SIENTIAPDE-1314

Implement tag value registration in Gates activity and update related tests. Enhanced the write_metrics method to process and register tag values, improving metrics tracking. Adjusted tests to validate new functionality.

scouter/activities/gates.py

@@ -284,6 +284,7 @@ class Gates(BaseActivity):
             metadata: dict[str, Any]
         """
         metadata = input_data['metadata']
+        tag_values = DataFrame(input_data['tag_values'])
 
         self.info(f'Writing metrics for {metadata["model_name"]}', metadata=metadata)
 
@@ -293,4 +294,13 @@ class Gates(BaseActivity):
             pipeline_name=metadata['workflow_name'],
         ).inc()
 
+        # Register metrics
+        for _, row in tag_values.iterrows():
+            metrics.TAG_CHANGES_MONITOR.labels(
+                pod_id=self.pod_id,
+                model_name=metadata['model_name'],
+                pipeline_name=metadata['workflow_name'],
+                tag_name=row['variable'],
+            ).set(row['value'])
+
         self.info(f'Metrics written for {metadata["model_name"]}', metadata=metadata)

scouter/activities/redis.py

@@ -13,7 +13,6 @@ with workflow.unsafe.imports_passed_through():
     from sientia_do.temporal.activities.redis_base import Redis as RedisBase
     from sientia_do.temporal.constants import DATETIME_FORMAT, now
 
-    from scouter import metrics
 
 
 class Redis(RedisBase):
@@ -220,12 +219,10 @@ class Redis(RedisBase):
             data_hold = {tag: content for tag, content in data_hold.items() if tag in tags}
             self.debug(f'Data hold after removing removed tags: {data_hold}', metadata=metadata)
 
-            to_register_metrics = []
             for _, row in data.iterrows():
                 value = row['value']
 
                 data_hold[row['name']] = value
-                to_register_metrics.append((row['name'], value))
 
             if fill_missing_tags:
                 self.debug('Filling missing tags in data package', metadata=metadata)
@@ -240,16 +237,6 @@ class Redis(RedisBase):
 
             self.set(key, data_hold, ttl=retention_time)
 
-            # Register metrics
-            self.debug(f'Metrics to register: {to_register_metrics}', metadata=metadata)
-            for metric in to_register_metrics:
-                metrics.TAG_CHANGES_MONITOR.labels(
-                    pod_id=self.pod_id,
-                    model_name=metadata['model_name'],
-                    pipeline_name=metadata['workflow_name'],
-                    tag_name=metric[0],
-                ).set(metric[1])
-
             data_hold_df = DataFrame(data_hold, index=[0])
             data_hold_melted = data_hold_df.melt(
                 id_vars='timestamp', var_name='variable', value_name='value'