.logger. - Updated retry policy imports in workflow files to reflect the new module structure.	2025-08-19 10:42:27 -03:00
vitor-aignosi	3ee076214c	SIENTIAPDE-1169 Implement server validation and output tag management in OPC class - Added a new method to validate the existence of OPC servers before writing data, improving error handling. - Introduced a method to manage writing of prediction and confidence tags, streamlining the data writing process. - Refactored the write_opc_data method to utilize the new validation and management methods for better code organization and clarity.	2025-08-19 09:07:05 -03:00
vitor-aignosi	fc6c95c264	SIENTIAPDE-1169 Refactor OPC data writing and repository initialization - Simplified success tracking logic in the OPC class for writing prediction and confidence data. - Removed unused pod_id attribute from OpcRepository initialization. - Updated test cases to include pod_id for improved metrics tracking during data writing operations.	2025-08-19 08:31:58 -03:00
vitor-aignosi	cc7efba887	SIENTIAPDE-1169 Refactor OPC data writing to improve success tracking - Updated the OPC class to store the success status of data writing operations for both prediction and confidence tags. - Added logging for successful and failed writes to the OPC server, enhancing traceability of data operations.	2025-08-18 16:30:33 -03:00
vitor-aignosi	37a31a51a4	SIENTIAPDE-1169 Refactor OPC metrics to use unpacking for CORE_LABELS in metrics.py - Updated the definition of prediction OPC writing metrics to utilize unpacking for CORE_LABELS, enhancing code clarity and maintainability.	2025-08-18 14:17:43 -03:00
vitor-aignosi	e567b8d0a7	SIENTIAPDE-1169 Update OPC metrics to include opc_server_id for enhanced tracking	2025-08-18 14:15:22 -03:00
vitor-aignosi	366d406689	SIENTIAPDE-1169 Enhance OpcRepository initialization to include pod_id for improved tracking	2025-08-18 14:08:00 -03:00
vitor-aignosi	f56755b69e	SIENTIAPDE-1169 Refactor opc_repository.py to import metrics module - Added import statement for the metrics module to enhance functionality in the OPC repository. - This change supports the integration of metrics tracking for OPC operations.	2025-08-18 14:04:02 -03:00
vitor-aignosi	e35eb300cb	SIENTIAPDE-1169 Implement OPC writing metrics and enhance OPC class initialization - Added metrics for counting predictions written to the OPC server and monitoring their response times. - Enhanced the OPC class initialization to include the pod ID for better tracking. - Updated the write method to increment the prediction count and observe response times.	2025-08-18 13:58:43 -03:00
vitor-aignosi	6eb71739db	SIENTIAPDE-1169 Update helm chart version in values.yaml to 0.5.0	2025-08-18 13:47:50 -03:00
vitor-aignosi	e82b25582c	SIENTIAPDE-1169 Update helm chart version in values.yaml and modify logging in worker.py - Updated helm upgrade command in values.yaml to version 0.5.0-uat. - Changed log message in worker.py to indicate the start of the SDK Metrics Server, while retaining the original log for the Temporal Client.	2025-08-18 09:45:54 -03:00
vitor-aignosi	a2a9f95aa5	SIENTIAPDE-1169 SIENTIAPDE-1174 Add SDK metrics configuration and update worker for telemetry - Introduced sdk-metrics service in values.yaml with ClusterIP configuration. - Updated worker.py to integrate SDK metrics telemetry using the new HTTP_SDK_METRICS_PORT environment variable. - Enhanced Prometheus configuration to bind SDK metrics to the specified port.	2025-08-18 09:41:17 -03:00
vitor-aignosi	7f3457e318	SIENTIAPDE-1169 Enhance BaseActivity initialization across multiple activities to include error counter - Updated the initialization of the BaseActivity in Gates, MLFlow, and OPC classes to set the error counter to True, improving error tracking and handling capabilities.	2025-08-14 15:41:03 -03:00
vitor-aignosi	da10f900a8	SIENTIAPDE-1169 Update dependencies and configuration for improved functionality - Updated sientia-dataops-library version from 1.3.7 to 1.3.8 in requirements.txt. - Changed GITHUB_BRANCH in values.yaml to reflect new testing focus: SIENTIAPDE-1169. - Modified notification level in gates.py from WARNING to ERROR for better error handling.	2025-08-14 15:25:04 -03:00
Bruno Domingues	f195b5116e	Merge pull request #14 from Aignosi/SIENTIAPDE-1174-mapear-e-implementar-metricas-a-serem-criadas Sientiapde 1174 mapear e implementar metricas a serem criadas	2025-08-13 16:35:04 -03:00
vitor-aignosi	dd513ddfaf	SIENTIAPDE-1174 Add async test for write_metrics method in gates_activity - Implemented a new test to validate the write_metrics functionality, ensuring metrics are correctly recorded for predictions, confidence, and response time. - Utilized mocking to verify interactions with the metrics tracking system.	2025-08-05 14:39:02 -03:00
vitor-aignosi	fbdf9c3c6c	SIENTIAPDE-1174 SIENTIAPDE-1174 Update tests to enhance MLFlow and workflow activity assertions - Added logger initialization in MLFlowRepository for improved logging. - Updated prediction test assertions to reflect changes in output structure. - Increased activity method call count assertions in workflow tests for accuracy.	2025-08-05 14:19:56 -03:00
vitor-aignosi	3d7de2ef5e	Merge branch 'main' into SIENTIAPDE-1174-mapear-e-implementar-metricas-a-serem-criadas	2025-08-05 14:05:09 -03:00
vitor-aignosi	c92e2f41c3	SIENTIAPDE-1174 pdate metrics tracking to include response time histogram - Changed PREDICTION_RESPONSE_TIME_MONITOR from Gauge to Histogram for better response time analysis. - Updated response time observation method in gates.py to utilize the new Histogram functionality.	2025-08-04 16:09:26 -03:00
vitor-aignosi	3cf7b4ec16	SIENTIAPDE-1174 SIENTIAPDE-1174 Update replica count and image tag in values.yaml - Increased replicaCount from 1 to 3 for improved availability. - Updated image tag from 0.3.1 to 0.3.2 for the latest features and fixes.	2025-08-04 15:24:20 -03:00
vitor-aignosi	663b286ad7	SIENTIAPDE-1174 SIENTIAPDE-1174 Update tests.ipynb to normalize counter and rollout values, and fix MLFlowRepository initialization error - Changed execution_count for a cell to null for consistency. - Updated normalization logic for counter and rollout values to scale between -100 and 100. - Fixed TypeError in MLFlowRepository initialization by ensuring the logger argument is provided.	2025-08-04 10:03:15 -03:00
Bruno Domingues	28743eb720	Merge pull request #13 from Aignosi/SIENTIAPDE-1172-criar-pipeline-de-alertas-orquestrador Sientiapde 1172 criar pipeline de alertas orquestrador	2025-08-04 10:02:56 -03:00
vitor-aignosi	47df5ebc60	SIENTIAPDE-1174 SIENTIAPDE-1174 Update MLFlowRepository initialization to include logger for enhanced logging capabilities	2025-08-01 17:15:49 -03:00
vitor-aignosi	669494c90b	SIENTIAPDE-1174 Mark application as DOWN in metrics on shutdown to improve failure reporting	2025-08-01 12:01:29 -03:00
vitor-aignosi	963f089c7b	SIENTIAPDE-1174 SIENTIAPDE-1174 Update replica count and enhance logging in MLFlow - Changed replicaCount in values.yaml from 3 to 1 for reduced resource usage. - Added debug logging for prediction response data in MLFlow to improve traceability.	2025-08-01 10:32:06 -03:00
vitor-aignosi	4f6f4d1fa9	SIENTIAPDE-1174 Enable data index reset in MLFlow by uncommenting data.reset_index, improving data processing consistency.	2025-08-01 10:20:42 -03:00
vitor-aignosi	4fb89b3862	SIENTIAPDE-1174 Comment out data.reset_index in MLFlow to prevent index reset during data processing, improving data handling without altering existing functionality.	2025-08-01 10:16:41 -03:00
vitor-aignosi	d2952654b4	SIENTIAPDE-1174 SIENTIAPDE-1174 Add write_metrics activity to main workflow for enhanced metrics tracking - Included the write_metrics activity in the main workflow to support Prometheus metrics tracking.	2025-08-01 10:03:19 -03:00
vitor-aignosi	70f1abe681	SIENTIAPDE-1174 Update dependencies, modify replica count, and implement metrics tracking - Updated sientia-dataops-library version from 1.3.5 to 1.3.7 in requirements.txt. - Changed replicaCount in values.yaml from 5 to 3 and incremented image tag from 0.2.7 to 0.3.1. - Added Prometheus metrics tracking in gates.py and worker.py, including a new write_metrics method. - Configured Prometheus service and ServiceMonitor in values.yaml for metrics collection.	2025-08-01 10:00:47 -03:00