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feat(profiling): port tracking asyncio.wait'ed Tasks #15338
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Bootstrap import analysisComparison of import times between this PR and base. SummaryThe average import time from this PR is: 258 ± 7 ms. The average import time from base is: 280 ± 10 ms. The import time difference between this PR and base is: -19.5 ± 0.4 ms. Import time breakdownThe following import paths have shrunk:
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Performance SLOsComparing candidate kowalski/port-asyncio-wait-tracking (c36130a) with baseline main (2cc3c8b) 🟡 Near SLO Breach (3 suites)🟡 flasksimple - 18/18✅ appsec-getTime: ✅ 4.579ms (SLO: <4.750ms -3.6%) vs baseline: -0.2% Memory: ✅ 63.956MB (SLO: <66.500MB -3.8%) vs baseline: +4.8% ✅ appsec-postTime: ✅ 6.616ms (SLO: <6.750ms 🟡 -2.0%) vs baseline: -0.2% Memory: ✅ 64.369MB (SLO: <66.500MB -3.2%) vs baseline: +4.8% ✅ appsec-telemetryTime: ✅ 4.589ms (SLO: <4.750ms -3.4%) vs baseline: +0.1% Memory: ✅ 64.029MB (SLO: <66.500MB -3.7%) vs baseline: +4.9% ✅ debuggerTime: ✅ 1.854ms (SLO: <2.000ms -7.3%) vs baseline: -0.1% Memory: ✅ 47.866MB (SLO: <49.500MB -3.3%) vs baseline: +4.8% ✅ iast-getTime: ✅ 1.857ms (SLO: <2.000ms -7.1%) vs baseline: -0.2% Memory: ✅ 44.562MB (SLO: <49.000MB -9.1%) vs baseline: +5.2% ✅ profilerTime: ✅ 1.925ms (SLO: <2.100ms -8.3%) vs baseline: +0.2% Memory: ✅ 48.442MB (SLO: <50.000MB -3.1%) vs baseline: +4.7% ✅ resource-renamingTime: ✅ 3.376ms (SLO: <3.650ms -7.5%) vs baseline: +0.2% Memory: ✅ 54.693MB (SLO: <56.000MB -2.3%) vs baseline: +4.8% ✅ tracerTime: ✅ 3.365ms (SLO: <3.650ms -7.8%) vs baseline: +0.2% Memory: ✅ 54.513MB (SLO: <56.500MB -3.5%) vs baseline: +4.6% ✅ tracer-nativeTime: ✅ 3.359ms (SLO: <3.650ms -8.0%) vs baseline: ~same Memory: ✅ 54.559MB (SLO: <60.000MB -9.1%) vs baseline: +4.7% 🟡 otelspan - 22/22✅ add-eventTime: ✅ 38.601ms (SLO: <47.150ms 📉 -18.1%) vs baseline: +0.3% Memory: ✅ 38.993MB (SLO: <47.000MB 📉 -17.0%) vs baseline: +4.8% ✅ add-metricsTime: ✅ 256.542ms (SLO: <344.800ms 📉 -25.6%) vs baseline: +0.6% Memory: ✅ 43.275MB (SLO: <47.500MB -8.9%) vs baseline: +4.9% ✅ add-tagsTime: ✅ 315.441ms (SLO: <321.000ms 🟡 -1.7%) vs baseline: -0.1% Memory: ✅ 43.353MB (SLO: <47.500MB -8.7%) vs baseline: +5.1% ✅ get-contextTime: ✅ 78.976ms (SLO: <92.350ms 📉 -14.5%) vs baseline: +0.5% Memory: ✅ 39.257MB (SLO: <46.500MB 📉 -15.6%) vs baseline: +4.7% ✅ is-recordingTime: ✅ 36.204ms (SLO: <44.500ms 📉 -18.6%) vs baseline: +1.0% Memory: ✅ 38.822MB (SLO: <47.500MB 📉 -18.3%) vs baseline: +4.5% ✅ record-exceptionTime: ✅ 57.161ms (SLO: <67.650ms 📉 -15.5%) vs baseline: +0.3% Memory: ✅ 39.360MB (SLO: <47.000MB 📉 -16.3%) vs baseline: +5.0% ✅ set-statusTime: ✅ 42.443ms (SLO: <50.400ms 📉 -15.8%) vs baseline: +0.3% Memory: ✅ 38.787MB (SLO: <47.000MB 📉 -17.5%) vs baseline: +5.0% ✅ startTime: ✅ 36.096ms (SLO: <43.450ms 📉 -16.9%) vs baseline: +2.6% Memory: ✅ 38.793MB (SLO: <47.000MB 📉 -17.5%) vs baseline: +4.6% ✅ start-finishTime: ✅ 82.169ms (SLO: <88.000ms -6.6%) vs baseline: +0.5% Memory: ✅ 36.608MB (SLO: <46.500MB 📉 -21.3%) vs baseline: +5.0% ✅ start-finish-telemetryTime: ✅ 83.385ms (SLO: <89.000ms -6.3%) vs baseline: +0.3% Memory: ✅ 36.589MB (SLO: <46.500MB 📉 -21.3%) vs baseline: +4.7% ✅ update-nameTime: ✅ 37.039ms (SLO: <45.150ms 📉 -18.0%) vs baseline: +1.0% Memory: ✅ 39.015MB (SLO: <47.000MB 📉 -17.0%) vs baseline: +5.2% 🟡 telemetryaddmetric - 30/30✅ 1-count-metric-1-timesTime: ✅ 3.140µs (SLO: <20.000µs 📉 -84.3%) vs baseline: +7.3% Memory: ✅ 34.623MB (SLO: <35.500MB -2.5%) vs baseline: +4.9% ✅ 1-count-metrics-100-timesTime: ✅ 201.279µs (SLO: <220.000µs -8.5%) vs baseline: +1.1% Memory: ✅ 34.544MB (SLO: <35.500MB -2.7%) vs baseline: +4.9% ✅ 1-distribution-metric-1-timesTime: ✅ 3.386µs (SLO: <20.000µs 📉 -83.1%) vs baseline: +2.6% Memory: ✅ 34.505MB (SLO: <35.500MB -2.8%) vs baseline: +4.7% ✅ 1-distribution-metrics-100-timesTime: ✅ 219.581µs (SLO: <220.000µs 🟡 -0.2%) vs baseline: +1.6% Memory: ✅ 34.505MB (SLO: <35.500MB -2.8%) vs baseline: +4.4% ✅ 1-gauge-metric-1-timesTime: ✅ 2.178µs (SLO: <20.000µs 📉 -89.1%) vs baseline: -0.2% Memory: ✅ 34.485MB (SLO: <35.500MB -2.9%) vs baseline: +4.6% ✅ 1-gauge-metrics-100-timesTime: ✅ 136.539µs (SLO: <150.000µs -9.0%) vs baseline: +0.2% Memory: ✅ 34.583MB (SLO: <35.500MB -2.6%) vs baseline: +4.9% ✅ 1-rate-metric-1-timesTime: ✅ 3.192µs (SLO: <20.000µs 📉 -84.0%) vs baseline: +4.8% Memory: ✅ 34.524MB (SLO: <35.500MB -2.7%) vs baseline: +4.9% ✅ 1-rate-metrics-100-timesTime: ✅ 213.757µs (SLO: <250.000µs 📉 -14.5%) vs baseline: +1.1% Memory: ✅ 34.505MB (SLO: <35.500MB -2.8%) vs baseline: +4.8% ✅ 100-count-metrics-100-timesTime: ✅ 19.886ms (SLO: <22.000ms -9.6%) vs baseline: -0.9% Memory: ✅ 34.564MB (SLO: <35.500MB -2.6%) vs baseline: +5.0% ✅ 100-distribution-metrics-100-timesTime: ✅ 2.278ms (SLO: <2.300ms 🟡 -0.9%) vs baseline: -0.2% Memory: ✅ 34.524MB (SLO: <35.500MB -2.7%) vs baseline: +5.0% ✅ 100-gauge-metrics-100-timesTime: ✅ 1.412ms (SLO: <1.550ms -8.9%) vs baseline: +0.8% Memory: ✅ 34.505MB (SLO: <35.500MB -2.8%) vs baseline: +4.7% ✅ 100-rate-metrics-100-timesTime: ✅ 2.185ms (SLO: <2.550ms 📉 -14.3%) vs baseline: +0.2% Memory: ✅ 34.564MB (SLO: <35.500MB -2.6%) vs baseline: +5.0% ✅ flush-1-metricTime: ✅ 4.583µs (SLO: <20.000µs 📉 -77.1%) vs baseline: ~same Memory: ✅ 34.544MB (SLO: <35.500MB -2.7%) vs baseline: +5.2% ✅ flush-100-metricsTime: ✅ 173.027µs (SLO: <250.000µs 📉 -30.8%) vs baseline: -1.9% Memory: ✅ 34.524MB (SLO: <35.500MB -2.7%) vs baseline: +4.9% ✅ flush-1000-metricsTime: ✅ 2.115ms (SLO: <2.500ms 📉 -15.4%) vs baseline: ~same Memory: ✅ 35.350MB (SLO: <36.500MB -3.2%) vs baseline: +5.0%
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Description
https://datadoghq.atlassian.net/browse/PROF-13092
As title says, we need to import some Python wrapping from Echion.
Related: #15311
Currently awaiting on https://datadoghq.atlassian.net/browse/PROF-13091 because it seems our wrapping helpers don't support coroutines properly in Python 3.13+ (or #15313 ?)