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ci: skip the reliably-failing tracer flare cleanup check #15553
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brettlangdon
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minor thoughts/concerns over skipping the cleanup check, but not intending to block fixing up the flakiness short term.
| if self.prepare_called: | ||
| assert self._get_handler() is None, "File handler was not removed" | ||
| # XXX this fails quite often in CI for unknown reason | ||
| # if self.prepare_called: |
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are we leaking state between tests at all?
if we don't have this check, are the tests going to fail for other reasons?
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e.g. should we have a if self._get_handler(): self._remove_handlers() ?
or maybe "both", we have a tear down which will always clean up the handlers, but we still allow individual tests to fail so we can be sure we are isolating state between tests and it only fails when it does indeed not clean up the handlers?
Bootstrap import analysisComparison of import times between this PR and base. SummaryThe average import time from this PR is: 267 ± 4 ms. The average import time from base is: 270 ± 4 ms. The import time difference between this PR and base is: -2.4 ± 0.2 ms. Import time breakdownThe following import paths have shrunk:
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Performance SLOsComparing candidate emmett.butler/skip-flare-cleanup-check (e0757f8) with baseline main (d238908) 📈 Performance Regressions (2 suites)📈 iastaspectsospath - 24/24✅ ospathbasename_aspectTime: ✅ 5.194µs (SLO: <10.000µs 📉 -48.1%) vs baseline: 📈 +27.1% Memory: ✅ 40.324MB (SLO: <41.000MB 🟡 -1.6%) vs baseline: +4.9% ✅ ospathbasename_noaspectTime: ✅ 1.083µs (SLO: <10.000µs 📉 -89.2%) vs baseline: +0.8% Memory: ✅ 40.128MB (SLO: <41.000MB -2.1%) vs baseline: +4.6% ✅ ospathjoin_aspectTime: ✅ 6.124µs (SLO: <10.000µs 📉 -38.8%) vs baseline: -0.6% Memory: ✅ 40.088MB (SLO: <41.000MB -2.2%) vs baseline: +4.5% ✅ ospathjoin_noaspectTime: ✅ 2.290µs (SLO: <10.000µs 📉 -77.1%) vs baseline: +0.6% Memory: ✅ 40.167MB (SLO: <41.000MB -2.0%) vs baseline: +4.9% ✅ ospathnormcase_aspectTime: ✅ 3.433µs (SLO: <10.000µs 📉 -65.7%) vs baseline: +0.3% Memory: ✅ 40.246MB (SLO: <41.000MB 🟡 -1.8%) vs baseline: +5.0% ✅ ospathnormcase_noaspectTime: ✅ 0.578µs (SLO: <10.000µs 📉 -94.2%) vs baseline: +1.0% Memory: ✅ 40.069MB (SLO: <41.000MB -2.3%) vs baseline: +4.5% ✅ ospathsplit_aspectTime: ✅ 4.767µs (SLO: <10.000µs 📉 -52.3%) vs baseline: -0.7% Memory: ✅ 40.187MB (SLO: <41.000MB 🟡 -2.0%) vs baseline: +4.8% ✅ ospathsplit_noaspectTime: ✅ 1.596µs (SLO: <10.000µs 📉 -84.0%) vs baseline: +0.8% Memory: ✅ 40.305MB (SLO: <41.000MB 🟡 -1.7%) vs baseline: +5.1% ✅ ospathsplitdrive_aspectTime: ✅ 3.649µs (SLO: <10.000µs 📉 -63.5%) vs baseline: -1.1% Memory: ✅ 40.442MB (SLO: <41.000MB 🟡 -1.4%) vs baseline: +5.1% ✅ ospathsplitdrive_noaspectTime: ✅ 0.696µs (SLO: <10.000µs 📉 -93.0%) vs baseline: -0.2% Memory: ✅ 40.324MB (SLO: <41.000MB 🟡 -1.6%) vs baseline: +5.1% ✅ ospathsplitext_aspectTime: ✅ 4.490µs (SLO: <10.000µs 📉 -55.1%) vs baseline: -1.1% Memory: ✅ 40.403MB (SLO: <41.000MB 🟡 -1.5%) vs baseline: +5.6% ✅ ospathsplitext_noaspectTime: ✅ 1.389µs (SLO: <10.000µs 📉 -86.1%) vs baseline: +0.7% Memory: ✅ 40.265MB (SLO: <41.000MB 🟡 -1.8%) vs baseline: +4.8% 📈 telemetryaddmetric - 30/30✅ 1-count-metric-1-timesTime: ✅ 3.390µs (SLO: <20.000µs 📉 -83.1%) vs baseline: 📈 +15.1% Memory: ✅ 34.682MB (SLO: <35.500MB -2.3%) vs baseline: +4.7% ✅ 1-count-metrics-100-timesTime: ✅ 201.118µs (SLO: <220.000µs -8.6%) vs baseline: +0.1% Memory: ✅ 34.859MB (SLO: <35.500MB 🟡 -1.8%) vs baseline: +4.6% ✅ 1-distribution-metric-1-timesTime: ✅ 3.265µs (SLO: <20.000µs 📉 -83.7%) vs baseline: -0.3% Memory: ✅ 34.800MB (SLO: <35.500MB 🟡 -2.0%) vs baseline: +4.1% ✅ 1-distribution-metrics-100-timesTime: ✅ 214.653µs (SLO: <230.000µs -6.7%) vs baseline: -1.1% Memory: ✅ 34.859MB (SLO: <35.500MB 🟡 -1.8%) vs baseline: +4.0% ✅ 1-gauge-metric-1-timesTime: ✅ 2.181µs (SLO: <20.000µs 📉 -89.1%) vs baseline: -0.5% Memory: ✅ 34.819MB (SLO: <35.500MB 🟡 -1.9%) vs baseline: +5.2% ✅ 1-gauge-metrics-100-timesTime: ✅ 135.774µs (SLO: <150.000µs -9.5%) vs baseline: -0.5% Memory: ✅ 34.721MB (SLO: <35.500MB -2.2%) vs baseline: +4.4% ✅ 1-rate-metric-1-timesTime: ✅ 3.062µs (SLO: <20.000µs 📉 -84.7%) vs baseline: -0.6% Memory: ✅ 34.780MB (SLO: <35.500MB -2.0%) vs baseline: +4.8% ✅ 1-rate-metrics-100-timesTime: ✅ 215.096µs (SLO: <250.000µs 📉 -14.0%) vs baseline: +0.2% Memory: ✅ 34.800MB (SLO: <35.500MB 🟡 -2.0%) vs baseline: +5.2% ✅ 100-count-metrics-100-timesTime: ✅ 20.248ms (SLO: <22.000ms -8.0%) vs baseline: -0.9% Memory: ✅ 34.721MB (SLO: <35.500MB -2.2%) vs baseline: +4.8% ✅ 100-distribution-metrics-100-timesTime: ✅ 2.256ms (SLO: <2.550ms 📉 -11.5%) vs baseline: -0.6% Memory: ✅ 34.721MB (SLO: <35.500MB -2.2%) vs baseline: +3.7% ✅ 100-gauge-metrics-100-timesTime: ✅ 1.401ms (SLO: <1.550ms -9.6%) vs baseline: +0.2% Memory: ✅ 34.800MB (SLO: <35.500MB 🟡 -2.0%) vs baseline: +4.9% ✅ 100-rate-metrics-100-timesTime: ✅ 2.207ms (SLO: <2.550ms 📉 -13.5%) vs baseline: +0.2% Memory: ✅ 34.800MB (SLO: <35.500MB 🟡 -2.0%) vs baseline: +5.0% ✅ flush-1-metricTime: ✅ 4.615µs (SLO: <20.000µs 📉 -76.9%) vs baseline: -0.2% Memory: ✅ 35.075MB (SLO: <35.500MB 🟡 -1.2%) vs baseline: +4.7% ✅ flush-100-metricsTime: ✅ 176.129µs (SLO: <250.000µs 📉 -29.5%) vs baseline: +0.3% Memory: ✅ 35.095MB (SLO: <35.500MB 🟡 -1.1%) vs baseline: +4.9% ✅ flush-1000-metricsTime: ✅ 2.200ms (SLO: <2.500ms 📉 -12.0%) vs baseline: +0.9% Memory: ✅ 35.920MB (SLO: <36.500MB 🟡 -1.6%) vs baseline: +4.9% 🟡 Near SLO Breach (17 suites)🟡 coreapiscenario - 10/10 (1 unstable)
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This change skips a check that reliably fails in CI but not locally (example https://gitlab.ddbuild.io/DataDog/apm-reliability/dd-trace-py/-/jobs/1276781621). There have been a few attempts to fix these failures in other ways (see #15203 (comment)).