migration(workflow-engine): Delete malformed anomaly conditions

migrations_lockfile.txt

@@ -43,4 +43,4 @@ tempest: 0001_squashed_0003_use_encrypted_char_field
 
 uptime: 0001_squashed_0055_backfill_2xx_status_assertion
 
-workflow_engine: 0120_replace_boolean_deescalation_comparisons
+workflow_engine: 0121_delete_malformed_anomaly_conditions

src/sentry/workflow_engine/migrations/0121_delete_malformed_anomaly_conditions.py

@@ -0,0 +1,93 @@
+# Generated by Django 5.2.16 on 2026-09-17 21:56
+
+from collections import defaultdict
+
+from django.db import migrations
+from django.db.backends.base.schema import BaseDatabaseSchemaEditor
+from django.db.migrations.state import StateApps
+
+from sentry.new_migrations.migrations import CheckedMigration
+from sentry.utils.iterators import chunked
+from sentry.utils.query import RangeQuerySetWrapper
+
+BATCH_SIZE = 1000
+
+
+def delete_malformed_anomaly_conditions(
+    apps: StateApps, schema_editor: BaseDatabaseSchemaEditor
+) -> None:
+    AlertRuleTrigger = apps.get_model("sentry", "AlertRuleTrigger")
+    DataCondition = apps.get_model("workflow_engine", "DataCondition")
+    DataConditionAlertRuleTrigger = apps.get_model(
+        "workflow_engine", "DataConditionAlertRuleTrigger"
+    )
+    anomaly_condition_ids = DataCondition.objects.filter(
+        type="anomaly_detection", comparison=0.0
+    ).values_list("id", flat=True)
+
+    for condition_ids in chunked(
+        RangeQuerySetWrapper(
+            anomaly_condition_ids,
+            step=BATCH_SIZE,
+            result_value_getter=lambda condition_id: condition_id,
+        ),
+        BATCH_SIZE,
+    ):
+        condition_ids_by_trigger_id = defaultdict(list)
+        for trigger_id, condition_id in DataConditionAlertRuleTrigger.objects.filter(
+            data_condition_id__in=condition_ids,
+            alert_rule_trigger_id__isnull=False,
+        ).values_list("alert_rule_trigger_id", "data_condition_id"):
+            condition_ids_by_trigger_id[trigger_id].append(condition_id)
+
+        triggers = AlertRuleTrigger.objects.filter(
+            id__in=condition_ids_by_trigger_id
+        ).select_related("alert_rule")
+
+        for trigger in triggers:
+            conditions = DataCondition.objects.filter(
+                id__in=condition_ids_by_trigger_id[trigger.id]
+            )
+            condition_group_ids = conditions.values_list("condition_group_id", flat=True)
+            DataCondition.objects.filter(condition_group_id__in=condition_group_ids).exclude(
+                type="anomaly_detection"
+            ).delete()
+
+            alert_rule = trigger.alert_rule
+            if (
+                alert_rule.sensitivity is None
+                or alert_rule.seasonality is None
+                or alert_rule.threshold_type is None
+            ):
+                continue
+
+            conditions.update(
+                comparison={
+                    "seasonality": alert_rule.seasonality,
+                    "sensitivity": alert_rule.sensitivity,
+                    "threshold_type": alert_rule.threshold_type,
+                }
+            )
+
+
+class Migration(CheckedMigration):
+    is_post_deployment = True
+
+    dependencies = [
+        ("workflow_engine", "0120_replace_boolean_deescalation_comparisons"),
+    ]
+
+    operations = [
+        migrations.RunPython(
+            delete_malformed_anomaly_conditions,
+            reverse_code=migrations.RunPython.noop,
+            hints={
+                "tables": [
+                    "sentry_alertrule",
+                    "sentry_alertruletrigger",
+                    "workflow_engine_datacondition",
+                    "workflow_engine_dataconditionalertruletrigger",
+                ]
+            },
+        ),
+    ]

tests/sentry/migrations/test_0121_delete_malformed_anomaly_conditions.py

@@ -0,0 +1,200 @@
+from sentry.testutils.cases import TestMigrations
+
+
+class DeleteMalformedAnomalyConditionsTest(TestMigrations):
+    app = "workflow_engine"
+    migrate_from = "0120_replace_boolean_deescalation_comparisons"
+    migrate_to = "0121_delete_malformed_anomaly_conditions"
+
+    def setup_before_migration(self, apps):
+        AlertRule = apps.get_model("sentry", "AlertRule")
+        AlertRuleTrigger = apps.get_model("sentry", "AlertRuleTrigger")
+        DataCondition = apps.get_model("workflow_engine", "DataCondition")
+        DataConditionAlertRuleTrigger = apps.get_model(
+            "workflow_engine", "DataConditionAlertRuleTrigger"
+        )
+        DataConditionGroup = apps.get_model("workflow_engine", "DataConditionGroup")
+        SnubaQuery = apps.get_model("sentry", "SnubaQuery")
+
+        snuba_query = SnubaQuery.objects.create(
+            type=0,
+            dataset="events",
+            query="",
+            aggregate="count()",
+            time_window=60,
+            resolution=60,
+        )
+        alert_rule = AlertRule.objects_with_snapshots.create(
+            organization_id=self.organization.id,
+            snuba_query_id=snuba_query.id,
+            name="Malformed anomaly detector",
+            threshold_type=1,
+            threshold_period=1,
+            detection_type="dynamic",
+            sensitivity="medium",
+            seasonality="weekly",
+        )
+        alert_rule_trigger = AlertRuleTrigger.objects.create(
+            alert_rule_id=alert_rule.id,
+            label="critical",
+            threshold_type=1,
+            alert_threshold=0,
+        )
+
+        malformed_group = DataConditionGroup.objects.create(organization_id=self.organization.id)
+        self.anomaly_condition = DataCondition.objects.create(
+            condition_group_id=malformed_group.id,
+            type="anomaly_detection",
+            comparison=0.0,
+            condition_result=75,
+        )
+        self.malformed_condition = DataCondition.objects.create(
+            condition_group_id=malformed_group.id,
+            type="lte",
+            comparison=0,
+            condition_result=0,
+        )
+        DataConditionAlertRuleTrigger.objects.create(
+            data_condition_id=self.anomaly_condition.id,
+            alert_rule_trigger_id=alert_rule_trigger.id,
+        )
+
+        second_malformed_group = DataConditionGroup.objects.create(
+            organization_id=self.organization.id
+        )
+        self.second_anomaly_condition = DataCondition.objects.create(
+            condition_group_id=second_malformed_group.id,
+            type="anomaly_detection",
+            comparison=0.0,
+            condition_result=75,
+        )
+        self.second_malformed_condition = DataCondition.objects.create(
+            condition_group_id=second_malformed_group.id,
+            type="lte",
+            comparison=0,
+            condition_result=0,
+        )
+        DataConditionAlertRuleTrigger.objects.create(
+            data_condition_id=self.second_anomaly_condition.id,
+            alert_rule_trigger_id=alert_rule_trigger.id,
+        )
+
+        incomplete_snuba_query = SnubaQuery.objects.create(
+            type=0,
+            dataset="events",
+            query="",
+            aggregate="count()",
+            time_window=60,
+            resolution=60,
+        )
+        incomplete_alert_rule = AlertRule.objects_with_snapshots.create(
+            organization_id=self.organization.id,
+            snuba_query_id=incomplete_snuba_query.id,
+            name="Incomplete anomaly detector",
+            threshold_type=1,
+            threshold_period=1,
+            detection_type="dynamic",
+            sensitivity=None,
+            seasonality="weekly",
+        )
+        incomplete_alert_rule_trigger = AlertRuleTrigger.objects.create(
+            alert_rule_id=incomplete_alert_rule.id,
+            label="critical",
+            threshold_type=1,
+            alert_threshold=0,
+        )
+        incomplete_group = DataConditionGroup.objects.create(organization_id=self.organization.id)
+        self.incomplete_anomaly_condition = DataCondition.objects.create(
+            condition_group_id=incomplete_group.id,
+            type="anomaly_detection",
+            comparison=0.0,
+            condition_result=75,
+        )
+        self.incomplete_mixed_condition = DataCondition.objects.create(
+            condition_group_id=incomplete_group.id,
+            type="lte",
+            comparison=0,
+            condition_result=0,
+        )
+        DataConditionAlertRuleTrigger.objects.create(
+            data_condition_id=self.incomplete_anomaly_condition.id,
+            alert_rule_trigger_id=incomplete_alert_rule_trigger.id,
+        )
+
+        orphaned_group = DataConditionGroup.objects.create(organization_id=self.organization.id)
+        self.orphaned_anomaly_condition = DataCondition.objects.create(
+            condition_group_id=orphaned_group.id,
+            type="anomaly_detection",
+            comparison=0.0,
+            condition_result=75,
+        )
+        self.orphaned_mixed_condition = DataCondition.objects.create(
+            condition_group_id=orphaned_group.id,
+            type="lte",
+            comparison=0,
+            condition_result=0,
+        )
+
+        valid_anomaly_group = DataConditionGroup.objects.create(
+            organization_id=self.organization.id
+        )
+        self.valid_anomaly_condition = DataCondition.objects.create(
+            condition_group_id=valid_anomaly_group.id,
+            type="anomaly_detection",
+            comparison={
+                "sensitivity": "high",
+                "seasonality": "auto",
+                "threshold_type": 0,
+            },
+            condition_result=75,
+        )
+        self.valid_mixed_condition = DataCondition.objects.create(
+            condition_group_id=valid_anomaly_group.id,
+            type="lte",
+            comparison=0,
+            condition_result=0,
+        )
+
+        static_group = DataConditionGroup.objects.create(organization_id=self.organization.id)
+        self.valid_static_condition = DataCondition.objects.create(
+            condition_group_id=static_group.id,
+            type="lte",
+            comparison=0,
+            condition_result=0,
+        )
+
+    def test(self):
+        DataCondition = self.apps.get_model("workflow_engine", "DataCondition")
+
+        anomaly_condition = DataCondition.objects.get(id=self.anomaly_condition.id)
+        assert anomaly_condition.comparison == {
+            "seasonality": "weekly",
+            "sensitivity": "medium",
+            "threshold_type": 1,
+        }
+        assert not DataCondition.objects.filter(id=self.malformed_condition.id).exists()
+
+        second_anomaly_condition = DataCondition.objects.get(id=self.second_anomaly_condition.id)
+        assert second_anomaly_condition.comparison == anomaly_condition.comparison
+        assert not DataCondition.objects.filter(id=self.second_malformed_condition.id).exists()
+
+        incomplete_anomaly_condition = DataCondition.objects.get(
+            id=self.incomplete_anomaly_condition.id
+        )
+        assert incomplete_anomaly_condition.comparison == 0.0
+        assert not DataCondition.objects.filter(id=self.incomplete_mixed_condition.id).exists()
+
+        orphaned_anomaly_condition = DataCondition.objects.get(
+            id=self.orphaned_anomaly_condition.id
+        )
+        assert orphaned_anomaly_condition.comparison == 0.0
+        assert DataCondition.objects.filter(id=self.orphaned_mixed_condition.id).exists()
+
+        valid_anomaly_condition = DataCondition.objects.get(id=self.valid_anomaly_condition.id)
+        assert valid_anomaly_condition.comparison == {
+            "sensitivity": "high",
+            "seasonality": "auto",
+            "threshold_type": 0,
+        }
+        assert DataCondition.objects.filter(id=self.valid_mixed_condition.id).exists()
+        assert DataCondition.objects.filter(id=self.valid_static_condition.id).exists()