From 1b53a3408b71220dc6a41f95acdc21ca7d1a59c1 Mon Sep 17 00:00:00 2001
From: Evan Purkhiser <evanpurkhiser@gmail.com>
Date: Thu, 24 Oct 2024 17:40:53 -0400
Subject: [PATCH] ref(crons): Acocunt for math edge cases in
 _evaluate_tick_decision (#79717)

---
 src/sentry/monitors/clock_dispatch.py        |  9 ++-
 tests/sentry/monitors/test_clock_dispatch.py | 73 ++++++++++++++++++++
 2 files changed, 79 insertions(+), 3 deletions(-)

diff --git a/src/sentry/monitors/clock_dispatch.py b/src/sentry/monitors/clock_dispatch.py
index 765fa8fe21db1f..1639dce673cd8b 100644
--- a/src/sentry/monitors/clock_dispatch.py
+++ b/src/sentry/monitors/clock_dispatch.py
@@ -142,8 +142,8 @@ def _evaluate_tick_decision(tick: datetime):
     if past_minute_volume is None:
         return
 
-    # Can't make any decisions if we don't have historic data
-    if len(historic_volume) == 0:
+    # We need AT LEAST two data points to calculate standard deviation
+    if len(historic_volume) < 2:
         return
 
     # Record some statistics about the past_minute_volume volume in comparison
@@ -157,7 +157,10 @@ def _evaluate_tick_decision(tick: datetime):
     # Calculate the z-score of our past minutes volume in comparison to the
     # historic volume data. The z-score is measured in terms of standard
     # deviations from the mean
-    z_score = (past_minute_volume - historic_mean) / historic_stdev
+    if historic_stdev != 0.0:
+        z_score = (past_minute_volume - historic_mean) / historic_stdev
+    else:
+        z_score = 0.0
 
     # Percentage deviation from the mean for our past minutes volume
     pct_deviation = (abs(past_minute_volume - historic_mean) / historic_mean) * 100
diff --git a/tests/sentry/monitors/test_clock_dispatch.py b/tests/sentry/monitors/test_clock_dispatch.py
index 0f4b7bc5a5ad30..f53855de55b8d5 100644
--- a/tests/sentry/monitors/test_clock_dispatch.py
+++ b/tests/sentry/monitors/test_clock_dispatch.py
@@ -323,3 +323,76 @@ def test_evaluate_tick_decision_volume_drop(metrics, logger):
         52.0,
         sample_rate=1.0,
     )
+
+
+@mock.patch("sentry.monitors.clock_dispatch.logger")
+@mock.patch("sentry.monitors.clock_dispatch.metrics")
+@override_options({"crons.tick_volume_anomaly_detection": True})
+def test_evaluate_tick_decision_low_history(metrics, logger):
+    tick = timezone.now().replace(second=0, microsecond=0)
+
+    # This is the timestamp we're looking at just after the tick
+    past_ts = tick - timedelta(minutes=1)
+
+    # Only add one historic value (and the current value being evaluated)
+    update_check_in_volume([past_ts - MONITOR_VOLUME_DECISION_STEP] * 900)
+    update_check_in_volume([past_ts] * 900)
+
+    _evaluate_tick_decision(tick)
+
+    # We should do nothing because there was not enough daata to make any
+    # calculation
+    assert not logger.info.called
+    assert not metrics.gauge.called
+
+
+@mock.patch("sentry.monitors.clock_dispatch.logger")
+@mock.patch("sentry.monitors.clock_dispatch.metrics")
+@override_options({"crons.tick_volume_anomaly_detection": True})
+def test_evaluate_tick_decision_uniform(metrics, logger):
+    tick = timezone.now().replace(second=0, microsecond=0)
+
+    # This is the timestamp we're looking at just after the tick
+    past_ts = tick - timedelta(minutes=1)
+
+    # Fill with a uniform history (all values the same). This will give us a
+    # standard deviation of 0. In this case the z-value needs to be computed
+    # differently.
+    fill_historic_volume(
+        start=past_ts - MONITOR_VOLUME_DECISION_STEP,
+        length=MONITOR_VOLUME_RETENTION,
+        step=MONITOR_VOLUME_DECISION_STEP,
+        counts=[1000],
+    )
+    update_check_in_volume([past_ts] * 1000)
+
+    _evaluate_tick_decision(tick)
+
+    logger.info.assert_called_with(
+        "monitors.clock_dispatch.volume_history",
+        extra={
+            "reference_datetime": str(tick),
+            "evaluation_minute": past_ts.strftime("%H:%M"),
+            "history_count": 30,
+            "z_score": 0.0,
+            "pct_deviation": 0.0,
+            "historic_mean": 1000,
+            "historic_stdev": 0.0,
+        },
+    )
+
+    metrics.gauge.assert_any_call(
+        "monitors.task.volume_history.count",
+        30,
+        sample_rate=1.0,
+    )
+    metrics.gauge.assert_any_call(
+        "monitors.task.volume_history.z_score",
+        0.0,
+        sample_rate=1.0,
+    )
+    metrics.gauge.assert_any_call(
+        "monitors.task.volume_history.pct_deviation",
+        0.0,
+        sample_rate=1.0,
+    )