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chore: exclude libdatadog from ADMS auto generated PRs for dependency updates#1688

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chore: exclude libdatadog from ADMS auto generated PRs for dependency updates#1688
gh-worker-dd-mergequeue-cf854d[bot] merged 1 commit intomainfrom
ekump/APMSP-2694-opt-out-auto-dep-upgrades

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@ekump ekump commented Mar 7, 2026 •
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What does this PR do?

ADMS opens auto-generated PRs to update dependencies. None of the PRs properly compile. Rust is not listed as officially supported. The common components team monitors dependabot issues for security updates. These PRs just create noise and unnecessary work.

examples:

#1665
#1666
#1667
#1668
#1669
#1670
#1671
#1672
#1673
#1674

Motivation

What inspired you to submit this pull request?

Additional Notes

Anything else we should know when reviewing?

How to test the change?

Describe here in detail how the change can be validated.

@ekump ekump changed the title (chore): exclude libdatadog from ADMS auto-generated PRs for dependency updates (chore): exclude libdatadog from ADMS auto generated PRs for dependency updates Mar 7, 2026
@ekump ekump marked this pull request as ready for review March 7, 2026 03:54
@ekump ekump requested a review from a team as a code owner March 7, 2026 03:54
@ekump ekump changed the title (chore): exclude libdatadog from ADMS auto generated PRs for dependency updates chore: exclude libdatadog from ADMS auto generated PRs for dependency updates Mar 7, 2026
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Benchmarks

Comparison

Benchmark execution time: 2026-03-07 04:05:58

Comparing candidate commit c856aca in PR branch ekump/APMSP-2694-opt-out-auto-dep-upgrades with baseline commit 7e909c0 in branch main.

Found 0 performance improvements and 0 performance regressions! Performance is the same for 57 metrics, 2 unstable metrics.

Explanation

This is an A/B test comparing a candidate commit's performance against that of a baseline commit. Performance changes are noted in the tables below as:

  • 🟩 = significantly better candidate vs. baseline
  • 🟥 = significantly worse candidate vs. baseline

We compute a confidence interval (CI) over the relative difference of means between metrics from the candidate and baseline commits, considering the baseline as the reference.

If the CI is entirely outside the configured SIGNIFICANT_IMPACT_THRESHOLD (or the deprecated UNCONFIDENCE_THRESHOLD), the change is considered significant.

Feel free to reach out to #apm-benchmarking-platform on Slack if you have any questions.

More details about the CI and significant changes

You can imagine this CI as a range of values that is likely to contain the true difference of means between the candidate and baseline commits.

CIs of the difference of means are often centered around 0%, because often changes are not that big:

---------------------------------(------|---^--------)-------------------------------->
                              -0.6%    0%  0.3%     +1.2%
                                 |          |        |
         lower bound of the CI --'          |        |
sample mean (center of the CI) -------------'        |
         upper bound of the CI ----------------------'

As described above, a change is considered significant if the CI is entirely outside the configured SIGNIFICANT_IMPACT_THRESHOLD (or the deprecated UNCONFIDENCE_THRESHOLD).

For instance, for an execution time metric, this confidence interval indicates a significantly worse performance:

----------------------------------------|---------|---(---------^---------)---------->
                                       0%        1%  1.3%      2.2%      3.1%
                                                  |   |         |         |
       significant impact threshold --------------'   |         |         |
                      lower bound of CI --------------'         |         |
       sample mean (center of the CI) --------------------------'         |
                      upper bound of CI ----------------------------------'

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 c856aca 1772855283 ekump/APMSP-2694-opt-out-auto-dep-upgrades
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
profile_add_sample_frames_x1000 execution_time 4.175ms 4.180ms ± 0.008ms 4.179ms ± 0.001ms 4.181ms 4.185ms 4.190ms 4.292ms 2.71% 11.945 156.264 0.20% 0.001ms 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
profile_add_sample_frames_x1000 execution_time [4.179ms; 4.181ms] or [-0.028%; +0.028%] None None None

Group 2

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz c856aca 1772855283 ekump/APMSP-2694-opt-out-auto-dep-upgrades
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
ip_address/quantize_peer_ip_address_benchmark execution_time 4.920µs 5.035µs ± 0.052µs 5.049µs ± 0.034µs 5.070µs 5.114µs 5.117µs 5.117µs 1.35% -0.392 -0.762 1.03% 0.004µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
ip_address/quantize_peer_ip_address_benchmark execution_time [5.028µs; 5.042µs] or [-0.144%; +0.144%] None None None

Group 3

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz c856aca 1772855283 ekump/APMSP-2694-opt-out-auto-dep-upgrades
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 17.652µs 25.139µs ± 9.139µs 17.865µs ± 0.164µs 33.582µs 41.654µs 42.747µs 60.182µs 236.88% 0.798 -0.281 36.26% 0.646µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
two way interface execution_time [23.872µs; 26.405µs] or [-5.038%; +5.038%] None None None

Group 4

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz c856aca 1772855283 ekump/APMSP-2694-opt-out-auto-dep-upgrades
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 161.858µs 162.797µs ± 0.338µs 162.747µs ± 0.131µs 162.895µs 163.265µs 163.696µs 165.888µs 1.93% 4.365 35.288 0.21% 0.024µs 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 [162.750µs; 162.844µs] or [-0.029%; +0.029%] None None None

Group 5

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz c856aca 1772855283 ekump/APMSP-2694-opt-out-auto-dep-upgrades
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 85.509µs 86.027µs ± 0.154µs 86.005µs ± 0.045µs 86.072µs 86.161µs 86.838µs 87.367µs 1.58% 4.649 35.311 0.18% 0.011µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
sql/obfuscate_sql_string execution_time [86.006µs; 86.049µs] or [-0.025%; +0.025%] None None None

Group 6

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz c856aca 1772855283 ekump/APMSP-2694-opt-out-auto-dep-upgrades
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 240.285ns 250.066ns ± 12.014ns 245.403ns ± 3.009ns 252.161ns 281.422ns 291.485ns 292.668ns 19.26% 2.056 3.482 4.79% 0.850ns 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 [248.401ns; 251.731ns] or [-0.666%; +0.666%] None None None

Group 7

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz c856aca 1772855283 ekump/APMSP-2694-opt-out-auto-dep-upgrades
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 33.292µs 33.989µs ± 0.869µs 33.488µs ± 0.139µs 35.256µs 35.326µs 35.378µs 36.786µs 9.85% 0.951 -0.846 2.55% 0.061µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
redis/obfuscate_redis_string execution_time [33.869µs; 34.109µs] or [-0.354%; +0.354%] None None None

Group 8

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz c856aca 1772855283 ekump/APMSP-2694-opt-out-auto-dep-upgrades
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 48.371ms 48.773ms ± 1.140ms 48.641ms ± 0.053ms 48.692ms 48.872ms 52.276ms 62.709ms 28.92% 10.271 115.249 2.33% 0.081ms 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 [48.615ms; 48.931ms] or [-0.324%; +0.324%] None None None

Group 9

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz c856aca 1772855283 ekump/APMSP-2694-opt-out-auto-dep-upgrades
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 185.279µs 185.747µs ± 0.361µs 185.701µs ± 0.163µs 185.870µs 186.295µs 186.741µs 188.479µs 1.50% 3.692 22.326 0.19% 0.026µs 1 200
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... throughput 5305620.310op/s 5383685.731op/s ± 10382.142op/s 5385002.432op/s ± 4732.860op/s 5389496.014op/s 5395184.702op/s 5396992.566op/s 5397254.093op/s 0.23% -3.631 21.736 0.19% 734.128op/s 1 200
normalization/normalize_name/normalize_name/bad-name execution_time 17.918µs 17.988µs ± 0.056µs 17.980µs ± 0.021µs 18.006µs 18.047µs 18.087µs 18.635µs 3.64% 7.672 84.794 0.31% 0.004µs 1 200
normalization/normalize_name/normalize_name/bad-name throughput 53663890.876op/s 55592691.546op/s ± 170126.779op/s 55616923.720op/s ± 64673.664op/s 55669955.756op/s 55741683.866op/s 55777211.394op/s 55809564.634op/s 0.35% -7.413 80.811 0.31% 12029.780op/s 1 200
normalization/normalize_name/normalize_name/good execution_time 10.393µs 10.496µs ± 0.050µs 10.493µs ± 0.033µs 10.530µs 10.579µs 10.600µs 10.644µs 1.44% 0.240 -0.302 0.47% 0.004µs 1 200
normalization/normalize_name/normalize_name/good throughput 93948506.254op/s 95276334.541op/s ± 450499.712op/s 95300356.782op/s ± 302769.063op/s 95585696.837op/s 95957876.600op/s 96197275.779op/s 96216995.566op/s 0.96% -0.217 -0.324 0.47% 31855.140op/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 [185.697µs; 185.797µs] or [-0.027%; +0.027%] None None None
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... throughput [5382246.866op/s; 5385124.596op/s] or [-0.027%; +0.027%] None None None
normalization/normalize_name/normalize_name/bad-name execution_time [17.980µs; 17.996µs] or [-0.043%; +0.043%] None None None
normalization/normalize_name/normalize_name/bad-name throughput [55569113.611op/s; 55616269.482op/s] or [-0.042%; +0.042%] None None None
normalization/normalize_name/normalize_name/good execution_time [10.489µs; 10.503µs] or [-0.066%; +0.066%] None None None
normalization/normalize_name/normalize_name/good throughput [95213899.613op/s; 95338769.468op/s] or [-0.066%; +0.066%] None None None

Group 10

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz c856aca 1772855283 ekump/APMSP-2694-opt-out-auto-dep-upgrades
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
benching serializing traces from their internal representation to msgpack execution_time 13.902ms 13.970ms ± 0.033ms 13.966ms ± 0.015ms 13.983ms 14.014ms 14.093ms 14.120ms 1.10% 1.673 5.109 0.23% 0.002ms 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
benching serializing traces from their internal representation to msgpack execution_time [13.965ms; 13.974ms] or [-0.032%; +0.032%] None None None

Group 11

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz c856aca 1772855283 ekump/APMSP-2694-opt-out-auto-dep-upgrades
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
single_flag_killswitch/rules-based execution_time 187.586ns 190.069ns ± 2.299ns 189.878ns ± 1.578ns 191.251ns 193.448ns 196.728ns 205.196ns 8.07% 2.072 8.897 1.21% 0.163ns 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
single_flag_killswitch/rules-based execution_time [189.751ns; 190.388ns] or [-0.168%; +0.168%] None None None

Group 12

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz c856aca 1772855283 ekump/APMSP-2694-opt-out-auto-dep-upgrades
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
profile_add_sample2_frames_x1000 execution_time 732.747µs 734.157µs ± 0.702µs 734.099µs ± 0.355µs 734.465µs 735.089µs 735.588µs 740.406µs 0.86% 3.622 29.800 0.10% 0.050µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
profile_add_sample2_frames_x1000 execution_time [734.060µs; 734.255µs] or [-0.013%; +0.013%] None None None

Group 13

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz c856aca 1772855283 ekump/APMSP-2694-opt-out-auto-dep-upgrades
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 3.891µs 3.912µs ± 0.003µs 3.912µs ± 0.002µs 3.914µs 3.916µs 3.917µs 3.920µs 0.21% -1.590 10.883 0.08% 0.000µs 1 200
credit_card/is_card_number/ throughput 255071580.148op/s 255623845.152op/s ± 192436.293op/s 255616656.211op/s ± 132276.393op/s 255749609.044op/s 255874296.454op/s 255948018.074op/s 256983065.047op/s 0.53% 1.613 11.072 0.08% 13607.301op/s 1 200
credit_card/is_card_number/ 3782-8224-6310-005 execution_time 79.030µs 79.750µs ± 0.412µs 79.686µs ± 0.315µs 80.051µs 80.452µs 80.743µs 81.097µs 1.77% 0.511 -0.216 0.52% 0.029µs 1 200
credit_card/is_card_number/ 3782-8224-6310-005 throughput 12330896.676op/s 12539474.024op/s ± 64586.774op/s 12549198.595op/s ± 49737.425op/s 12593353.905op/s 12628107.327op/s 12647365.636op/s 12653459.601op/s 0.83% -0.488 -0.264 0.51% 4566.975op/s 1 200
credit_card/is_card_number/ 378282246310005 execution_time 72.283µs 73.018µs ± 0.349µs 72.987µs ± 0.246µs 73.239µs 73.626µs 73.914µs 74.126µs 1.56% 0.510 0.061 0.48% 0.025µs 1 200
credit_card/is_card_number/ 378282246310005 throughput 13490477.189op/s 13695583.895op/s ± 65322.348op/s 13701085.721op/s ± 46033.419op/s 13743491.953op/s 13790786.601op/s 13812286.984op/s 13834568.436op/s 0.97% -0.484 0.016 0.48% 4618.988op/s 1 200
credit_card/is_card_number/37828224631 execution_time 3.895µs 3.911µs ± 0.002µs 3.911µs ± 0.001µs 3.913µs 3.916µs 3.917µs 3.917µs 0.16% -1.207 8.913 0.06% 0.000µs 1 200
credit_card/is_card_number/37828224631 throughput 255266060.939op/s 255657563.618op/s ± 162900.179op/s 255664632.019op/s ± 96309.710op/s 255751244.896op/s 255881362.028op/s 255929348.367op/s 256753439.150op/s 0.43% 1.225 9.045 0.06% 11518.782op/s 1 200
credit_card/is_card_number/378282246310005 execution_time 69.128µs 69.760µs ± 0.342µs 69.741µs ± 0.224µs 69.960µs 70.376µs 70.735µs 70.863µs 1.61% 0.607 0.337 0.49% 0.024µs 1 200
credit_card/is_card_number/378282246310005 throughput 14111796.197op/s 14335292.649op/s ± 70053.475op/s 14338817.699op/s ± 45893.852op/s 14386261.293op/s 14437711.233op/s 14445808.776op/s 14465816.572op/s 0.89% -0.578 0.277 0.49% 4953.529op/s 1 200
credit_card/is_card_number/37828224631000521389798 execution_time 52.145µs 52.214µs ± 0.038µs 52.212µs ± 0.025µs 52.236µs 52.278µs 52.311µs 52.335µs 0.23% 0.539 0.155 0.07% 0.003µs 1 200
credit_card/is_card_number/37828224631000521389798 throughput 19107852.382op/s 19152074.167op/s ± 14024.438op/s 19152557.201op/s ± 9288.690op/s 19162151.877op/s 19171579.188op/s 19175796.157op/s 19177202.142op/s 0.13% -0.535 0.147 0.07% 991.677op/s 1 200
credit_card/is_card_number/x371413321323331 execution_time 6.027µs 6.036µs ± 0.009µs 6.033µs ± 0.002µs 6.036µs 6.047µs 6.073µs 6.107µs 1.22% 4.199 21.297 0.16% 0.001µs 1 200
credit_card/is_card_number/x371413321323331 throughput 163751747.212op/s 165686522.402op/s ± 257201.753op/s 165746027.672op/s ± 59744.070op/s 165796862.673op/s 165863255.056op/s 165902598.761op/s 165911703.333op/s 0.10% -4.173 21.002 0.15% 18186.910op/s 1 200
credit_card/is_card_number_no_luhn/ execution_time 3.894µs 3.912µs ± 0.003µs 3.911µs ± 0.001µs 3.913µs 3.916µs 3.920µs 3.924µs 0.33% -0.101 11.116 0.07% 0.000µs 1 200
credit_card/is_card_number_no_luhn/ throughput 254829827.811op/s 255635839.456op/s ± 184256.661op/s 255661742.311op/s ± 86408.842op/s 255735904.453op/s 255832565.873op/s 255929279.647op/s 256836358.864op/s 0.46% 0.129 11.228 0.07% 13028.913op/s 1 200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 execution_time 64.052µs 64.387µs ± 0.137µs 64.364µs ± 0.087µs 64.463µs 64.623µs 64.783µs 64.841µs 0.74% 0.709 0.582 0.21% 0.010µs 1 200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 throughput 15422340.803op/s 15531271.234op/s ± 33081.160op/s 15536745.249op/s ± 21048.018op/s 15555475.951op/s 15575734.019op/s 15587535.633op/s 15612436.867op/s 0.49% -0.696 0.560 0.21% 2339.191op/s 1 200
credit_card/is_card_number_no_luhn/ 378282246310005 execution_time 57.969µs 58.150µs ± 0.119µs 58.110µs ± 0.059µs 58.189µs 58.377µs 58.508µs 58.596µs 0.84% 1.292 1.446 0.20% 0.008µs 1 200
credit_card/is_card_number_no_luhn/ 378282246310005 throughput 17065957.459op/s 17196894.392op/s ± 35055.660op/s 17208636.766op/s ± 17349.202op/s 17220483.556op/s 17235764.460op/s 17243692.757op/s 17250694.066op/s 0.24% -1.281 1.409 0.20% 2478.810op/s 1 200
credit_card/is_card_number_no_luhn/37828224631 execution_time 3.891µs 3.912µs ± 0.003µs 3.912µs ± 0.002µs 3.914µs 3.916µs 3.920µs 3.921µs 0.23% -1.417 12.914 0.08% 0.000µs 1 200
credit_card/is_card_number_no_luhn/37828224631 throughput 255025330.488op/s 255618722.011op/s ± 193510.016op/s 255624552.413op/s ± 112302.814op/s 255738546.199op/s 255861211.765op/s 255905295.462op/s 257024912.016op/s 0.55% 1.446 13.135 0.08% 13683.224op/s 1 200
credit_card/is_card_number_no_luhn/378282246310005 execution_time 54.576µs 54.928µs ± 0.273µs 54.871µs ± 0.175µs 55.061µs 55.446µs 55.801µs 55.854µs 1.79% 1.205 1.306 0.50% 0.019µs 1 200
credit_card/is_card_number_no_luhn/378282246310005 throughput 17903750.226op/s 18206033.193op/s ± 89843.942op/s 18224715.455op/s ± 57988.756op/s 18277555.787op/s 18301573.736op/s 18318341.067op/s 18323046.587op/s 0.54% -1.177 1.214 0.49% 6352.926op/s 1 200
credit_card/is_card_number_no_luhn/37828224631000521389798 execution_time 52.142µs 52.202µs ± 0.036µs 52.197µs ± 0.023µs 52.223µs 52.269µs 52.313µs 52.363µs 0.32% 1.004 1.643 0.07% 0.003µs 1 200
credit_card/is_card_number_no_luhn/37828224631000521389798 throughput 19097621.471op/s 19156195.931op/s ± 13133.363op/s 19158257.988op/s ± 8505.886op/s 19166232.453op/s 19173103.587op/s 19176588.990op/s 19178228.875op/s 0.10% -0.998 1.621 0.07% 928.669op/s 1 200
credit_card/is_card_number_no_luhn/x371413321323331 execution_time 6.027µs 6.035µs ± 0.007µs 6.034µs ± 0.002µs 6.036µs 6.040µs 6.072µs 6.074µs 0.68% 3.998 20.319 0.11% 0.000µs 1 200
credit_card/is_card_number_no_luhn/x371413321323331 throughput 164626192.733op/s 165706093.037op/s ± 180420.858op/s 165737572.709op/s ± 66624.859op/s 165799429.918op/s 165864444.667op/s 165905829.575op/s 165916737.034op/s 0.11% -3.977 20.164 0.11% 12757.681op/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 [3.912µs; 3.912µs] or [-0.010%; +0.010%] None None None
credit_card/is_card_number/ throughput [255597175.333op/s; 255650514.972op/s] or [-0.010%; +0.010%] None None None
credit_card/is_card_number/ 3782-8224-6310-005 execution_time [79.693µs; 79.807µs] or [-0.072%; +0.072%] None None None
credit_card/is_card_number/ 3782-8224-6310-005 throughput [12530522.918op/s; 12548425.129op/s] or [-0.071%; +0.071%] None None None
credit_card/is_card_number/ 378282246310005 execution_time [72.970µs; 73.066µs] or [-0.066%; +0.066%] None None None
credit_card/is_card_number/ 378282246310005 throughput [13686530.846op/s; 13704636.944op/s] or [-0.066%; +0.066%] None None None
credit_card/is_card_number/37828224631 execution_time [3.911µs; 3.912µs] or [-0.009%; +0.009%] None None None
credit_card/is_card_number/37828224631 throughput [255634987.220op/s; 255680140.016op/s] or [-0.009%; +0.009%] None None None
credit_card/is_card_number/378282246310005 execution_time [69.712µs; 69.807µs] or [-0.068%; +0.068%] None None None
credit_card/is_card_number/378282246310005 throughput [14325583.911op/s; 14345001.387op/s] or [-0.068%; +0.068%] None None None
credit_card/is_card_number/37828224631000521389798 execution_time [52.208µs; 52.219µs] or [-0.010%; +0.010%] None None None
credit_card/is_card_number/37828224631000521389798 throughput [19150130.515op/s; 19154017.819op/s] or [-0.010%; +0.010%] None None None
credit_card/is_card_number/x371413321323331 execution_time [6.034µs; 6.037µs] or [-0.022%; +0.022%] None None None
credit_card/is_card_number/x371413321323331 throughput [165650876.713op/s; 165722168.091op/s] or [-0.022%; +0.022%] None None None
credit_card/is_card_number_no_luhn/ execution_time [3.911µs; 3.912µs] or [-0.010%; +0.010%] None None None
credit_card/is_card_number_no_luhn/ throughput [255610303.255op/s; 255661375.657op/s] or [-0.010%; +0.010%] None None None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 execution_time [64.367µs; 64.406µs] or [-0.030%; +0.030%] None None None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 throughput [15526686.503op/s; 15535855.964op/s] or [-0.030%; +0.030%] None None None
credit_card/is_card_number_no_luhn/ 378282246310005 execution_time [58.134µs; 58.167µs] or [-0.028%; +0.028%] None None None
credit_card/is_card_number_no_luhn/ 378282246310005 throughput [17192036.015op/s; 17201752.769op/s] or [-0.028%; +0.028%] None None None
credit_card/is_card_number_no_luhn/37828224631 execution_time [3.912µs; 3.912µs] or [-0.010%; +0.010%] None None None
credit_card/is_card_number_no_luhn/37828224631 throughput [255591903.384op/s; 255645540.638op/s] or [-0.010%; +0.010%] None None None
credit_card/is_card_number_no_luhn/378282246310005 execution_time [54.890µs; 54.966µs] or [-0.069%; +0.069%] None None None
credit_card/is_card_number_no_luhn/378282246310005 throughput [18193581.687op/s; 18218484.700op/s] or [-0.068%; +0.068%] None None None
credit_card/is_card_number_no_luhn/37828224631000521389798 execution_time [52.197µs; 52.207µs] or [-0.010%; +0.010%] None None None
credit_card/is_card_number_no_luhn/37828224631000521389798 throughput [19154375.773op/s; 19158016.088op/s] or [-0.010%; +0.010%] None None None
credit_card/is_card_number_no_luhn/x371413321323331 execution_time [6.034µs; 6.036µs] or [-0.015%; +0.015%] None None None
credit_card/is_card_number_no_luhn/x371413321323331 throughput [165681088.441op/s; 165731097.632op/s] or [-0.015%; +0.015%] None None None

Group 14

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz c856aca 1772855283 ekump/APMSP-2694-opt-out-auto-dep-upgrades
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 1.219µs 3.210µs ± 1.426µs 2.996µs ± 0.032µs 3.023µs 3.655µs 13.987µs 14.734µs 391.79% 7.320 54.849 44.31% 0.101µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
write only interface execution_time [3.013µs; 3.408µs] or [-6.156%; +6.156%] None None None

Group 15

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz c856aca 1772855283 ekump/APMSP-2694-opt-out-auto-dep-upgrades
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 534.057µs 535.689µs ± 1.264µs 535.177µs ± 0.456µs 536.497µs 538.010µs 539.260µs 541.219µs 1.13% 1.324 1.480 0.24% 0.089µs 1 200
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000... throughput 1847679.478op/s 1866763.456op/s ± 4390.903op/s 1868539.970op/s ± 1592.485op/s 1869766.990op/s 1871400.228op/s 1872246.346op/s 1872459.101op/s 0.21% -1.312 1.423 0.23% 310.484op/s 1 200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて execution_time 380.086µs 380.751µs ± 0.327µs 380.741µs ± 0.208µs 380.935µs 381.312µs 381.605µs 382.090µs 0.35% 0.612 0.841 0.09% 0.023µs 1 200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて throughput 2617184.731op/s 2626391.974op/s ± 2254.206op/s 2626454.956op/s ± 1437.726op/s 2628024.499op/s 2629814.895op/s 2630638.777op/s 2630985.019op/s 0.17% -0.606 0.824 0.09% 159.396op/s 1 200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters execution_time 189.740µs 190.215µs ± 0.219µs 190.221µs ± 0.149µs 190.352µs 190.539µs 190.813µs 190.979µs 0.40% 0.346 0.222 0.12% 0.016µs 1 200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters throughput 5236164.442op/s 5257226.305op/s ± 6060.451op/s 5257046.313op/s ± 4113.244op/s 5261613.317op/s 5266842.055op/s 5268633.029op/s 5270357.872op/s 0.25% -0.339 0.208 0.11% 428.539op/s 1 200
normalization/normalize_service/normalize_service/[empty string] execution_time 37.208µs 37.454µs ± 0.069µs 37.449µs ± 0.038µs 37.490µs 37.571µs 37.635µs 37.669µs 0.59% 0.058 1.199 0.18% 0.005µs 1 200
normalization/normalize_service/normalize_service/[empty string] throughput 26546830.901op/s 26699849.069op/s ± 48944.026op/s 26702821.442op/s ± 27152.837op/s 26727097.483op/s 26772251.860op/s 26833305.626op/s 26875704.187op/s 0.65% -0.040 1.207 0.18% 3460.865op/s 1 200
normalization/normalize_service/normalize_service/test_ASCII execution_time 45.758µs 45.908µs ± 0.122µs 45.895µs ± 0.042µs 45.944µs 45.984µs 46.027µs 47.440µs 3.37% 9.974 123.209 0.26% 0.009µs 1 200
normalization/normalize_service/normalize_service/test_ASCII throughput 21079100.025op/s 21782829.246op/s ± 56368.408op/s 21788860.615op/s ± 20000.437op/s 21802940.992op/s 21826403.097op/s 21848342.234op/s 21854239.990op/s 0.30% -9.770 119.832 0.26% 3985.848op/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 [535.514µs; 535.865µs] or [-0.033%; +0.033%] None None None
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000... throughput [1866154.919op/s; 1867371.993op/s] or [-0.033%; +0.033%] None None None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて execution_time [380.705µs; 380.796µs] or [-0.012%; +0.012%] None None None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて throughput [2626079.563op/s; 2626704.385op/s] or [-0.012%; +0.012%] None None None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters execution_time [190.184µs; 190.245µs] or [-0.016%; +0.016%] None None None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters throughput [5256386.385op/s; 5258066.226op/s] or [-0.016%; +0.016%] None None None
normalization/normalize_service/normalize_service/[empty string] execution_time [37.444µs; 37.463µs] or [-0.025%; +0.025%] None None None
normalization/normalize_service/normalize_service/[empty string] throughput [26693065.898op/s; 26706632.240op/s] or [-0.025%; +0.025%] None None None
normalization/normalize_service/normalize_service/test_ASCII execution_time [45.891µs; 45.925µs] or [-0.037%; +0.037%] None None None
normalization/normalize_service/normalize_service/test_ASCII throughput [21775017.127op/s; 21790641.365op/s] or [-0.036%; +0.036%] None None None

Group 16

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz c856aca 1772855283 ekump/APMSP-2694-opt-out-auto-dep-upgrades
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
sdk_test_data/rules-based execution_time 144.006µs 146.204µs ± 1.716µs 145.832µs ± 0.579µs 146.545µs 148.016µs 152.313µs 161.794µs 10.95% 5.052 37.387 1.17% 0.121µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
sdk_test_data/rules-based execution_time [145.966µs; 146.442µs] or [-0.163%; +0.163%] None None None

Group 17

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz c856aca 1772855283 ekump/APMSP-2694-opt-out-auto-dep-upgrades
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 2.346µs 2.406µs ± 0.017µs 2.404µs ± 0.007µs 2.411µs 2.438µs 2.445µs 2.447µs 1.80% -0.350 1.616 0.72% 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 [2.403µs; 2.408µs] or [-0.099%; +0.099%] None None None

Group 18

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz c856aca 1772855283 ekump/APMSP-2694-opt-out-auto-dep-upgrades
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 10.648ms 10.674ms ± 0.015ms 10.672ms ± 0.009ms 10.683ms 10.699ms 10.718ms 10.747ms 0.70% 1.328 3.572 0.14% 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 [10.672ms; 10.676ms] or [-0.019%; +0.019%] None None None

Group 19

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz c856aca 1772855283 ekump/APMSP-2694-opt-out-auto-dep-upgrades
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
receiver_entry_point/report/2597 execution_time 3.123ms 3.158ms ± 0.024ms 3.150ms ± 0.010ms 3.168ms 3.208ms 3.225ms 3.247ms 3.07% 1.260 1.120 0.74% 0.002ms 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
receiver_entry_point/report/2597 execution_time [3.155ms; 3.162ms] or [-0.103%; +0.103%] None None None

Baseline

Omitted due to size.

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codecov-commenter commented Mar 7, 2026

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 71.38%. Comparing base (7e909c0) to head (c856aca).

Additional details and impacted files 
@@           Coverage Diff           @@
##             main    #1688   +/-   ##
=======================================
  Coverage   71.37%   71.38%           
=======================================
  Files         427      427           
  Lines       62903    62903           
=======================================
+ Hits        44899    44903    +4     
+ Misses      18004    18000    -4
Components Coverage Δ
libdd-crashtracker 62.98% <ø> (-0.02%) ⬇️
libdd-crashtracker-ffi 16.56% <ø> (ø)
libdd-alloc 98.77% <ø> (ø)
libdd-data-pipeline 88.02% <ø> (ø)
libdd-data-pipeline-ffi 75.72% <ø> (ø)
libdd-common 79.73% <ø> (ø)
libdd-common-ffi 73.40% <ø> (ø)
libdd-telemetry 62.48% <ø> (ø)
libdd-telemetry-ffi 16.75% <ø> (ø)
libdd-dogstatsd-client 82.64% <ø> (ø)
datadog-ipc 80.35% <ø> (ø)
libdd-profiling 81.60% <ø> (ø)
libdd-profiling-ffi 63.65% <ø> (ø)
datadog-sidecar 34.48% <ø> (ø)
datdog-sidecar-ffi 16.55% <ø> (ø)
spawn-worker 54.69% <ø> (ø)
libdd-tinybytes 93.16% <ø> (ø)
libdd-trace-normalization 81.71% <ø> (ø)
libdd-trace-obfuscation 94.69% <ø> (ø)
libdd-trace-protobuf 68.25% <ø> (ø)
libdd-trace-utils 89.08% <ø> (ø)
datadog-tracer-flare 88.95% <ø> (ø)
libdd-log 74.69% <ø> (ø)
🚀 New features to boost your workflow:
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dd-octo-sts bot commented Mar 7, 2026

Artifact Size Benchmark Report

aarch64-alpine-linux-musl
Artifact Baseline Commit Change
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.so 8.70 MB 8.70 MB 0% (0 B) 👌
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.a 98.65 MB 98.65 MB 0% (0 B) 👌
aarch64-unknown-linux-gnu
Artifact Baseline Commit Change
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.so 11.29 MB 11.29 MB 0% (0 B) 👌
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.a 114.30 MB 114.30 MB 0% (0 B) 👌
libdatadog-x64-windows
Artifact Baseline Commit Change
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.dll 27.17 MB 27.17 MB 0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.lib 76.26 KB 76.26 KB 0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.pdb 186.04 MB 186.02 MB -0% (-16.00 KB) 👌
/libdatadog-x64-windows/debug/static/datadog_profiling_ffi.lib 917.20 MB 917.20 MB 0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.dll 9.93 MB 9.93 MB 0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.lib 76.26 KB 76.26 KB 0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.pdb 24.76 MB 24.76 MB 0% (0 B) 👌
/libdatadog-x64-windows/release/static/datadog_profiling_ffi.lib 51.43 MB 51.43 MB 0% (0 B) 👌
libdatadog-x86-windows
Artifact Baseline Commit Change
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.dll 22.97 MB 22.97 MB 0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.lib 77.44 KB 77.44 KB 0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.pdb 190.24 MB 190.24 MB 0% (0 B) 👌
/libdatadog-x86-windows/debug/static/datadog_profiling_ffi.lib 900.85 MB 900.85 MB 0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.dll 7.53 MB 7.53 MB 0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.lib 77.44 KB 77.44 KB 0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.pdb 26.52 MB 26.52 MB 0% (0 B) 👌
/libdatadog-x86-windows/release/static/datadog_profiling_ffi.lib 47.07 MB 47.07 MB 0% (0 B) 👌
x86_64-alpine-linux-musl
Artifact Baseline Commit Change
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.a 86.54 MB 86.54 MB -0% (-8 B) 👌
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.so 10.23 MB 10.23 MB 0% (0 B) 👌
x86_64-unknown-linux-gnu
Artifact Baseline Commit Change
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.a 107.16 MB 107.16 MB 0% (0 B) 👌
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.so 11.98 MB 11.98 MB 0% (0 B) 👌

@gh-worker-dd-mergequeue-cf854d gh-worker-dd-mergequeue-cf854d bot merged commit f8900a6 into main Mar 9, 2026
86 of 90 checks passed
@gh-worker-dd-mergequeue-cf854d gh-worker-dd-mergequeue-cf854d bot deleted the ekump/APMSP-2694-opt-out-auto-dep-upgrades branch March 9, 2026 00:04
@gyuheon0h gyuheon0h mentioned this pull request Mar 11, 2026
Merged
gh-worker-dd-mergequeue-cf854d bot pushed a commit that referenced this pull request Mar 11, 2026
@gyuheon0h
chore(cargo): bump to 29.0.0 (#1702)
001bd56 
# What does this PR do?

Bump to 29.0.0

[feat(profiling)!: add Tracepoint sample type](#1676)
[feat(obfuscation/redis): Reach feature parity on redis obfuscation [APMSP-2668]](#1632)
[fix(sidecar): Handle backpressure more gracefully](#1682)
[feat(trace-protobuf)!: Add two fields to ClientGroupedStats [SVLS-8627]](#1630)
[chore: exclude libdatadog from ADMS auto generated PRs for dependency updates](#1688)
[chore(ci): run crashtracking ffi example tests in CI](#1687)
[fix(crashtracking): use libunwind to unwind frames](#1663)
[feat: publish tracer metadata as OTel process ctx](#1658)
[ci: run thread count test in own process](#1693)
[feat(obfuscation/json): Init json obfuscation [APMSP-2665]](#1635)
[chore(ci): add final_status property on junit XML [APMSP-2610]](#1681)
[refactor(data-pipeline-ffi): move macro definitions for better reuse](#1699)
[fix(obfuscation/memcached): fuzzing fix](#1695)
[ci: replace use of cargo cross for centos7 tests](#1675)
#1702 (comment)
[feat(stats_exporter)!: add process tags to CSS payloads](#1709)

# Motivation

I mainly am creating this to use the new unwinding from ucontext for crashtracking

# Additional Notes

Anything else we should know when reviewing?

# How to test the change?

Describe here in detail how the change can be validated.


[APMSP-2668]: https://datadoghq.atlassian.net/browse/APMSP-2668?atlOrigin=eyJpIjoiNWRkNTljNzYxNjVmNDY3MDlhMDU5Y2ZhYzA5YTRkZjUiLCJwIjoiZ2l0aHViLWNvbS1KU1cifQ
[SVLS-8627]: https://datadoghq.atlassian.net/browse/SVLS-8627?atlOrigin=eyJpIjoiNWRkNTljNzYxNjVmNDY3MDlhMDU5Y2ZhYzA5YTRkZjUiLCJwIjoiZ2l0aHViLWNvbS1KU1cifQ
[APMSP-2665]: https://datadoghq.atlassian.net/browse/APMSP-2665?atlOrigin=eyJpIjoiNWRkNTljNzYxNjVmNDY3MDlhMDU5Y2ZhYzA5YTRkZjUiLCJwIjoiZ2l0aHViLWNvbS1KU1cifQ

Co-authored-by: gyuheon.oh <gyuheon.oh@datadoghq.com>
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@ekump @codecov-commenter @morrisonlevi @bwoebi