feat(alerts): Support apdex alerts for anomaly detection

src/sentry/seer/anomaly_detection/store_data.py

@@ -6,6 +6,8 @@
 from django.utils import timezone
 from urllib3.exceptions import MaxRetryError, TimeoutError
 
+from sentry import release_health
+from sentry.api.endpoints.organization_on_demand_metrics_estimation_stats import get_stats_generator
 from sentry.conf.server import SEER_ANOMALY_DETECTION_STORE_DATA_URL
 from sentry.incidents.models.alert_rule import AlertRule, AlertRuleStatus
 from sentry.models.project import Project
@@ -142,24 +144,38 @@ def fetch_historical_data(
         dataset_label = "errors"
     dataset = get_dataset(dataset_label)
 
-    if not project or not dataset or not alert_rule.organization:
+    if not project or not alert_rule.organization:
         return None
 
+    snuba_params = SnubaParams(
+        organization=alert_rule.organization,
+        projects=[project],
+        start=start,
+        end=end,
+    )
+
     if dataset == metrics_performance:
-        return get_crash_free_historical_data(
+        historical_data = get_crash_free_historical_data(
             start, end, project, alert_rule.organization, granularity
         )
-
+    elif "apdex" in snuba_query.aggregate:
+        generator = get_stats_generator(use_discover=True, remove_on_demand=False)
+        historical_data = generator(
+            query_columns=[snuba_query.aggregate],
+            query=snuba_query.query,
+            snuba_params=snuba_params,
+            rollup=granularity,
+            zerofill_results=True,
+            comparison_delta=alert_rule.comparison_delta,
+        )
     else:
+        if not dataset:
+            return None
+
         historical_data = dataset.timeseries_query(
             selected_columns=[snuba_query.aggregate],
             query=snuba_query.query,
-            snuba_params=SnubaParams(
-                organization=alert_rule.organization,
-                projects=[project],
-                start=start,
-                end=end,
-            ),
+            snuba_params=snuba_params,
             rollup=granularity,
             referrer=Referrer.ANOMALY_DETECTION_HISTORICAL_DATA_QUERY.value,
             zerofill_results=True,

tests/sentry/seer/anomaly_detection/test_store_data.py

@@ -14,6 +14,7 @@
 from sentry.testutils.factories import EventType
 from sentry.testutils.helpers.datetime import iso_format
 from sentry.testutils.performance_issues.event_generators import get_event
+from sentry.utils.samples import load_data
 from sentry.utils.snuba import SnubaTSResult
 from tests.sentry.incidents.endpoints.test_organization_alert_rule_index import AlertRuleBase
 
@@ -157,3 +158,29 @@ def test_anomaly_detection_fetch_historical_data_crash_rate_alert(self):
         assert result
         assert self.time_1 in result.data.get("data").get("intervals")
         assert 1 in result.data.get("data").get("groups")[0].get("series").get("sum(session)")
+
+    def test_anomaly_detection_fetch_historical_data_apdex_alert(self):
+        # TODO generate whatever apdex data is
+        # store a transaction event
+        # apply the apdex formula(?)
+        event_data = load_data("transaction")
+        event_data["timestamp"] = iso_format(self.time_1_dt)
+        event_data["start_timestamp"] = iso_format(self.time_1_dt)
+        event_data["event_id"] = "a" * 32
+        self.store_event(data=event_data, project_id=self.project.id)
+
+        alert_rule = self.create_alert_rule(
+            projects=[self.project],
+            dataset=Dataset.PerformanceMetrics,
+            name="JustAValidRule",
+            query="",
+            aggregate="apdex(300)",
+            time_window=1,
+            threshold_type=AlertRuleThresholdType.BELOW,
+            threshold_period=1,
+        )
+        snuba_query = SnubaQuery.objects.get(id=alert_rule.snuba_query_id)
+        result = fetch_historical_data(alert_rule, snuba_query, self.project)
+        assert result
+        assert {"time": int(self.time_1_ts), "count": 1} in result.data.get("data")
+        # assert {"time": int(self.time_2_ts)} in result.data.get("data")