fix(simple_metrics): update adaptive state even without thresholds so removed thresholds recover (SIENTIAPDE-2191)

laborious/activities/model_metrics.py

@@ -537,7 +537,7 @@ class ModelMetrics(SientiaMonitoring):
                 - metadata (dict): Workflow metadata; `schedule_name` identifies the doc.
                 - simple_metrics (list[dict]): Rows from `calculate_simple_metrics`; empty for an
                   empty or under-sampled window, which counts as a non-breach run.
-                - thresholds (dict): `simple_metrics_thresholds` from `model_config`.
+                - thresholds (dict): `simple_metrics_thresholds` from `model_config` (may be None: no breach).
                 - interval_minutes (int): Window size, used to compute the recovery runs.
 
         Return:

laborious/workflows/simple_metrics.py

@@ -77,7 +77,7 @@ class SimpleMetrics:
         if target_data and not enough_samples:
             workflow.logger.info(
                 f'{len(target_data)} rows < simple_metrics_min_samples={min_samples}: '
-                'threshold alerting skipped'
+                'threshold alerting and escalation skipped'
             )
 
         simple_metrics = None
@@ -114,17 +114,15 @@ class SimpleMetrics:
                 start_to_close_timeout=timedelta(seconds=300),
             )
 
-        if not thresholds:
-            # No thresholds = no breach possible, so skip the Mongo round trip.
-            return
-
         try:
             await workflow.execute_activity_method(
                 Activities.update_simple_metrics_adaptive_state,
                 {
                     **metadata,
                     # Only a valid breach escalates: an empty or under-sampled window is sent as
-                    # no rows, which counts as a healthy run (spec decision 8).
+                    # no rows, which counts as a healthy run (spec decision 8). Always called, even
+                    # without thresholds (no breach), so an escalated doc recovers after they are
+                    # removed.
                     'simple_metrics': (simple_metrics or []) if enough_samples else [],
                     'thresholds': thresholds,
                     'interval_minutes': interval_minutes,