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[APMSP-1512] Add metadata headers for stats #712

Merged
merged 6 commits into from
Nov 8, 2024
Merged

[APMSP-1512] Add metadata headers for stats #712

merged 6 commits into from
Nov 8, 2024
+95 −85

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VianneyRuhlmann
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@VianneyRuhlmann VianneyRuhlmann commented Nov 5, 2024 •
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What does this PR do?

  • Add Datadog-Meta-... headers to stats
  • Add git_commit_sha to TraceExporter meta for ClientStatsPayload
  • Add interpreter_vendor to TraceExporter meta
  • Rename the version field to app_version to be more explicit

This PR can be reviewed commit-by-commit

Motivation

These headers are required by design doc

Additional Notes

Anything else we should know when reviewing?

How to test the change?

Describe here in detail how the change can be validated.

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pr-commenter bot commented Nov 6, 2024 •
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Benchmarks

Comparison

Benchmark execution time: 2024-11-08 10:44:16

Comparing candidate commit 11abb1a in PR branch vianney/data-pipeline/add-meta-headers-for-stats with baseline commit 6943925 in branch main.

Found 0 performance improvements and 0 performance regressions! Performance is the same for 51 metrics, 2 unstable metrics.

Candidate

Candidate benchmark details

Group 1

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 11abb1a 1731062019 vianney/data-pipeline/add-meta-headers-for-stats
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
benching deserializing traces from msgpack to their internal representation execution_time 1.129µs 1.196µs ± 0.026µs 1.195µs ± 0.018µs 1.217µs 1.222µs 1.224µs 1.225µs 2.51% -1.169 0.628 2.18% 0.002µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
benching deserializing traces from msgpack to their internal representation execution_time [1.192µs; 1.200µs] or [-0.302%; +0.302%] None None None

Group 2

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 11abb1a 1731062019 vianney/data-pipeline/add-meta-headers-for-stats
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
redis/obfuscate_redis_string execution_time 37.928µs 38.486µs ± 1.040µs 38.009µs ± 0.024µs 38.046µs 40.747µs 40.767µs 41.176µs 8.33% 1.707 0.938 2.70% 0.074µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
redis/obfuscate_redis_string execution_time [38.341µs; 38.630µs] or [-0.375%; +0.375%] None None None

Group 3

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 11abb1a 1731062019 vianney/data-pipeline/add-meta-headers-for-stats
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
tags/replace_trace_tags execution_time 2.647µs 2.707µs ± 0.019µs 2.711µs ± 0.005µs 2.715µs 2.741µs 2.745µs 2.752µs 1.51% -1.102 2.689 0.71% 0.001µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
tags/replace_trace_tags execution_time [2.705µs; 2.710µs] or [-0.098%; +0.098%] None None None

Group 4

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 11abb1a 1731062019 vianney/data-pipeline/add-meta-headers-for-stats
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
credit_card/is_card_number/ execution_time 4.608µs 4.621µs ± 0.002µs 4.621µs ± 0.001µs 4.622µs 4.624µs 4.625µs 4.626µs 0.12% -1.688 13.775 0.04% 0.000µs 1 200
credit_card/is_card_number/ throughput 216147496.495op/s 216399805.929op/s ± 83538.630op/s 216398279.634op/s ± 51524.070op/s 216453810.417op/s 216506013.252op/s 216543113.780op/s 217018763.900op/s 0.29% 1.703 13.898 0.04% 5907.073op/s 1 200
credit_card/is_card_number/ 3782-8224-6310-005 execution_time 90.098µs 90.889µs ± 0.347µs 90.857µs ± 0.197µs 91.064µs 91.536µs 91.943µs 92.064µs 1.33% 0.786 1.201 0.38% 0.025µs 1 200
credit_card/is_card_number/ 3782-8224-6310-005 throughput 10862063.739op/s 11002628.207op/s ± 41840.975op/s 11006366.083op/s ± 23859.493op/s 11029939.946op/s 11060238.737op/s 11090793.465op/s 11099016.546op/s 0.84% -0.757 1.146 0.38% 2958.604op/s 1 200
credit_card/is_card_number/ 378282246310005 execution_time 82.694µs 84.467µs ± 0.621µs 84.408µs ± 0.377µs 84.816µs 85.608µs 85.994µs 86.314µs 2.26% 0.277 0.357 0.73% 0.044µs 1 200
credit_card/is_card_number/ 378282246310005 throughput 11585587.996op/s 11839642.050op/s ± 86944.415op/s 11847190.556op/s ± 52949.262op/s 11894084.481op/s 11971369.947op/s 12035514.325op/s 12092733.994op/s 2.07% -0.226 0.344 0.73% 6147.899op/s 1 200
credit_card/is_card_number/37828224631 execution_time 4.606µs 4.622µs ± 0.004µs 4.622µs ± 0.001µs 4.623µs 4.625µs 4.627µs 4.663µs 0.89% 6.446 73.329 0.08% 0.000µs 1 200
credit_card/is_card_number/37828224631 throughput 214475362.440op/s 216370346.903op/s ± 172552.036op/s 216373678.142op/s ± 68982.514op/s 216451553.349op/s 216515349.640op/s 216560165.083op/s 217090869.985op/s 0.33% -6.365 72.314 0.08% 12201.271op/s 1 200
credit_card/is_card_number/378282246310005 execution_time 79.307µs 80.248µs ± 0.369µs 80.300µs ± 0.257µs 80.511µs 80.836µs 80.924µs 81.038µs 0.92% -0.267 -0.416 0.46% 0.026µs 1 200
credit_card/is_card_number/378282246310005 throughput 12339903.328op/s 12461668.705op/s ± 57447.642op/s 12453374.566op/s ± 39919.518op/s 12500401.576op/s 12557949.538op/s 12594108.954op/s 12609176.555op/s 1.25% 0.287 -0.402 0.46% 4062.162op/s 1 200
credit_card/is_card_number/37828224631000521389798 execution_time 58.866µs 59.002µs ± 0.157µs 58.922µs ± 0.047µs 59.086µs 59.333µs 59.468µs 59.754µs 1.41% 1.625 2.821 0.27% 0.011µs 1 200
credit_card/is_card_number/37828224631000521389798 throughput 16735182.473op/s 16948777.415op/s ± 44906.477op/s 16971596.339op/s ± 13562.030op/s 16980217.198op/s 16986405.610op/s 16987494.927op/s 16987612.633op/s 0.09% -1.607 2.721 0.26% 3175.367op/s 1 200
credit_card/is_card_number/x371413321323331 execution_time 6.818µs 6.827µs ± 0.027µs 6.822µs ± 0.002µs 6.824µs 6.829µs 6.983µs 7.027µs 3.01% 5.453 31.422 0.39% 0.002µs 1 200
credit_card/is_card_number/x371413321323331 throughput 142302064.962op/s 146472087.421op/s ± 567379.845op/s 146583494.699op/s ± 40192.358op/s 146629791.508op/s 146655210.554op/s 146661371.771op/s 146668846.356op/s 0.06% -5.410 30.870 0.39% 40119.814op/s 1 200
credit_card/is_card_number_no_luhn/ execution_time 4.606µs 4.621µs ± 0.002µs 4.621µs ± 0.001µs 4.623µs 4.625µs 4.627µs 4.627µs 0.13% -1.221 10.601 0.05% 0.000µs 1 200
credit_card/is_card_number_no_luhn/ throughput 216106095.710op/s 216380763.511op/s ± 103468.166op/s 216389872.960op/s ± 58936.609op/s 216440241.652op/s 216507892.378op/s 216542360.145op/s 217101781.509op/s 0.33% 1.237 10.719 0.05% 7316.304op/s 1 200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 execution_time 73.379µs 73.804µs ± 0.150µs 73.820µs ± 0.097µs 73.905µs 74.007µs 74.077µs 74.133µs 0.42% -0.510 -0.029 0.20% 0.011µs 1 200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 throughput 13489292.031op/s 13549505.953op/s ± 27558.779op/s 13546522.412op/s ± 17828.912op/s 13565912.254op/s 13601279.026op/s 13615793.333op/s 13627873.089op/s 0.60% 0.521 -0.016 0.20% 1948.700op/s 1 200
credit_card/is_card_number_no_luhn/ 378282246310005 execution_time 66.370µs 66.625µs ± 0.112µs 66.626µs ± 0.059µs 66.678µs 66.782µs 66.829µs 67.484µs 1.29% 2.092 15.739 0.17% 0.008µs 1 200
credit_card/is_card_number_no_luhn/ 378282246310005 throughput 14818338.941op/s 15009367.962op/s ± 25206.091op/s 15009057.867op/s ± 13234.976op/s 15022933.862op/s 15042647.949op/s 15062918.875op/s 15067091.964op/s 0.39% -2.026 15.145 0.17% 1782.340op/s 1 200
credit_card/is_card_number_no_luhn/37828224631 execution_time 4.609µs 4.622µs ± 0.006µs 4.621µs ± 0.001µs 4.623µs 4.625µs 4.626µs 4.695µs 1.59% 11.021 141.489 0.12% 0.000µs 1 200
credit_card/is_card_number_no_luhn/37828224631 throughput 213014475.731op/s 216375936.256op/s ± 259145.639op/s 216401666.293op/s ± 69747.626op/s 216466444.375op/s 216523923.139op/s 216544425.186op/s 216953905.015op/s 0.26% -10.941 140.144 0.12% 18324.364op/s 1 200
credit_card/is_card_number_no_luhn/378282246310005 execution_time 62.008µs 62.299µs ± 0.117µs 62.280µs ± 0.065µs 62.349µs 62.517µs 62.667µs 62.791µs 0.82% 1.102 2.586 0.19% 0.008µs 1 200
credit_card/is_card_number_no_luhn/378282246310005 throughput 15925765.752op/s 16051759.413op/s ± 30206.636op/s 16056471.708op/s ± 16777.584op/s 16072028.643op/s 16086198.606op/s 16118228.245op/s 16126901.284op/s 0.44% -1.083 2.529 0.19% 2135.932op/s 1 200
credit_card/is_card_number_no_luhn/37828224631000521389798 execution_time 58.864µs 59.014µs ± 0.168µs 58.921µs ± 0.046µs 59.179µs 59.302µs 59.532µs 59.558µs 1.08% 1.199 0.609 0.28% 0.012µs 1 200
credit_card/is_card_number_no_luhn/37828224631000521389798 throughput 16790433.562op/s 16945148.012op/s ± 48070.080op/s 16971761.535op/s ± 13387.500op/s 16982218.768op/s 16986450.164op/s 16987999.728op/s 16988351.088op/s 0.10% -1.190 0.569 0.28% 3399.068op/s 1 200
credit_card/is_card_number_no_luhn/x371413321323331 execution_time 6.817µs 6.828µs ± 0.031µs 6.822µs ± 0.002µs 6.824µs 6.865µs 6.954µs 7.098µs 4.04% 6.038 41.280 0.46% 0.002µs 1 200
credit_card/is_card_number_no_luhn/x371413321323331 throughput 140886272.680op/s 146450626.672op/s ± 650609.843op/s 146576489.133op/s ± 36445.991op/s 146625164.544op/s 146649683.446op/s 146661747.532op/s 146693693.262op/s 0.08% -5.947 39.978 0.44% 46005.063op/s 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
credit_card/is_card_number/ execution_time [4.621µs; 4.621µs] or [-0.005%; +0.005%] None None None
credit_card/is_card_number/ throughput [216388228.278op/s; 216411383.580op/s] or [-0.005%; +0.005%] None None None
credit_card/is_card_number/ 3782-8224-6310-005 execution_time [90.841µs; 90.937µs] or [-0.053%; +0.053%] None None None
credit_card/is_card_number/ 3782-8224-6310-005 throughput [10996829.450op/s; 11008426.964op/s] or [-0.053%; +0.053%] None None None
credit_card/is_card_number/ 378282246310005 execution_time [84.380µs; 84.553µs] or [-0.102%; +0.102%] None None None
credit_card/is_card_number/ 378282246310005 throughput [11827592.390op/s; 11851691.710op/s] or [-0.102%; +0.102%] None None None
credit_card/is_card_number/37828224631 execution_time [4.621µs; 4.622µs] or [-0.011%; +0.011%] None None None
credit_card/is_card_number/37828224631 throughput [216346432.851op/s; 216394260.956op/s] or [-0.011%; +0.011%] None None None
credit_card/is_card_number/378282246310005 execution_time [80.197µs; 80.299µs] or [-0.064%; +0.064%] None None None
credit_card/is_card_number/378282246310005 throughput [12453707.014op/s; 12469630.396op/s] or [-0.064%; +0.064%] None None None
credit_card/is_card_number/37828224631000521389798 execution_time [58.980µs; 59.023µs] or [-0.037%; +0.037%] None None None
credit_card/is_card_number/37828224631000521389798 throughput [16942553.810op/s; 16955001.021op/s] or [-0.037%; +0.037%] None None None
credit_card/is_card_number/x371413321323331 execution_time [6.824µs; 6.831µs] or [-0.055%; +0.055%] None None None
credit_card/is_card_number/x371413321323331 throughput [146393454.031op/s; 146550720.811op/s] or [-0.054%; +0.054%] None None None
credit_card/is_card_number_no_luhn/ execution_time [4.621µs; 4.622µs] or [-0.007%; +0.007%] None None None
credit_card/is_card_number_no_luhn/ throughput [216366423.819op/s; 216395103.204op/s] or [-0.007%; +0.007%] None None None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 execution_time [73.783µs; 73.825µs] or [-0.028%; +0.028%] None None None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 throughput [13545686.572op/s; 13553325.335op/s] or [-0.028%; +0.028%] None None None
credit_card/is_card_number_no_luhn/ 378282246310005 execution_time [66.610µs; 66.641µs] or [-0.023%; +0.023%] None None None
credit_card/is_card_number_no_luhn/ 378282246310005 throughput [15005874.641op/s; 15012861.284op/s] or [-0.023%; +0.023%] None None None
credit_card/is_card_number_no_luhn/37828224631 execution_time [4.621µs; 4.622µs] or [-0.017%; +0.017%] None None None
credit_card/is_card_number_no_luhn/37828224631 throughput [216340021.163op/s; 216411851.350op/s] or [-0.017%; +0.017%] None None None
credit_card/is_card_number_no_luhn/378282246310005 execution_time [62.282µs; 62.315µs] or [-0.026%; +0.026%] None None None
credit_card/is_card_number_no_luhn/378282246310005 throughput [16047573.064op/s; 16055945.762op/s] or [-0.026%; +0.026%] None None None
credit_card/is_card_number_no_luhn/37828224631000521389798 execution_time [58.991µs; 59.038µs] or [-0.039%; +0.039%] None None None
credit_card/is_card_number_no_luhn/37828224631000521389798 throughput [16938485.961op/s; 16951810.063op/s] or [-0.039%; +0.039%] None None None
credit_card/is_card_number_no_luhn/x371413321323331 execution_time [6.824µs; 6.833µs] or [-0.063%; +0.063%] None None None
credit_card/is_card_number_no_luhn/x371413321323331 throughput [146360458.405op/s; 146540794.939op/s] or [-0.062%; +0.062%] None None None

Group 5

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 11abb1a 1731062019 vianney/data-pipeline/add-meta-headers-for-stats
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000... execution_time 505.904µs 507.099µs ± 0.449µs 507.054µs ± 0.276µs 507.349µs 507.898µs 508.449µs 508.539µs 0.29% 0.611 0.676 0.09% 0.032µs 1 200
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000... throughput 1966416.384op/s 1972004.322op/s ± 1743.451op/s 1972175.733op/s ± 1071.998op/s 1973179.442op/s 1974510.441op/s 1975006.490op/s 1976659.374op/s 0.23% -0.605 0.665 0.09% 123.281op/s 1 200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて execution_time 467.876µs 468.619µs ± 0.296µs 468.601µs ± 0.224µs 468.832µs 469.103µs 469.271µs 469.717µs 0.24% 0.294 0.027 0.06% 0.021µs 1 200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて throughput 2128940.276op/s 2133930.229op/s ± 1346.106op/s 2134011.665op/s ± 1019.490op/s 2134977.131op/s 2135929.653op/s 2136521.778op/s 2137319.156op/s 0.15% -0.291 0.020 0.06% 95.184op/s 1 200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters execution_time 179.843µs 180.202µs ± 0.192µs 180.183µs ± 0.121µs 180.310µs 180.489µs 180.581µs 181.412µs 0.68% 1.628 7.605 0.11% 0.014µs 1 200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters throughput 5512299.688op/s 5549323.167op/s ± 5897.582op/s 5549915.774op/s ± 3728.204op/s 5553381.986op/s 5557202.951op/s 5559296.640op/s 5560406.973op/s 0.19% -1.606 7.447 0.11% 417.022op/s 1 200
normalization/normalize_service/normalize_service/[empty string] execution_time 44.784µs 44.946µs ± 0.062µs 44.945µs ± 0.039µs 44.982µs 45.041µs 45.101µs 45.183µs 0.53% 0.239 0.841 0.14% 0.004µs 1 200
normalization/normalize_service/normalize_service/[empty string] throughput 22132179.383op/s 22248954.109op/s ± 30648.610op/s 22249559.162op/s ± 19151.141op/s 22269831.942op/s 22297155.707op/s 22321361.808op/s 22329349.937op/s 0.36% -0.227 0.825 0.14% 2167.184op/s 1 200
normalization/normalize_service/normalize_service/test_ASCII execution_time 49.021µs 49.199µs ± 0.061µs 49.198µs ± 0.046µs 49.239µs 49.294µs 49.322µs 49.520µs 0.65% 0.656 3.115 0.12% 0.004µs 1 200
normalization/normalize_service/normalize_service/test_ASCII throughput 20193899.447op/s 20325445.231op/s ± 24975.240op/s 20325883.698op/s ± 19058.819op/s 20345843.434op/s 20360603.313op/s 20382272.204op/s 20399308.055op/s 0.36% -0.639 3.040 0.12% 1766.016op/s 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000... execution_time [507.037µs; 507.161µs] or [-0.012%; +0.012%] None None None
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000... throughput [1971762.696op/s; 1972245.947op/s] or [-0.012%; +0.012%] None None None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて execution_time [468.578µs; 468.660µs] or [-0.009%; +0.009%] None None None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて throughput [2133743.672op/s; 2134116.786op/s] or [-0.009%; +0.009%] None None None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters execution_time [180.176µs; 180.229µs] or [-0.015%; +0.015%] None None None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters throughput [5548505.819op/s; 5550140.515op/s] or [-0.015%; +0.015%] None None None
normalization/normalize_service/normalize_service/[empty string] execution_time [44.937µs; 44.955µs] or [-0.019%; +0.019%] None None None
normalization/normalize_service/normalize_service/[empty string] throughput [22244706.507op/s; 22253201.712op/s] or [-0.019%; +0.019%] None None None
normalization/normalize_service/normalize_service/test_ASCII execution_time [49.191µs; 49.208µs] or [-0.017%; +0.017%] None None None
normalization/normalize_service/normalize_service/test_ASCII throughput [20321983.903op/s; 20328906.559op/s] or [-0.017%; +0.017%] None None None

Group 6

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 11abb1a 1731062019 vianney/data-pipeline/add-meta-headers-for-stats
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
benching string interning on wordpress profile execution_time 142.121µs 142.912µs ± 0.602µs 142.846µs ± 0.191µs 143.040µs 143.431µs 144.133µs 149.477µs 4.64% 7.135 71.216 0.42% 0.043µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
benching string interning on wordpress profile execution_time [142.828µs; 142.995µs] or [-0.058%; +0.058%] None None None

Group 7

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 11abb1a 1731062019 vianney/data-pipeline/add-meta-headers-for-stats
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
write only interface execution_time 1.423µs 3.271µs ± 1.441µs 3.119µs ± 0.022µs 3.138µs 3.180µs 14.073µs 15.052µs 382.58% 7.614 58.007 43.94% 0.102µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
write only interface execution_time [3.071µs; 3.471µs] or [-6.105%; +6.105%] None None None

Group 8

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 11abb1a 1731062019 vianney/data-pipeline/add-meta-headers-for-stats
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
two way interface execution_time 18.367µs 24.807µs ± 11.045µs 19.187µs ± 0.246µs 33.155µs 41.545µs 46.387µs 97.671µs 409.04% 3.158 15.515 44.41% 0.781µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
two way interface execution_time [23.276µs; 26.338µs] or [-6.171%; +6.171%] None None None

Group 9

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 11abb1a 1731062019 vianney/data-pipeline/add-meta-headers-for-stats
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
sql/obfuscate_sql_string execution_time 67.885µs 68.068µs ± 0.184µs 68.046µs ± 0.050µs 68.103µs 68.209µs 68.404µs 70.297µs 3.31% 9.161 106.859 0.27% 0.013µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
sql/obfuscate_sql_string execution_time [68.043µs; 68.093µs] or [-0.037%; +0.037%] None None None

Group 10

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 11abb1a 1731062019 vianney/data-pipeline/add-meta-headers-for-stats
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
concentrator/add_spans_to_concentrator execution_time 9.120ms 9.155ms ± 0.014ms 9.154ms ± 0.008ms 9.162ms 9.178ms 9.185ms 9.241ms 0.95% 1.018 5.990 0.15% 0.001ms 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
concentrator/add_spans_to_concentrator execution_time [9.153ms; 9.157ms] or [-0.021%; +0.021%] None None None

Group 11

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 11abb1a 1731062019 vianney/data-pipeline/add-meta-headers-for-stats
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
normalization/normalize_trace/test_trace execution_time 294.824ns 307.261ns ± 14.207ns 300.316ns ± 3.897ns 314.869ns 339.832ns 350.020ns 350.625ns 16.75% 1.542 1.450 4.61% 1.005ns 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
normalization/normalize_trace/test_trace execution_time [305.292ns; 309.230ns] or [-0.641%; +0.641%] None None None

Group 12

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 11abb1a 1731062019 vianney/data-pipeline/add-meta-headers-for-stats
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... execution_time 271.767µs 273.292µs ± 0.891µs 273.192µs ± 0.579µs 273.766µs 274.910µs 275.684µs 276.365µs 1.16% 0.780 0.498 0.33% 0.063µs 1 200
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... throughput 3618404.508op/s 3659123.117op/s ± 11898.787op/s 3660427.955op/s ± 7737.043op/s 3668338.543op/s 3675777.416op/s 3677569.146op/s 3679629.388op/s 0.52% -0.762 0.454 0.32% 841.371op/s 1 200
normalization/normalize_name/normalize_name/bad-name execution_time 25.814µs 25.933µs ± 0.060µs 25.937µs ± 0.039µs 25.972µs 26.026µs 26.078µs 26.134µs 0.76% 0.138 -0.141 0.23% 0.004µs 1 200
normalization/normalize_name/normalize_name/bad-name throughput 38263851.067op/s 38561739.553op/s ± 88563.803op/s 38554904.535op/s ± 58668.175op/s 38632851.970op/s 38711100.524op/s 38736641.018op/s 38738851.266op/s 0.48% -0.126 -0.160 0.23% 6262.407op/s 1 200
normalization/normalize_name/normalize_name/good execution_time 15.419µs 15.470µs ± 0.035µs 15.466µs ± 0.021µs 15.489µs 15.525µs 15.551µs 15.724µs 1.67% 2.230 12.522 0.23% 0.002µs 1 200
normalization/normalize_name/normalize_name/good throughput 63599037.747op/s 64642025.726op/s ± 145449.063op/s 64660014.970op/s ± 89962.458op/s 64746824.406op/s 64815323.188op/s 64839792.218op/s 64856486.108op/s 0.30% -2.167 11.936 0.22% 10284.802op/s 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... execution_time [273.169µs; 273.416µs] or [-0.045%; +0.045%] None None None
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... throughput [3657474.060op/s; 3660772.175op/s] or [-0.045%; +0.045%] None None None
normalization/normalize_name/normalize_name/bad-name execution_time [25.924µs; 25.941µs] or [-0.032%; +0.032%] None None None
normalization/normalize_name/normalize_name/bad-name throughput [38549465.462op/s; 38574013.644op/s] or [-0.032%; +0.032%] None None None
normalization/normalize_name/normalize_name/good execution_time [15.465µs; 15.475µs] or [-0.031%; +0.031%] None None None
normalization/normalize_name/normalize_name/good throughput [64621867.885op/s; 64662183.568op/s] or [-0.031%; +0.031%] None None None

Baseline

Omitted due to size.

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codecov-commenter commented Nov 6, 2024 •
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Codecov Report

Attention: Patch coverage is 93.61702% with 3 lines in your changes missing coverage. Please review.

Project coverage is 71.55%. Comparing base (6943925) to head (11abb1a).

Additional details and impacted files 
@@            Coverage Diff             @@
##             main     #712      +/-   ##
==========================================
- Coverage   71.56%   71.55%   -0.01%     
==========================================
  Files         281      281              
  Lines       42414    42421       +7     
==========================================
+ Hits        30353    30356       +3     
- Misses      12061    12065       +4
Components Coverage Δ
crashtracker 43.37% <ø> (+0.03%) ⬆️
crashtracker-ffi 9.20% <ø> (ø)
datadog-alloc 98.73% <ø> (ø)
data-pipeline 92.21% <93.61%> (+0.01%) ⬆️
data-pipeline-ffi 0.00% <0.00%> (ø)
ddcommon 83.46% <ø> (ø)
ddcommon-ffi 69.12% <ø> (ø)
ddtelemetry 59.10% <ø> (ø)
ddtelemetry-ffi 22.13% <ø> (ø)
dogstatsd 89.45% <ø> (ø)
dogstatsd-client 79.77% <ø> (ø)
ipc 82.75% <ø> (-0.11%) ⬇️
profiling 84.30% <ø> (ø)
profiling-ffi 77.46% <ø> (ø)
serverless 0.00% <ø> (ø)
sidecar 37.42% <ø> (ø)
sidecar-ffi 0.00% <ø> (ø)
spawn-worker 50.36% <ø> (ø)
tinybytes 94.77% <ø> (ø)
trace-mini-agent 72.45% <ø> (ø)
trace-normalization 98.25% <ø> (ø)
trace-obfuscation 95.77% <ø> (ø)
trace-protobuf 77.67% <ø> (ø)
trace-utils 93.55% <ø> (ø)

@VianneyRuhlmann VianneyRuhlmann changed the title Add metadata headers for stats [APMSP-1512] Add metadata headers for stats Nov 6, 2024
@VianneyRuhlmann VianneyRuhlmann force-pushed the vianney/data-pipeline/add-meta-headers-for-stats branch from b3fe681 to f6cdd9f Compare November 6, 2024 16:11
@VianneyRuhlmann VianneyRuhlmann force-pushed the vianney/data-pipeline/add-meta-headers-for-stats branch from f6cdd9f to 759ed00 Compare November 7, 2024 09:01
@VianneyRuhlmann VianneyRuhlmann marked this pull request as ready for review November 7, 2024 09:47
@VianneyRuhlmann VianneyRuhlmann requested a review from a team as a code owner November 7, 2024 09:47
ichinaski
ichinaski reviewed Nov 7, 2024
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data-pipeline/src/stats_exporter.rs
git_commit_sha: meta.git_commit_sha.clone(),
// These fields will be set by the Agent
container_id: String::new(),
tags: Vec::new(),
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👍 From trace-agent perspective

ekump
ekump approved these changes Nov 7, 2024
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LGTM...but I noticed we don't have integration tests hitting the test-agent for sending stats to validate we're sending the right headers and payloads. Should we? Does the test-agent even support the stats endpoint right now?

@VianneyRuhlmann
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LGTM...but I noticed we don't have integration tests hitting the test-agent for sending stats to validate we're sending the right headers and payloads. Should we? Does the test-agent even support the stats endpoint right now?

It has support for stats endpoint but I don't think it allows to check headers in snapshots

@VianneyRuhlmann VianneyRuhlmann merged commit 573e678 into main Nov 8, 2024
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@VianneyRuhlmann VianneyRuhlmann deleted the vianney/data-pipeline/add-meta-headers-for-stats branch November 8, 2024 12:34
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