from datetime import timedelta from unittest import mock import pytest from django.urls import reverse from sentry.testutils.cases import MetricsEnhancedPerformanceTestCase from sentry.testutils.helpers.datetime import before_now, iso_format from sentry.testutils.silo import region_silo_test pytestmark = pytest.mark.sentry_metrics @region_silo_test class OrganizationEventsStatsMetricsEnhancedPerformanceEndpointTest( MetricsEnhancedPerformanceTestCase ): endpoint = "sentry-api-0-organization-events-stats" METRIC_STRINGS = [ "foo_transaction", "d:transactions/measurements.datacenter_memory@pebibyte", ] def setUp(self): super().setUp() self.login_as(user=self.user) self.day_ago = before_now(days=1).replace(hour=10, minute=0, second=0, microsecond=0) self.DEFAULT_METRIC_TIMESTAMP = self.day_ago self.url = reverse( "sentry-api-0-organization-events-stats", kwargs={"organization_slug": self.project.organization.slug}, ) self.features = { "organizations:performance-use-metrics": True, } def do_request(self, data, url=None, features=None): if features is None: features = {"organizations:discover-basic": True} features.update(self.features) with self.feature(features): return self.client.get(self.url if url is None else url, data=data, format="json") # These throughput tests should roughly match the ones in OrganizationEventsStatsEndpointTest def test_throughput_epm_hour_rollup(self): # Each of these denotes how many events to create in each hour event_counts = [6, 0, 6, 3, 0, 3] for hour, count in enumerate(event_counts): for minute in range(count): self.store_transaction_metric( 1, timestamp=self.day_ago + timedelta(hours=hour, minutes=minute) ) for axis in ["epm()", "tpm()"]: response = self.do_request( data={ "start": iso_format(self.day_ago), "end": iso_format(self.day_ago + timedelta(hours=6)), "interval": "1h", "yAxis": axis, "project": self.project.id, "dataset": "metricsEnhanced", }, ) assert response.status_code == 200, response.content data = response.data["data"] assert len(data) == 6 assert response.data["isMetricsData"] rows = data[0:6] for test in zip(event_counts, rows): assert test[1][1][0]["count"] == test[0] / (3600.0 / 60.0) def test_throughput_epm_day_rollup(self): # Each of these denotes how many events to create in each minute event_counts = [6, 0, 6, 3, 0, 3] for hour, count in enumerate(event_counts): for minute in range(count): self.store_transaction_metric( 1, timestamp=self.day_ago + timedelta(hours=hour, minutes=minute) ) for axis in ["epm()", "tpm()"]: response = self.do_request( data={ "start": iso_format(self.day_ago), "end": iso_format(self.day_ago + timedelta(hours=24)), "interval": "24h", "yAxis": axis, "project": self.project.id, "dataset": "metricsEnhanced", }, ) assert response.status_code == 200, response.content data = response.data["data"] assert len(data) == 2 assert response.data["isMetricsData"] assert data[0][1][0]["count"] == sum(event_counts) / (86400.0 / 60.0) def test_throughput_epm_hour_rollup_offset_of_hour(self): # Each of these denotes how many events to create in each hour event_counts = [6, 0, 6, 3, 0, 3] for hour, count in enumerate(event_counts): for minute in range(count): self.store_transaction_metric( 1, timestamp=self.day_ago + timedelta(hours=hour, minutes=minute + 30) ) for axis in ["tpm()", "epm()"]: response = self.do_request( data={ "start": iso_format(self.day_ago + timedelta(minutes=30)), "end": iso_format(self.day_ago + timedelta(hours=6, minutes=30)), "interval": "1h", "yAxis": axis, "project": self.project.id, "dataset": "metricsEnhanced", }, ) assert response.status_code == 200, response.content data = response.data["data"] assert len(data) == 6 assert response.data["isMetricsData"] rows = data[0:6] for test in zip(event_counts, rows): assert test[1][1][0]["count"] == test[0] / (3600.0 / 60.0) def test_throughput_eps_minute_rollup(self): # Each of these denotes how many events to create in each minute event_counts = [6, 0, 6, 3, 0, 3] for minute, count in enumerate(event_counts): for second in range(count): self.store_transaction_metric( 1, timestamp=self.day_ago + timedelta(minutes=minute, seconds=second) ) for axis in ["eps()", "tps()"]: response = self.do_request( data={ "start": iso_format(self.day_ago), "end": iso_format(self.day_ago + timedelta(minutes=6)), "interval": "1m", "yAxis": axis, "project": self.project.id, "dataset": "metricsEnhanced", }, ) assert response.status_code == 200, response.content data = response.data["data"] assert len(data) == 6 assert response.data["isMetricsData"] rows = data[0:6] for test in zip(event_counts, rows): assert test[1][1][0]["count"] == test[0] / 60.0 def test_failure_rate(self): for hour in range(6): timestamp = self.day_ago + timedelta(hours=hour, minutes=30) self.store_transaction_metric(1, tags={"transaction.status": "ok"}, timestamp=timestamp) if hour < 3: self.store_transaction_metric( 1, tags={"transaction.status": "internal_error"}, timestamp=timestamp ) response = self.do_request( data={ "start": iso_format(self.day_ago), "end": iso_format(self.day_ago + timedelta(hours=6)), "interval": "1h", "yAxis": ["failure_rate()"], "project": self.project.id, "dataset": "metricsEnhanced", }, ) assert response.status_code == 200, response.content data = response.data["data"] assert len(data) == 6 assert response.data["isMetricsData"] assert [attrs for time, attrs in response.data["data"]] == [ [{"count": 0.5}], [{"count": 0.5}], [{"count": 0.5}], [{"count": 0}], [{"count": 0}], [{"count": 0}], ] def test_percentiles_multi_axis(self): for hour in range(6): timestamp = self.day_ago + timedelta(hours=hour, minutes=30) self.store_transaction_metric(111, timestamp=timestamp) self.store_transaction_metric(222, metric="measurements.lcp", timestamp=timestamp) response = self.do_request( data={ "start": iso_format(self.day_ago), "end": iso_format(self.day_ago + timedelta(hours=6)), "interval": "1h", "yAxis": ["p75(measurements.lcp)", "p75(transaction.duration)"], "project": self.project.id, "dataset": "metricsEnhanced", }, ) assert response.status_code == 200, response.content lcp = response.data["p75(measurements.lcp)"] duration = response.data["p75(transaction.duration)"] assert len(duration["data"]) == 6 assert duration["isMetricsData"] assert len(lcp["data"]) == 6 assert lcp["isMetricsData"] for item in duration["data"]: assert item[1][0]["count"] == 111 for item in lcp["data"]: assert item[1][0]["count"] == 222 @mock.patch("sentry.snuba.metrics_enhanced_performance.timeseries_query", return_value={}) def test_multiple_yaxis_only_one_query(self, mock_query): self.do_request( data={ "project": self.project.id, "start": iso_format(self.day_ago), "end": iso_format(self.day_ago + timedelta(hours=2)), "interval": "1h", "yAxis": ["epm()", "eps()", "tpm()", "p50(transaction.duration)"], "dataset": "metricsEnhanced", }, ) assert mock_query.call_count == 1 def test_aggregate_function_user_count(self): self.store_transaction_metric( 1, metric="user", timestamp=self.day_ago + timedelta(minutes=30) ) self.store_transaction_metric( 1, metric="user", timestamp=self.day_ago + timedelta(hours=1, minutes=30) ) response = self.do_request( data={ "start": iso_format(self.day_ago), "end": iso_format(self.day_ago + timedelta(hours=2)), "interval": "1h", "yAxis": "count_unique(user)", "dataset": "metricsEnhanced", }, ) assert response.status_code == 200, response.content assert response.data["isMetricsData"] assert [attrs for time, attrs in response.data["data"]] == [[{"count": 1}], [{"count": 1}]] meta = response.data["meta"] assert meta["isMetricsData"] == response.data["isMetricsData"] def test_non_mep_query_fallsback(self): def get_mep(query): response = self.do_request( data={ "project": self.project.id, "start": iso_format(self.day_ago), "end": iso_format(self.day_ago + timedelta(hours=2)), "interval": "1h", "query": query, "yAxis": ["epm()"], "dataset": "metricsEnhanced", }, ) assert response.status_code == 200, response.content return response.data["isMetricsData"] assert get_mep(""), "empty query" assert get_mep("event.type:transaction"), "event type transaction" assert not get_mep("event.type:error"), "event type error" assert not get_mep("transaction.duration:<15min"), "outlier filter" assert get_mep("epm():>0.01"), "throughput filter" assert not get_mep( "event.type:transaction OR event.type:error" ), "boolean with non-mep filter" assert get_mep( "event.type:transaction OR transaction:foo_transaction" ), "boolean with mep filter" def test_having_condition_with_preventing_aggregates(self): response = self.do_request( data={ "project": self.project.id, "start": iso_format(self.day_ago), "end": iso_format(self.day_ago + timedelta(hours=2)), "interval": "1h", "query": "p95():<5s", "yAxis": ["epm()"], "dataset": "metricsEnhanced", "preventMetricAggregates": "1", }, ) assert response.status_code == 200, response.content assert not response.data["isMetricsData"] meta = response.data["meta"] assert meta["isMetricsData"] == response.data["isMetricsData"] def test_explicit_not_mep(self): response = self.do_request( data={ "project": self.project.id, "start": iso_format(self.day_ago), "end": iso_format(self.day_ago + timedelta(hours=2)), "interval": "1h", # Should be a mep able query "query": "", "yAxis": ["epm()"], "metricsEnhanced": "0", }, ) assert response.status_code == 200, response.content assert not response.data["isMetricsData"] meta = response.data["meta"] assert meta["isMetricsData"] == response.data["isMetricsData"] def test_sum_transaction_duration(self): self.store_transaction_metric(123, timestamp=self.day_ago + timedelta(minutes=30)) self.store_transaction_metric(456, timestamp=self.day_ago + timedelta(hours=1, minutes=30)) self.store_transaction_metric(789, timestamp=self.day_ago + timedelta(hours=1, minutes=30)) response = self.do_request( data={ "start": iso_format(self.day_ago), "end": iso_format(self.day_ago + timedelta(hours=2)), "interval": "1h", "yAxis": "sum(transaction.duration)", "dataset": "metricsEnhanced", }, ) assert response.status_code == 200, response.content assert response.data["isMetricsData"] assert [attrs for time, attrs in response.data["data"]] == [ [{"count": 123}], [{"count": 1245}], ] meta = response.data["meta"] assert meta["isMetricsData"] == response.data["isMetricsData"] assert meta["fields"] == {"time": "date", "sum_transaction_duration": "duration"} assert meta["units"] == {"time": None, "sum_transaction_duration": "millisecond"} def test_custom_measurement(self): self.store_transaction_metric( 123, metric="measurements.bytes_transfered", internal_metric="d:transactions/measurements.datacenter_memory@pebibyte", entity="metrics_distributions", tags={"transaction": "foo_transaction"}, timestamp=self.day_ago + timedelta(minutes=30), ) self.store_transaction_metric( 456, metric="measurements.bytes_transfered", internal_metric="d:transactions/measurements.datacenter_memory@pebibyte", entity="metrics_distributions", tags={"transaction": "foo_transaction"}, timestamp=self.day_ago + timedelta(hours=1, minutes=30), ) self.store_transaction_metric( 789, metric="measurements.bytes_transfered", internal_metric="d:transactions/measurements.datacenter_memory@pebibyte", entity="metrics_distributions", tags={"transaction": "foo_transaction"}, timestamp=self.day_ago + timedelta(hours=1, minutes=30), ) response = self.do_request( data={ "start": iso_format(self.day_ago), "end": iso_format(self.day_ago + timedelta(hours=2)), "interval": "1h", "yAxis": "sum(measurements.datacenter_memory)", "dataset": "metricsEnhanced", }, ) assert response.status_code == 200, response.content assert response.data["isMetricsData"] assert [attrs for time, attrs in response.data["data"]] == [ [{"count": 123}], [{"count": 1245}], ] meta = response.data["meta"] assert meta["isMetricsData"] == response.data["isMetricsData"] assert meta["fields"] == {"time": "date", "sum_measurements_datacenter_memory": "size"} assert meta["units"] == {"time": None, "sum_measurements_datacenter_memory": "pebibyte"} def test_does_not_fallback_if_custom_metric_is_out_of_request_time_range(self): self.store_transaction_metric( 123, timestamp=self.day_ago + timedelta(hours=1), internal_metric="d:transactions/measurements.custom@kibibyte", entity="metrics_distributions", ) response = self.do_request( data={ "start": iso_format(self.day_ago), "end": iso_format(self.day_ago + timedelta(hours=2)), "interval": "1h", "yAxis": "p99(measurements.custom)", "dataset": "metricsEnhanced", }, ) meta = response.data["meta"] assert response.status_code == 200, response.content assert response.data["isMetricsData"] assert meta["isMetricsData"] assert meta["fields"] == {"time": "date", "p99_measurements_custom": "size"} assert meta["units"] == {"time": None, "p99_measurements_custom": "kibibyte"} def test_multi_yaxis_custom_measurement(self): self.store_transaction_metric( 123, metric="measurements.bytes_transfered", internal_metric="d:transactions/measurements.datacenter_memory@pebibyte", entity="metrics_distributions", tags={"transaction": "foo_transaction"}, timestamp=self.day_ago + timedelta(minutes=30), ) self.store_transaction_metric( 456, metric="measurements.bytes_transfered", internal_metric="d:transactions/measurements.datacenter_memory@pebibyte", entity="metrics_distributions", tags={"transaction": "foo_transaction"}, timestamp=self.day_ago + timedelta(hours=1, minutes=30), ) self.store_transaction_metric( 789, metric="measurements.bytes_transfered", internal_metric="d:transactions/measurements.datacenter_memory@pebibyte", entity="metrics_distributions", tags={"transaction": "foo_transaction"}, timestamp=self.day_ago + timedelta(hours=1, minutes=30), ) response = self.do_request( data={ "start": iso_format(self.day_ago), "end": iso_format(self.day_ago + timedelta(hours=2)), "interval": "1h", "yAxis": [ "sum(measurements.datacenter_memory)", "p50(measurements.datacenter_memory)", ], "dataset": "metricsEnhanced", }, ) assert response.status_code == 200, response.content sum_data = response.data["sum(measurements.datacenter_memory)"] p50_data = response.data["p50(measurements.datacenter_memory)"] assert sum_data["isMetricsData"] assert p50_data["isMetricsData"] assert [attrs for time, attrs in sum_data["data"]] == [ [{"count": 123}], [{"count": 1245}], ] assert [attrs for time, attrs in p50_data["data"]] == [ [{"count": 123}], [{"count": 622.5}], ] sum_meta = sum_data["meta"] assert sum_meta["isMetricsData"] == sum_data["isMetricsData"] assert sum_meta["fields"] == { "time": "date", "sum_measurements_datacenter_memory": "size", "p50_measurements_datacenter_memory": "size", } assert sum_meta["units"] == { "time": None, "sum_measurements_datacenter_memory": "pebibyte", "p50_measurements_datacenter_memory": "pebibyte", } p50_meta = p50_data["meta"] assert p50_meta["isMetricsData"] == p50_data["isMetricsData"] assert p50_meta["fields"] == { "time": "date", "sum_measurements_datacenter_memory": "size", "p50_measurements_datacenter_memory": "size", } assert p50_meta["units"] == { "time": None, "sum_measurements_datacenter_memory": "pebibyte", "p50_measurements_datacenter_memory": "pebibyte", } def test_dataset_metrics_does_not_fallback(self): self.store_transaction_metric(123, timestamp=self.day_ago + timedelta(minutes=30)) self.store_transaction_metric(456, timestamp=self.day_ago + timedelta(hours=1, minutes=30)) self.store_transaction_metric(789, timestamp=self.day_ago + timedelta(hours=1, minutes=30)) response = self.do_request( data={ "start": iso_format(self.day_ago), "end": iso_format(self.day_ago + timedelta(hours=2)), "interval": "1h", "query": "transaction.duration:<5s", "yAxis": "sum(transaction.duration)", "dataset": "metrics", }, ) assert response.status_code == 400, response.content def test_title_filter(self): self.store_transaction_metric( 123, tags={"transaction": "foo_transaction"}, timestamp=self.day_ago + timedelta(minutes=30), ) response = self.do_request( data={ "start": iso_format(self.day_ago), "end": iso_format(self.day_ago + timedelta(hours=2)), "interval": "1h", "query": "title:foo_transaction", "yAxis": [ "sum(transaction.duration)", ], "dataset": "metricsEnhanced", }, ) assert response.status_code == 200, response.content data = response.data["data"] assert [attrs for time, attrs in data] == [ [{"count": 123}], [{"count": 0}], ] def test_custom_performance_metric_meta_contains_field_and_unit_data(self): self.store_transaction_metric( 123, timestamp=self.day_ago + timedelta(hours=1), internal_metric="d:transactions/measurements.custom@kibibyte", entity="metrics_distributions", ) response = self.do_request( data={ "start": iso_format(self.day_ago), "end": iso_format(self.day_ago + timedelta(hours=2)), "interval": "1h", "yAxis": "p99(measurements.custom)", "query": "", }, ) assert response.status_code == 200 meta = response.data["meta"] assert meta["fields"] == {"time": "date", "p99_measurements_custom": "size"} assert meta["units"] == {"time": None, "p99_measurements_custom": "kibibyte"} def test_multi_series_custom_performance_metric_meta_contains_field_and_unit_data(self): self.store_transaction_metric( 123, timestamp=self.day_ago + timedelta(hours=1), internal_metric="d:transactions/measurements.custom@kibibyte", entity="metrics_distributions", ) self.store_transaction_metric( 123, timestamp=self.day_ago + timedelta(hours=1), internal_metric="d:transactions/measurements.another.custom@pebibyte", entity="metrics_distributions", ) response = self.do_request( data={ "start": iso_format(self.day_ago), "end": iso_format(self.day_ago + timedelta(hours=2)), "interval": "1h", "yAxis": [ "p95(measurements.custom)", "p99(measurements.custom)", "p99(measurements.another.custom)", ], "query": "", }, ) assert response.status_code == 200 meta = response.data["p95(measurements.custom)"]["meta"] assert meta["fields"] == { "time": "date", "p95_measurements_custom": "size", "p99_measurements_custom": "size", "p99_measurements_another_custom": "size", } assert meta["units"] == { "time": None, "p95_measurements_custom": "kibibyte", "p99_measurements_custom": "kibibyte", "p99_measurements_another_custom": "pebibyte", } assert meta == response.data["p99(measurements.custom)"]["meta"] assert meta == response.data["p99(measurements.another.custom)"]["meta"] class OrganizationEventsStatsMetricsEnhancedPerformanceEndpointTestWithMetricLayer( OrganizationEventsStatsMetricsEnhancedPerformanceEndpointTest ): def setUp(self): super().setUp() self.features["organizations:use-metrics-layer"] = True