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.

laborious/activities/gates.py

@@ -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,
@@ -309,3 +310,34 @@ class Gates(BaseActivity):
         if data.empty:
             return datetime.now().strftime('%Y-%m-%d %H:%M:%S')
         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]
+
+        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']
+        ).set(response_time)