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chore(anomaly detection): too many instances of test is run in parallel during deployment, skipping test for now #2166

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Seems like there is some issue with how test parallelization is setup. One test is getting executed 100+ times in parallel and this seems to make the tests run very slow, resulting in a timeout.

@ram-senth ram-senth requested a review from a team as a code owner March 14, 2025 17:52
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sentry-autofix bot commented Mar 14, 2025

✅ Sentry found no issues in your recent changes ✅

@ram-senth ram-senth force-pushed the anomaly-detection/flaky-test branch from 4384a46 to bdc87cc Compare March 14, 2025 18:31
@ram-senth ram-senth force-pushed the anomaly-detection/flaky-test branch from bdc87cc to 21be9ac Compare March 14, 2025 18:50
Comment on lines +538 to +571
# TODO: Enable this test once we have a way to run tests in parallel without causing multiple parallel runs
# def test_detect_anomalies_combo_large_current(self):
# config = AnomalyDetectionConfig(
# time_period=15, sensitivity="low", direction="both", expected_seasonality="auto"
# )

# loaded_synthetic_data = convert_synthetic_ts(
# "tests/seer/anomaly_detection/test_data/synthetic_series", as_ts_datatype=True
# )
# ts_history = loaded_synthetic_data.timeseries[0]
# last_history_timestamp = ts_history[-1].timestamp
# last_history_value = ts_history[-1].value
# n = 700 # should be greater than 7 days * 24 hours * 60 minutes * 15 minutes = 672

# # Generate new observation window of n points which are the same as the last point
# ts_current = []
# for j in range(1, n + 1):
# ts_current.append(
# TimeSeriesPoint(
# timestamp=last_history_timestamp + config.time_period * 60 * j,
# value=last_history_value,
# )
# )

# context = TimeSeriesWithHistory(history=ts_history, current=ts_current)

# request = DetectAnomaliesRequest(
# organization_id=1, project_id=1, config=config, context=context
# )

# response = AnomalyDetection().detect_anomalies(request=request, time_budget_ms=5000)

# assert isinstance(response, DetectAnomaliesResponse)
# assert isinstance(response.timeseries, list)
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I think you can just pass in a @pytest.mark.skip(reason="<reason>") to mark it rather than commenting it out.
https://stackoverflow.com/questions/38442897/how-do-i-disable-a-test-using-pytest

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2 participants