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feat(telemetry): add process_tags to Application in telemetry #1459

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feat(telemetry): add process_tags to Application in telemetry #1459

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@dubloom dubloom commented Jan 20, 2026

What does this PR do?

This PR adds a process_tags field to the telemetry Application struct. This tag can be set during configuration or later (when the process_tags are acquired).

Motivation

dd-trace-php needs to be send the process_tags for its telemetry according to this RFC.
It is important to note that the tracer will set the configuration of its sidecar before we can retrieve the process_tags. That's why I created a function specifically to set the processs_tags.

How to test the change?

A PR will be opened soon in dd-trace-php to test the functionnality.

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Benchmarks

Comparison

Benchmark execution time: 2026-02-06 09:34:44

Comparing candidate commit 84cf815 in PR branch dubloom/process-tags-telemetry with baseline commit f483c69 in branch main.

Found 0 performance improvements and 0 performance regressions! Performance is the same for 57 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 84cf815 1770369521 dubloom/process-tags-telemetry
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 143.791µs 145.865µs ± 1.605µs 145.607µs ± 0.485µs 146.139µs 147.420µs 150.581µs 160.753µs 10.40% 5.489 42.319 1.10% 0.113µs 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 [145.643µs; 146.087µs] or [-0.152%; +0.152%] None None None

Group 2

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 84cf815 1770369521 dubloom/process-tags-telemetry
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 542.661µs 543.537µs ± 0.604µs 543.472µs ± 0.291µs 543.770µs 544.544µs 545.100µs 548.663µs 0.96% 3.517 25.000 0.11% 0.043µs 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 [543.454µs; 543.621µs] or [-0.015%; +0.015%] None None None

Group 3

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 84cf815 1770369521 dubloom/process-tags-telemetry
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 1.204µs 3.203µs ± 1.384µs 3.001µs ± 0.029µs 3.028µs 3.673µs 13.653µs 14.706µs 389.98% 7.315 54.915 43.11% 0.098µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
write only interface execution_time [3.011µs; 3.394µs] or [-5.990%; +5.990%] None None None

Group 4

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 84cf815 1770369521 dubloom/process-tags-telemetry
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 188.917ns 191.228ns ± 1.897ns 191.064ns ± 1.389ns 192.353ns 195.013ns 196.704ns 197.070ns 3.14% 0.952 0.375 0.99% 0.134ns 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 [190.966ns; 191.491ns] or [-0.137%; +0.137%] None None None

Group 5

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 84cf815 1770369521 dubloom/process-tags-telemetry
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 534.809µs 536.659µs ± 1.312µs 536.113µs ± 0.551µs 537.400µs 539.000µs 540.896µs 542.194µs 1.13% 1.470 2.404 0.24% 0.093µs 1 200
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000... throughput 1844358.493op/s 1863390.381op/s ± 4537.878op/s 1865279.323op/s ± 1920.382op/s 1866574.765op/s 1868085.371op/s 1868644.817op/s 1869827.247op/s 0.24% -1.453 2.324 0.24% 320.876op/s 1 200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて execution_time 381.153µs 381.757µs ± 0.296µs 381.748µs ± 0.211µs 381.949µs 382.241µs 382.472µs 383.186µs 0.38% 0.691 1.892 0.08% 0.021µs 1 200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて throughput 2609698.980op/s 2619466.128op/s ± 2028.792op/s 2619532.246op/s ± 1447.776op/s 2620973.377op/s 2622519.747op/s 2623471.161op/s 2623620.432op/s 0.16% -0.683 1.860 0.08% 143.457op/s 1 200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters execution_time 189.270µs 189.846µs ± 0.285µs 189.843µs ± 0.237µs 190.077µs 190.284µs 190.441µs 190.653µs 0.43% 0.177 -0.818 0.15% 0.020µs 1 200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters throughput 5245118.509op/s 5267442.488op/s ± 7899.179op/s 5267507.320op/s ± 6593.444op/s 5274230.586op/s 5278793.846op/s 5281559.976op/s 5283461.789op/s 0.30% -0.171 -0.824 0.15% 558.556op/s 1 200
normalization/normalize_service/normalize_service/[empty string] execution_time 36.503µs 36.602µs ± 0.056µs 36.592µs ± 0.033µs 36.639µs 36.701µs 36.766µs 36.865µs 0.75% 1.169 2.737 0.15% 0.004µs 1 200
normalization/normalize_service/normalize_service/[empty string] throughput 27125731.501op/s 27321119.996op/s ± 42072.654op/s 27328080.397op/s ± 24986.887op/s 27349530.406op/s 27380101.848op/s 27393256.424op/s 27395044.581op/s 0.25% -1.154 2.670 0.15% 2974.986op/s 1 200
normalization/normalize_service/normalize_service/test_ASCII execution_time 45.924µs 46.045µs ± 0.052µs 46.043µs ± 0.034µs 46.075µs 46.128µs 46.188µs 46.244µs 0.44% 0.599 0.722 0.11% 0.004µs 1 200
normalization/normalize_service/normalize_service/test_ASCII throughput 21624349.017op/s 21717958.672op/s ± 24425.461op/s 21718610.547op/s ± 16243.793op/s 21735418.613op/s 21753014.007op/s 21763044.869op/s 21774974.989op/s 0.26% -0.592 0.703 0.11% 1727.141op/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 [536.478µs; 536.841µs] or [-0.034%; +0.034%] None None None
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000... throughput [1862761.474op/s; 1864019.287op/s] or [-0.034%; +0.034%] None None None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて execution_time [381.716µs; 381.798µs] or [-0.011%; +0.011%] None None None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて throughput [2619184.957op/s; 2619747.299op/s] or [-0.011%; +0.011%] None None None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters execution_time [189.806µs; 189.885µs] or [-0.021%; +0.021%] None None None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters throughput [5266347.737op/s; 5268537.238op/s] or [-0.021%; +0.021%] None None None
normalization/normalize_service/normalize_service/[empty string] execution_time [36.594µs; 36.610µs] or [-0.021%; +0.021%] None None None
normalization/normalize_service/normalize_service/[empty string] throughput [27315289.131op/s; 27326950.862op/s] or [-0.021%; +0.021%] None None None
normalization/normalize_service/normalize_service/test_ASCII execution_time [46.038µs; 46.052µs] or [-0.016%; +0.016%] None None None
normalization/normalize_service/normalize_service/test_ASCII throughput [21714573.538op/s; 21721343.806op/s] or [-0.016%; +0.016%] None None None

Group 6

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 84cf815 1770369521 dubloom/process-tags-telemetry
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 10.609ms 10.637ms ± 0.014ms 10.636ms ± 0.009ms 10.645ms 10.661ms 10.676ms 10.687ms 0.48% 0.697 0.736 0.13% 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 [10.635ms; 10.639ms] or [-0.018%; +0.018%] None None None

Group 7

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 84cf815 1770369521 dubloom/process-tags-telemetry
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 47.904ms 48.422ms ± 0.644ms 48.324ms ± 0.077ms 48.416ms 48.548ms 50.595ms 55.124ms 14.07% 7.735 68.512 1.33% 0.046ms 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 [48.332ms; 48.511ms] or [-0.184%; +0.184%] None None None

Group 8

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 84cf815 1770369521 dubloom/process-tags-telemetry
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 85.609µs 86.334µs ± 0.386µs 86.555µs ± 0.250µs 86.671µs 86.799µs 86.926µs 87.134µs 0.67% -0.184 -1.593 0.45% 0.027µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
sql/obfuscate_sql_string execution_time [86.281µs; 86.388µs] or [-0.062%; +0.062%] None None None

Group 9

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 84cf815 1770369521 dubloom/process-tags-telemetry
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 242.812ns 253.783ns ± 14.456ns 245.735ns ± 1.824ns 264.543ns 286.174ns 289.235ns 289.430ns 17.78% 1.291 0.072 5.68% 1.022ns 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 [251.780ns; 255.786ns] or [-0.789%; +0.789%] None None None

Group 10

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 84cf815 1770369521 dubloom/process-tags-telemetry
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 4.994µs 5.066µs ± 0.045µs 5.059µs ± 0.030µs 5.089µs 5.144µs 5.148µs 5.156µs 1.91% 0.241 -1.000 0.88% 0.003µs 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 [5.060µs; 5.072µs] or [-0.122%; +0.122%] None None None

Group 11

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 84cf815 1770369521 dubloom/process-tags-telemetry
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 34.327µs 34.731µs ± 0.592µs 34.481µs ± 0.056µs 34.578µs 35.853µs 35.959µs 38.759µs 12.41% 2.622 9.960 1.70% 0.042µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
redis/obfuscate_redis_string execution_time [34.649µs; 34.813µs] or [-0.236%; +0.236%] None None None

Group 12

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 84cf815 1770369521 dubloom/process-tags-telemetry
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 9.544ms 9.850ms ± 0.078ms 9.855ms ± 0.032ms 9.888ms 9.947ms 10.081ms 10.111ms 2.60% -0.546 3.263 0.79% 0.005ms 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 [9.839ms; 9.860ms] or [-0.109%; +0.109%] None None None

Group 13

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 84cf815 1770369521 dubloom/process-tags-telemetry
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 3.968ms 3.973ms ± 0.007ms 3.972ms ± 0.002ms 3.974ms 3.976ms 3.980ms 4.063ms 2.29% 11.834 154.609 0.17% 0.000ms 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 [3.972ms; 3.974ms] or [-0.024%; +0.024%] None None None

Group 14

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 84cf815 1770369521 dubloom/process-tags-telemetry
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 204.545µs 205.394µs ± 0.500µs 205.347µs ± 0.390µs 205.753µs 206.201µs 206.377µs 207.186µs 0.90% 0.450 -0.301 0.24% 0.035µs 1 200
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... throughput 4826582.835op/s 4868728.486op/s ± 11832.271op/s 4869814.076op/s ± 9254.343op/s 4877701.040op/s 4885415.743op/s 4887878.307op/s 4888909.443op/s 0.39% -0.440 -0.326 0.24% 836.668op/s 1 200
normalization/normalize_name/normalize_name/bad-name execution_time 18.582µs 18.648µs ± 0.061µs 18.630µs ± 0.026µs 18.662µs 18.787µs 18.826µs 19.009µs 2.03% 2.152 6.638 0.32% 0.004µs 1 200
normalization/normalize_name/normalize_name/bad-name throughput 52607809.228op/s 53626814.191op/s ± 173314.600op/s 53677500.186op/s ± 76168.615op/s 53740681.649op/s 53796703.489op/s 53809139.893op/s 53814784.107op/s 0.26% -2.113 6.349 0.32% 12255.193op/s 1 200
normalization/normalize_name/normalize_name/good execution_time 10.784µs 10.866µs ± 0.030µs 10.865µs ± 0.019µs 10.885µs 10.919µs 10.940µs 10.995µs 1.20% 0.485 1.538 0.27% 0.002µs 1 200
normalization/normalize_name/normalize_name/good throughput 90948727.134op/s 92032118.076op/s ± 252912.020op/s 92041663.256op/s ± 159880.882op/s 92192135.707op/s 92401187.336op/s 92659133.880op/s 92733449.380op/s 0.75% -0.458 1.480 0.27% 17883.580op/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 [205.324µs; 205.463µs] or [-0.034%; +0.034%] None None None
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... throughput [4867088.647op/s; 4870368.325op/s] or [-0.034%; +0.034%] None None None
normalization/normalize_name/normalize_name/bad-name execution_time [18.639µs; 18.656µs] or [-0.045%; +0.045%] None None None
normalization/normalize_name/normalize_name/bad-name throughput [53602794.454op/s; 53650833.928op/s] or [-0.045%; +0.045%] None None None
normalization/normalize_name/normalize_name/good execution_time [10.862µs; 10.870µs] or [-0.038%; +0.038%] None None None
normalization/normalize_name/normalize_name/good throughput [91997066.902op/s; 92067169.249op/s] or [-0.038%; +0.038%] None None None

Group 15

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 84cf815 1770369521 dubloom/process-tags-telemetry
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 17.690µs 25.555µs ± 9.227µs 18.016µs ± 0.165µs 33.679µs 41.827µs 45.156µs 66.796µs 270.76% 0.857 0.438 36.02% 0.652µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
two way interface execution_time [24.277µs; 26.834µs] or [-5.004%; +5.004%] None None None

Group 16

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 84cf815 1770369521 dubloom/process-tags-telemetry
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 2.438µs 2.460µs ± 0.028µs 2.455µs ± 0.005µs 2.460µs 2.505µs 2.508µs 2.783µs 13.40% 7.963 84.301 1.15% 0.002µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
tags/replace_trace_tags execution_time [2.456µs; 2.464µs] or [-0.159%; +0.159%] None None None

Group 17

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 84cf815 1770369521 dubloom/process-tags-telemetry
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 14.005ms 14.071ms ± 0.036ms 14.066ms ± 0.014ms 14.079ms 14.135ms 14.233ms 14.250ms 1.31% 2.305 7.804 0.25% 0.003ms 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 [14.066ms; 14.076ms] or [-0.035%; +0.035%] None None None

Group 18

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 84cf815 1770369521 dubloom/process-tags-telemetry
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 3.897µs 3.912µs ± 0.003µs 3.912µs ± 0.002µs 3.914µs 3.916µs 3.918µs 3.918µs 0.14% -0.826 4.502 0.07% 0.000µs 1 200
credit_card/is_card_number/ throughput 255238019.185op/s 255597531.088op/s ± 167851.867op/s 255600085.928op/s ± 115689.964op/s 255709148.004op/s 255849156.234op/s 255933595.522op/s 256576027.531op/s 0.38% 0.837 4.571 0.07% 11868.919op/s 1 200
credit_card/is_card_number/ 3782-8224-6310-005 execution_time 77.044µs 77.629µs ± 0.531µs 77.438µs ± 0.307µs 77.963µs 78.720µs 78.917µs 79.684µs 2.90% 1.157 1.170 0.68% 0.038µs 1 200
credit_card/is_card_number/ 3782-8224-6310-005 throughput 12549568.382op/s 12882330.120op/s ± 87420.861op/s 12913634.901op/s ± 51268.383op/s 12957491.330op/s 12974348.351op/s 12979280.513op/s 12979673.831op/s 0.51% -1.120 1.023 0.68% 6181.588op/s 1 200
credit_card/is_card_number/ 378282246310005 execution_time 70.619µs 70.884µs ± 0.326µs 70.736µs ± 0.058µs 70.962µs 71.701µs 72.162µs 72.308µs 2.22% 2.248 5.076 0.46% 0.023µs 1 200
credit_card/is_card_number/ 378282246310005 throughput 13829664.631op/s 14107942.549op/s ± 64217.905op/s 14137048.964op/s ± 11618.917op/s 14144980.330op/s 14154677.681op/s 14158097.173op/s 14160487.940op/s 0.17% -2.220 4.919 0.45% 4540.892op/s 1 200
credit_card/is_card_number/37828224631 execution_time 3.892µs 3.913µs ± 0.008µs 3.912µs ± 0.001µs 3.913µs 3.919µs 3.923µs 3.985µs 1.88% 7.568 66.967 0.20% 0.001µs 1 200
credit_card/is_card_number/37828224631 throughput 250938244.942op/s 255585158.305op/s ± 507304.338op/s 255655374.954op/s ± 86804.911op/s 255741162.729op/s 255857283.693op/s 255939596.526op/s 256924755.424op/s 0.50% -7.497 66.171 0.20% 35871.834op/s 1 200
credit_card/is_card_number/378282246310005 execution_time 67.438µs 67.792µs ± 0.368µs 67.695µs ± 0.090µs 67.849µs 68.382µs 69.202µs 70.852µs 4.66% 4.281 26.628 0.54% 0.026µs 1 200
credit_card/is_card_number/378282246310005 throughput 14114025.880op/s 14751530.064op/s ± 78247.353op/s 14772226.737op/s ± 19536.970op/s 14786590.062op/s 14815826.192op/s 14826199.780op/s 14828467.692op/s 0.38% -4.120 24.742 0.53% 5532.923op/s 1 200
credit_card/is_card_number/37828224631000521389798 execution_time 44.784µs 45.244µs ± 0.142µs 45.242µs ± 0.098µs 45.345µs 45.465µs 45.514µs 45.525µs 0.63% -0.364 -0.044 0.31% 0.010µs 1 200
credit_card/is_card_number/37828224631000521389798 throughput 21965798.460op/s 22102655.607op/s ± 69418.322op/s 22103213.351op/s ± 47725.320op/s 22145226.007op/s 22217149.986op/s 22263872.148op/s 22329549.346op/s 1.02% 0.382 -0.015 0.31% 4908.617op/s 1 200
credit_card/is_card_number/x371413321323331 execution_time 6.028µs 6.035µs ± 0.006µs 6.034µs ± 0.002µs 6.036µs 6.043µs 6.048µs 6.102µs 1.14% 7.253 76.051 0.10% 0.000µs 1 200
credit_card/is_card_number/x371413321323331 throughput 163871067.787op/s 165708410.699op/s ± 165243.861op/s 165740565.005op/s ± 57948.155op/s 165787676.816op/s 165839070.157op/s 165869891.428op/s 165889013.942op/s 0.09% -7.177 74.867 0.10% 11684.505op/s 1 200
credit_card/is_card_number_no_luhn/ execution_time 3.896µs 3.912µs ± 0.003µs 3.912µs ± 0.001µs 3.913µs 3.916µs 3.918µs 3.918µs 0.17% -0.838 6.618 0.07% 0.000µs 1 200
credit_card/is_card_number_no_luhn/ throughput 255215696.205op/s 255629006.396op/s ± 167157.884op/s 255639930.958op/s ± 91814.708op/s 255725893.862op/s 255861918.219op/s 255933893.161op/s 256675057.812op/s 0.40% 0.854 6.715 0.07% 11819.847op/s 1 200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 execution_time 65.026µs 65.731µs ± 0.137µs 65.758µs ± 0.051µs 65.799µs 65.873µs 65.911µs 65.934µs 0.27% -2.863 10.548 0.21% 0.010µs 1 200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 throughput 15166689.400op/s 15213478.595op/s ± 31884.927op/s 15207368.733op/s ± 11772.417op/s 15220581.270op/s 15248969.551op/s 15356439.227op/s 15378409.543op/s 1.12% 2.890 10.698 0.21% 2254.605op/s 1 200
credit_card/is_card_number_no_luhn/ 378282246310005 execution_time 52.944µs 53.017µs ± 0.040µs 53.009µs ± 0.020µs 53.031µs 53.106µs 53.141µs 53.153µs 0.27% 1.238 1.715 0.08% 0.003µs 1 200
credit_card/is_card_number_no_luhn/ 378282246310005 throughput 18813649.113op/s 18861773.445op/s ± 14209.551op/s 18864710.729op/s ± 6983.815op/s 18870393.767op/s 18880359.234op/s 18883406.284op/s 18887960.814op/s 0.12% -1.234 1.701 0.08% 1004.767op/s 1 200
credit_card/is_card_number_no_luhn/37828224631 execution_time 3.895µs 3.913µs ± 0.003µs 3.913µs ± 0.002µs 3.915µs 3.917µs 3.920µs 3.930µs 0.43% 0.012 9.889 0.08% 0.000µs 1 200
credit_card/is_card_number_no_luhn/37828224631 throughput 254471875.282op/s 255561933.796op/s ± 195860.740op/s 255567364.073op/s ± 119168.112op/s 255684606.037op/s 255811430.706op/s 255863781.238op/s 256738145.874op/s 0.46% 0.015 9.918 0.08% 13849.446op/s 1 200
credit_card/is_card_number_no_luhn/378282246310005 execution_time 49.762µs 49.852µs ± 0.042µs 49.854µs ± 0.031µs 49.883µs 49.927µs 49.946µs 49.959µs 0.21% 0.046 -0.436 0.09% 0.003µs 1 200
credit_card/is_card_number_no_luhn/378282246310005 throughput 20016267.948op/s 20059257.990op/s ± 17097.704op/s 20058434.912op/s ± 12427.215op/s 20070990.395op/s 20086675.107op/s 20094278.054op/s 20095803.996op/s 0.19% -0.042 -0.438 0.09% 1208.990op/s 1 200
credit_card/is_card_number_no_luhn/37828224631000521389798 execution_time 44.732µs 45.191µs ± 0.155µs 45.205µs ± 0.107µs 45.308µs 45.411µs 45.491µs 45.514µs 0.68% -0.341 -0.180 0.34% 0.011µs 1 200
credit_card/is_card_number_no_luhn/37828224631000521389798 throughput 21971226.798op/s 22128452.187op/s ± 76169.254op/s 22121672.689op/s ± 52618.602op/s 22177717.495op/s 22261638.811op/s 22316456.513op/s 22355572.429op/s 1.06% 0.359 -0.158 0.34% 5385.980op/s 1 200
credit_card/is_card_number_no_luhn/x371413321323331 execution_time 6.028µs 6.034µs ± 0.003µs 6.034µs ± 0.002µs 6.036µs 6.040µs 6.044µs 6.048µs 0.23% 0.959 2.029 0.05% 0.000µs 1 200
credit_card/is_card_number_no_luhn/x371413321323331 throughput 165342711.662op/s 165721055.585op/s ± 90685.666op/s 165731014.466op/s ± 49764.921op/s 165775784.302op/s 165854341.346op/s 165889070.819op/s 165904735.660op/s 0.10% -0.954 2.014 0.05% 6412.445op/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; 3.913µs] or [-0.009%; +0.009%] None None None
credit_card/is_card_number/ throughput [255574268.434op/s; 255620793.743op/s] or [-0.009%; +0.009%] None None None
credit_card/is_card_number/ 3782-8224-6310-005 execution_time [77.556µs; 77.703µs] or [-0.095%; +0.095%] None None None
credit_card/is_card_number/ 3782-8224-6310-005 throughput [12870214.430op/s; 12894445.811op/s] or [-0.094%; +0.094%] None None None
credit_card/is_card_number/ 378282246310005 execution_time [70.838µs; 70.929µs] or [-0.064%; +0.064%] None None None
credit_card/is_card_number/ 378282246310005 throughput [14099042.565op/s; 14116842.533op/s] or [-0.063%; +0.063%] None None None
credit_card/is_card_number/37828224631 execution_time [3.912µs; 3.914µs] or [-0.028%; +0.028%] None None None
credit_card/is_card_number/37828224631 throughput [255514850.803op/s; 255655465.807op/s] or [-0.028%; +0.028%] None None None
credit_card/is_card_number/378282246310005 execution_time [67.741µs; 67.842µs] or [-0.075%; +0.075%] None None None
credit_card/is_card_number/378282246310005 throughput [14740685.734op/s; 14762374.395op/s] or [-0.074%; +0.074%] None None None
credit_card/is_card_number/37828224631000521389798 execution_time [45.224µs; 45.264µs] or [-0.043%; +0.043%] None None None
credit_card/is_card_number/37828224631000521389798 throughput [22093034.895op/s; 22112276.319op/s] or [-0.044%; +0.044%] None None None
credit_card/is_card_number/x371413321323331 execution_time [6.034µs; 6.036µs] or [-0.014%; +0.014%] None None None
credit_card/is_card_number/x371413321323331 throughput [165685509.489op/s; 165731311.909op/s] or [-0.014%; +0.014%] None None None
credit_card/is_card_number_no_luhn/ execution_time [3.912µs; 3.912µs] or [-0.009%; +0.009%] None None None
credit_card/is_card_number_no_luhn/ throughput [255605839.921op/s; 255652172.871op/s] or [-0.009%; +0.009%] None None None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 execution_time [65.712µs; 65.750µs] or [-0.029%; +0.029%] None None None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 throughput [15209059.651op/s; 15217897.540op/s] or [-0.029%; +0.029%] None None None
credit_card/is_card_number_no_luhn/ 378282246310005 execution_time [53.012µs; 53.023µs] or [-0.010%; +0.010%] None None None
credit_card/is_card_number_no_luhn/ 378282246310005 throughput [18859804.138op/s; 18863742.752op/s] or [-0.010%; +0.010%] None None None
credit_card/is_card_number_no_luhn/37828224631 execution_time [3.913µs; 3.913µs] or [-0.011%; +0.011%] None None None
credit_card/is_card_number_no_luhn/37828224631 throughput [255534789.381op/s; 255589078.211op/s] or [-0.011%; +0.011%] None None None
credit_card/is_card_number_no_luhn/378282246310005 execution_time [49.846µs; 49.858µs] or [-0.012%; +0.012%] None None None
credit_card/is_card_number_no_luhn/378282246310005 throughput [20056888.412op/s; 20061627.567op/s] or [-0.012%; +0.012%] None None None
credit_card/is_card_number_no_luhn/37828224631000521389798 execution_time [45.170µs; 45.213µs] or [-0.048%; +0.048%] None None None
credit_card/is_card_number_no_luhn/37828224631000521389798 throughput [22117895.861op/s; 22139008.513op/s] or [-0.048%; +0.048%] None None None
credit_card/is_card_number_no_luhn/x371413321323331 execution_time [6.034µs; 6.035µs] or [-0.008%; +0.008%] None None None
credit_card/is_card_number_no_luhn/x371413321323331 throughput [165708487.424op/s; 165733623.746op/s] or [-0.008%; +0.008%] None None None

Group 19

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 84cf815 1770369521 dubloom/process-tags-telemetry
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 160.264µs 161.176µs ± 0.270µs 161.117µs ± 0.140µs 161.297µs 161.691µs 161.952µs 162.441µs 0.82% 1.013 3.594 0.17% 0.019µs 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 [161.139µs; 161.214µs] or [-0.023%; +0.023%] None None None

Baseline

Omitted due to size.

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codecov-commenter commented Jan 20, 2026 •
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Codecov Report

❌ Patch coverage is 0% with 47 lines in your changes missing coverage. Please review.
✅ Project coverage is 71.16%. Comparing base (f483c69) to head (84cf815).

Additional details and impacted files 
@@            Coverage Diff             @@
##             main    #1459      +/-   ##
==========================================
- Coverage   71.20%   71.16%   -0.04%     
==========================================
  Files         424      424              
  Lines       69802    69849      +47     
==========================================
+ Hits        49700    49706       +6     
- Misses      20102    20143      +41
Components Coverage Δ
libdd-crashtracker 62.36% <ø> (ø)
libdd-crashtracker-ffi 16.80% <ø> (ø)
libdd-alloc 98.73% <ø> (ø)
libdd-data-pipeline 86.86% <ø> (ø)
libdd-data-pipeline-ffi 78.68% <ø> (ø)
libdd-common 80.58% <ø> (ø)
libdd-common-ffi 74.54% <ø> (ø)
libdd-telemetry 65.06% <ø> (-0.03%) ⬇️
libdd-telemetry-ffi 21.17% <ø> (ø)
libdd-dogstatsd-client 83.75% <ø> (ø)
datadog-ipc 82.60% <ø> (ø)
libdd-profiling 81.73% <ø> (ø)
libdd-profiling-ffi 64.71% <ø> (ø)
datadog-sidecar 34.13% <0.00%> (-0.26%) ⬇️
datdog-sidecar-ffi 7.59% <0.00%> (-0.08%) ⬇️
spawn-worker 55.18% <ø> (ø)
libdd-tinybytes 93.43% <ø> (ø)
libdd-trace-normalization 82.33% <ø> (ø)
libdd-trace-obfuscation 94.17% <ø> (ø)
libdd-trace-protobuf 61.18% <ø> (ø)
libdd-trace-utils 89.37% <ø> (ø)
datadog-tracer-flare 62.06% <ø> (ø)
libdd-log 75.57% <ø> (ø)
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@dubloom dubloom force-pushed the dubloom/process-tags-telemetry branch from 5d8673a to 3b283c5 Compare January 20, 2026 10:26
@dubloom dubloom changed the title add process_tags to Application in telemetry feat(telemetry): add process_tags to Application in telemetry Jan 20, 2026
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Artifact Size Benchmark Report

aarch64-alpine-linux-musl
Artifact Baseline Commit Change
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.a 91.81 MB 91.81 MB +0% (+1.35 KB) 👌
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.so 8.00 MB 8.00 MB 0% (0 B) 👌
aarch64-apple-darwin
Artifact Baseline Commit Change
/aarch64-apple-darwin/lib/libdatadog_profiling.a 63.03 MB 63.03 MB +0% (+1.24 KB) 👌
/aarch64-apple-darwin/lib/libdatadog_profiling.dylib 9.20 MB 9.20 MB 0% (0 B) 👌
aarch64-unknown-linux-gnu
Artifact Baseline Commit Change
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.so 10.37 MB 10.37 MB 0% (0 B) 👌
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.a 106.16 MB 106.16 MB -0% (-2.80 KB) 👌
libdatadog-x64-windows
Artifact Baseline Commit Change
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.dll 24.71 MB 24.72 MB +0% (+2.00 KB) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.lib 76.33 KB 76.33 KB 0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.pdb 164.58 MB 164.58 MB 0% (0 B) 👌
/libdatadog-x64-windows/debug/static/datadog_profiling_ffi.lib 811.95 MB 811.95 MB +0% (+5.90 KB) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.dll 9.31 MB 9.31 MB 0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.lib 76.33 KB 76.33 KB 0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.pdb 22.93 MB 22.93 MB 0% (0 B) 👌
/libdatadog-x64-windows/release/static/datadog_profiling_ffi.lib 48.32 MB 48.32 MB +0% (+204 B) 👌
libdatadog-x86-windows
Artifact Baseline Commit Change
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.dll 20.82 MB 20.82 MB +0% (+1.00 KB) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.lib 77.50 KB 77.50 KB 0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.pdb 168.38 MB 168.40 MB +0% (+16.00 KB) 👌
/libdatadog-x86-windows/debug/static/datadog_profiling_ffi.lib 798.69 MB 798.69 MB +0% (+4.98 KB) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.dll 7.03 MB 7.03 MB 0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.lib 77.50 KB 77.50 KB 0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.pdb 24.48 MB 24.48 MB 0% (0 B) 👌
/libdatadog-x86-windows/release/static/datadog_profiling_ffi.lib 44.00 MB 44.00 MB +0% (+470 B) 👌
x86_64-alpine-linux-musl
Artifact Baseline Commit Change
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.a 79.91 MB 79.91 MB +0% (+3.10 KB) 👌
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.so 9.51 MB 9.51 MB 0% (0 B) 👌
x86_64-apple-darwin
Artifact Baseline Commit Change
/x86_64-apple-darwin/lib/libdatadog_profiling.a 64.40 MB 64.40 MB +0% (+600 B) 👌
/x86_64-apple-darwin/lib/libdatadog_profiling.dylib 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 99.86 MB 99.87 MB +0% (+5.64 KB) 👌
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.so 11.08 MB 11.08 MB 0% (0 B) 👌

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📚 Documentation Check Results

⚠️ 465 documentation warning(s) found

📦 libdd-telemetry - 465 warning(s)

Updated: 2026-02-06 09:19:53 UTC | Commit: 32e75d7 | missing-docs job results

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🔒 Cargo Deny Results

⚠️ 7 issue(s) found, showing only errors (advisories, bans, sources)

📦 libdd-telemetry - 7 error(s)

Show output 
error[vulnerability]: Integer overflow in `BytesMut::reserve`
   ┌─ /home/runner/work/libdatadog/libdatadog/Cargo.lock:19:1
   │
19 │ bytes 1.8.0 registry+https://github.com/rust-lang/crates.io-index
   │ ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ security vulnerability detected
   │
   ├ ID: RUSTSEC-2026-0007
   ├ Advisory: https://rustsec.org/advisories/RUSTSEC-2026-0007
   ├ In the unique reclaim path of `BytesMut::reserve`, the condition
     ```rs
     if v_capacity >= new_cap + offset
     ```
     uses an unchecked addition. When `new_cap + offset` overflows `usize` in release builds, this condition may incorrectly pass, causing `self.cap` to be set to a value that exceeds the actual allocated capacity. Subsequent APIs such as `spare_capacity_mut()` then trust this corrupted `cap` value and may create out-of-bounds slices, leading to UB.
     
     This behavior is observable in release builds (integer overflow wraps), whereas debug builds panic due to overflow checks.
     
     ## PoC
     
     ```rs
     use bytes::*;
     
     fn main() {
         let mut a = BytesMut::from(&b"hello world"[..]);
         let mut b = a.split_off(5);
     
         // Ensure b becomes the unique owner of the backing storage
         drop(a);
     
         // Trigger overflow in new_cap + offset inside reserve
         b.reserve(usize::MAX - 6);
     
         // This call relies on the corrupted cap and may cause UB & HBO
         b.put_u8(b'h');
     }
     ```
     
     # Workarounds
     
     Users of `BytesMut::reserve` are only affected if integer overflow checks are configured to wrap. When integer overflow is configured to panic, this issue does not apply.
   ├ Announcement: https://github.com/advisories/GHSA-434x-w66g-qw3r
   ├ Solution: Upgrade to >=1.11.1 (try `cargo update -p bytes`)
   ├ bytes v1.8.0
     ├── http v1.1.0
     │   ├── http-body v1.0.1
     │   │   ├── http-body-util v0.1.2
     │   │   │   ├── libdd-common v1.1.0
     │   │   │   │   └── libdd-telemetry v2.0.0
     │   │   │   └── libdd-telemetry v2.0.0 (*)
     │   │   ├── hyper v1.6.0
     │   │   │   ├── hyper-rustls v0.27.3
     │   │   │   │   └── libdd-common v1.1.0 (*)
     │   │   │   ├── hyper-util v0.1.17
     │   │   │   │   ├── hyper-rustls v0.27.3 (*)
     │   │   │   │   ├── libdd-common v1.1.0 (*)
     │   │   │   │   └── libdd-telemetry v2.0.0 (*)
     │   │   │   ├── libdd-common v1.1.0 (*)
     │   │   │   └── libdd-telemetry v2.0.0 (*)
     │   │   ├── hyper-util v0.1.17 (*)
     │   │   └── libdd-common v1.1.0 (*)
     │   ├── http-body-util v0.1.2 (*)
     │   ├── hyper v1.6.0 (*)
     │   ├── hyper-rustls v0.27.3 (*)
     │   ├── hyper-util v0.1.17 (*)
     │   ├── libdd-common v1.1.0 (*)
     │   └── libdd-telemetry v2.0.0 (*)
     ├── http-body v1.0.1 (*)
     ├── http-body-util v0.1.2 (*)
     ├── hyper v1.6.0 (*)
     ├── hyper-util v0.1.17 (*)
     ├── prost v0.14.3
     │   └── libdd-ddsketch v1.0.0
     │       └── libdd-telemetry v2.0.0 (*)
     ├── tokio v1.49.0
     │   ├── hyper v1.6.0 (*)
     │   ├── hyper-rustls v0.27.3 (*)
     │   ├── hyper-util v0.1.17 (*)
     │   ├── (dev) libdd-common v1.1.0 (*)
     │   ├── (dev) libdd-telemetry v2.0.0 (*)
     │   ├── tokio-rustls v0.26.0
     │   │   ├── hyper-rustls v0.27.3 (*)
     │   │   └── libdd-common v1.1.0 (*)
     │   └── tokio-util v0.7.12
     │       └── libdd-telemetry v2.0.0 (*)
     └── tokio-util v0.7.12 (*)

error[vulnerability]: Lenient `hyper` header parsing of `Content-Length` could allow request smuggling
   ┌─ /home/runner/work/libdatadog/libdatadog/Cargo.lock:64:1
   │
64 │ hyper 0.10.16 registry+https://github.com/rust-lang/crates.io-index
   │ ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ security vulnerability detected
   │
   ├ ID: RUSTSEC-2021-0078
   ├ Advisory: https://rustsec.org/advisories/RUSTSEC-2021-0078
   ├ `hyper`'s HTTP header parser accepted, according to RFC 7230, illegal contents inside `Content-Length` headers.
     Due to this, upstream HTTP proxies that ignore the header may still forward them along if it chooses to ignore the error.
     
     To be vulnerable, `hyper` must be used as an HTTP/1 server and using an HTTP proxy upstream that ignores the header's contents
     but still forwards it. Due to all the factors that must line up, an attack exploiting this vulnerability is unlikely.
   ├ Announcement: https://github.com/hyperium/hyper/security/advisories/GHSA-f3pg-qwvg-p99c
   ├ Solution: Upgrade to >=0.14.10 (try `cargo update -p hyper`)
   ├ hyper v0.10.16
     ├── iron v0.6.1
     │   └── multipart v0.18.0
     │       └── (dev) libdd-common v1.1.0
     │           └── libdd-telemetry v2.0.0
     ├── multipart v0.18.0 (*)
     └── nickel v0.11.0
         └── multipart v0.18.0 (*)

error[vulnerability]: Integer overflow in `hyper`'s parsing of the `Transfer-Encoding` header leads to data loss
   ┌─ /home/runner/work/libdatadog/libdatadog/Cargo.lock:64:1
   │
64 │ hyper 0.10.16 registry+https://github.com/rust-lang/crates.io-index
   │ ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ security vulnerability detected
   │
   ├ ID: RUSTSEC-2021-0079
   ├ Advisory: https://rustsec.org/advisories/RUSTSEC-2021-0079
   ├ When decoding chunk sizes that are too large, `hyper`'s code would encounter an integer overflow. Depending on the situation,
     this could lead to data loss from an incorrect total size, or in rarer cases, a request smuggling attack.
     
     To be vulnerable, you must be using `hyper` for any HTTP/1 purpose, including as a client or server, and consumers must send
     requests or responses that specify a chunk size greater than 18 exabytes. For a possible request smuggling attack to be possible,
     any upstream proxies must accept a chunk size greater than 64 bits.
   ├ Announcement: https://github.com/hyperium/hyper/security/advisories/GHSA-5h46-h7hh-c6x9
   ├ Solution: Upgrade to >=0.14.10 (try `cargo update -p hyper`)
   ├ hyper v0.10.16
     ├── iron v0.6.1
     │   └── multipart v0.18.0
     │       └── (dev) libdd-common v1.1.0
     │           └── libdd-telemetry v2.0.0
     ├── multipart v0.18.0 (*)
     └── nickel v0.11.0
         └── multipart v0.18.0 (*)

error[vulnerability]: `idna` accepts Punycode labels that do not produce any non-ASCII when decoded
   ┌─ /home/runner/work/libdatadog/libdatadog/Cargo.lock:70:1
   │
70 │ idna 0.1.5 registry+https://github.com/rust-lang/crates.io-index
   │ ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ security vulnerability detected
   │
   ├ ID: RUSTSEC-2024-0421
   ├ Advisory: https://rustsec.org/advisories/RUSTSEC-2024-0421
   ├ `idna` 0.5.0 and earlier accepts Punycode labels that do not produce any non-ASCII output, which means that either ASCII labels or the empty root label can be masked such that they appear unequal without IDNA processing or when processed with a different implementation and equal when processed with `idna` 0.5.0 or earlier.
     
     Concretely, `example.org` and `xn--example-.org` become equal after processing by `idna` 0.5.0 or earlier. Also, `example.org.xn--` and `example.org.` become equal after processing by `idna` 0.5.0 or earlier.
     
     In applications using `idna` (but not in `idna` itself) this may be able to lead to privilege escalation when host name comparison is part of a privilege check and the behavior is combined with a client that resolves domains with such labels instead of treating them as errors that preclude DNS resolution / URL fetching and with the attacker managing to introduce a DNS entry (and TLS certificate) for an `xn--`-masked name that turns into the name of the target when processed by `idna` 0.5.0 or earlier.
     
     ## Remedy
     
     Upgrade to `idna` 1.0.3 or later, if depending on `idna` directly, or to `url` 2.5.4 or later, if depending on `idna` via `url`. (This issue was fixed in `idna` 1.0.0, but versions earlier than 1.0.3 are not recommended for other reasons.)
     
     When upgrading, please take a moment to read about [alternative Unicode back ends for `idna`](https://docs.rs/crate/idna_adapter/latest).
     
     If you are using Rust earlier than 1.81 in combination with SQLx 0.8.2 or earlier, please also read an [issue](https://github.com/servo/rust-url/issues/992) about combining them with `url` 2.5.4 and `idna` 1.0.3.
     
     ## Additional information
     
     This issue resulted from `idna` 0.5.0 and earlier implementing the UTS 46 specification literally on this point and the specification having this bug. The specification bug has been fixed in [revision 33 of UTS 46](https://www.unicode.org/reports/tr46/tr46-33.html#Modifications).
     
     ## Acknowledgements
     
     Thanks to kageshiron for recognizing the security implications of this behavior.
   ├ Announcement: https://bugzilla.mozilla.org/show_bug.cgi?id=1887898
   ├ Solution: Upgrade to >=1.0.0 (try `cargo update -p idna`)
   ├ idna v0.1.5
     └── url v1.7.2
         ├── hyper v0.10.16
         │   ├── iron v0.6.1
         │   │   └── multipart v0.18.0
         │   │       └── (dev) libdd-common v1.1.0
         │   │           └── libdd-telemetry v2.0.0
         │   ├── multipart v0.18.0 (*)
         │   └── nickel v0.11.0
         │       └── multipart v0.18.0 (*)
         ├── iron v0.6.1 (*)
         ├── nickel v0.11.0 (*)
         └── tiny_http v0.6.4
             └── multipart v0.18.0 (*)

error[unmaintained]: multipart is Unmaintained
   ┌─ /home/runner/work/libdatadog/libdatadog/Cargo.lock:99:1
   │
99 │ multipart 0.18.0 registry+https://github.com/rust-lang/crates.io-index
   │ ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ unmaintained advisory detected
   │
   ├ ID: RUSTSEC-2023-0050
   ├ Advisory: https://rustsec.org/advisories/RUSTSEC-2023-0050
   ├ The `multipart` crate is unmaintained. The author has archived the github
     repository.
     
     Alternatives:
     
     - [multer](https://crates.io/crates/multer)
     - [multiparty](https://crates.io/crates/multiparty)
   ├ Solution: No safe upgrade is available!
   ├ multipart v0.18.0
     └── (dev) libdd-common v1.1.0
         └── libdd-telemetry v2.0.0

error[vulnerability]: Potential segfault in the time crate
    ┌─ /home/runner/work/libdatadog/libdatadog/Cargo.lock:177:1
    │
177 │ time 0.1.45 registry+https://github.com/rust-lang/crates.io-index
    │ ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ security vulnerability detected
    │
    ├ ID: RUSTSEC-2020-0071
    ├ Advisory: https://rustsec.org/advisories/RUSTSEC-2020-0071
    ├ ### Impact
      
      The affected functions set environment variables without synchronization. On Unix-like operating systems, this can crash in multithreaded programs. Programs may segfault due to dereferencing a dangling pointer if an environment variable is read in a different thread than the affected functions. This may occur without the user's knowledge, notably in the Rust standard library or third-party libraries.
      
      The affected functions from time 0.2.7 through 0.2.22 are:
      
      - `time::UtcOffset::local_offset_at`
      - `time::UtcOffset::try_local_offset_at`
      - `time::UtcOffset::current_local_offset`
      - `time::UtcOffset::try_current_local_offset`
      - `time::OffsetDateTime::now_local`
      - `time::OffsetDateTime::try_now_local`
      
      The affected functions in time 0.1 (all versions) are:
      
      - `time::at_utc`
      - `time::at`
      - `time::now`
      - `time::tzset`
      
      Non-Unix targets (including Windows and wasm) are unaffected.
      
      ### Patches
      
      Pending a proper fix, the internal method that determines the local offset has been modified to always return `None` on the affected operating systems. This has the effect of returning an `Err` on the `try_*` methods and `UTC` on the non-`try_*` methods.
      
      Users and library authors with time in their dependency tree should perform `cargo update`, which will pull in the updated, unaffected code.
      
      Users of time 0.1 do not have a patch and should upgrade to an unaffected version: time 0.2.23 or greater or the 0.3 series.
      
      ### Workarounds
      
      A possible workaround for crates affected through the transitive dependency in `chrono`, is to avoid using the default `oldtime` feature dependency of the `chrono` crate by disabling its `default-features` and manually specifying the required features instead.
      
      #### Examples:
      
      `Cargo.toml`:  
      
      ```toml
      chrono = { version = "0.4", default-features = false, features = ["serde"] }
      ```
      
      ```toml
      chrono = { version = "0.4.22", default-features = false, features = ["clock"] }
      ```
      
      Commandline:  
      
      ```bash
      cargo add chrono --no-default-features -F clock
      ```
      
      Sources:  
       - [chronotope/chrono#602 (comment)](https://github.com/chronotope/chrono/issues/602#issuecomment-1242149249)  
       - [vityafx/serde-aux#21](https://github.com/vityafx/serde-aux/issues/21)
    ├ Announcement: https://github.com/time-rs/time/issues/293
    ├ Solution: Upgrade to >=0.2.23 (try `cargo update -p time`)
    ├ time v0.1.45
      ├── hyper v0.10.16
      │   ├── iron v0.6.1
      │   │   └── multipart v0.18.0
      │   │       └── (dev) libdd-common v1.1.0
      │   │           └── libdd-telemetry v2.0.0
      │   ├── multipart v0.18.0 (*)
      │   └── nickel v0.11.0
      │       └── multipart v0.18.0 (*)
      └── nickel v0.11.0 (*)

error[vulnerability]: Logging user input may result in poisoning logs with ANSI escape sequences
    ┌─ /home/runner/work/libdatadog/libdatadog/Cargo.lock:189:1
    │
189 │ tracing-subscriber 0.3.19 registry+https://github.com/rust-lang/crates.io-index
    │ ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ security vulnerability detected
    │
    ├ ID: RUSTSEC-2025-0055
    ├ Advisory: https://rustsec.org/advisories/RUSTSEC-2025-0055
    ├ Previous versions of tracing-subscriber were vulnerable to ANSI escape sequence injection attacks. Untrusted user input containing ANSI escape sequences could be injected into terminal output when logged, potentially allowing attackers to:
      
      - Manipulate terminal title bars
      - Clear screens or modify terminal display
      - Potentially mislead users through terminal manipulation
      
      In isolation, impact is minimal, however security issues have been found in terminal emulators that enabled an attacker to use ANSI escape sequences via logs to exploit vulnerabilities in the terminal emulator.
      
      This was patched in [PR #3368](https://github.com/tokio-rs/tracing/pull/3368) to escape ANSI control characters from user input.
    ├ Announcement: https://github.com/advisories/GHSA-xwfj-jgwm-7wp5
    ├ Solution: Upgrade to >=0.3.20 (try `cargo update -p tracing-subscriber`)
    ├ tracing-subscriber v0.3.19
      └── (dev) libdd-telemetry v2.0.0

advisories FAILED, bans ok, sources ok

Updated: 2026-02-06 09:23:17 UTC | Commit: 32e75d7 | dependency-check job results

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@dubloom @codecov-commenter