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Merged
merged 8 commits into from
Jul 11, 2025
Merged

Implement with_endpoint for SendData #1139

merged 8 commits into from
Jul 11, 2025
+58 −3

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@shreyamalpani
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@shreyamalpani shreyamalpani commented Jul 10, 2025

What does this PR do?

Implements a function with_endpoint for SendData that returns a copy of the SendData using the user-defined endpoint.

Motivation

Supporting dual shipping for traces in the Lambda Extension - need to be able to make a copy of the original traces SendData and send it to another endpoint.

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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codecov-commenter commented Jul 10, 2025 •
edited
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Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 71.29%. Comparing base (b708db7) to head (27aef15).
Report is 2 commits behind head on main.

Additional details and impacted files 
@@            Coverage Diff             @@
##             main    #1139      +/-   ##
==========================================
+ Coverage   71.27%   71.29%   +0.01%     
==========================================
  Files         343      343              
  Lines       52396    52471      +75     
==========================================
+ Hits        37347    37410      +63     
- Misses      15049    15061      +12
Components Coverage Δ
datadog-crashtracker 43.89% <ø> (-0.03%) ⬇️
datadog-crashtracker-ffi 5.93% <ø> (ø)
datadog-alloc 98.73% <ø> (ø)
data-pipeline 89.23% <ø> (+0.01%) ⬆️
data-pipeline-ffi 87.61% <ø> (+0.05%) ⬆️
ddcommon 82.88% <ø> (ø)
ddcommon-ffi 69.66% <ø> (ø)
ddtelemetry 60.08% <ø> (ø)
ddtelemetry-ffi 21.32% <ø> (ø)
dogstatsd-client 83.26% <ø> (ø)
datadog-ipc 82.58% <ø> (-0.11%) ⬇️
datadog-profiling 77.13% <ø> (ø)
datadog-profiling-ffi 62.12% <ø> (ø)
datadog-sidecar 40.28% <ø> (ø)
datdog-sidecar-ffi 5.17% <ø> (ø)
spawn-worker 55.35% <ø> (ø)
tinybytes 90.96% <ø> (ø)
datadog-trace-normalization 98.24% <ø> (ø)
datadog-trace-obfuscation 94.17% <ø> (ø)
datadog-trace-protobuf 77.10% <ø> (ø)
datadog-trace-utils 89.17% <100.00%> (+0.13%) ⬆️
datadog-tracer-flare 78.54% <ø> (ø)
datadog-log 76.31% <ø> (ø)
🚀 New features to boost your workflow:
  • ❄️ Test Analytics: Detect flaky tests, report on failures, and find test suite problems.

@shreyamalpani shreyamalpani marked this pull request as ready for review July 10, 2025 19:41
@shreyamalpani shreyamalpani requested review from a team as code owners July 10, 2025 19:41
hoolioh
hoolioh reviewed Jul 11, 2025
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@shreyamalpani shreyamalpani requested a review from hoolioh July 11, 2025 13:12
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pr-commenter bot commented Jul 11, 2025 •
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Benchmarks

Comparison

Benchmark execution time: 2025-07-11 14:40:27

Comparing candidate commit 27aef15 in PR branch shreya.malpani/sendData-with-endpoint with baseline commit 5754984 in branch main.

Found 0 performance improvements and 0 performance regressions! Performance is the same for 52 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 27aef15 1752244136 shreya.malpani/sendData-with-endpoint
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 17.816µs 25.979µs ± 9.559µs 18.136µs ± 0.265µs 34.621µs 43.424µs 44.287µs 59.126µs 226.01% 0.691 -0.634 36.70% 0.676µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
two way interface execution_time [24.654µs; 27.303µs] or [-5.099%; +5.099%] None None None

Group 2

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 27aef15 1752244136 shreya.malpani/sendData-with-endpoint
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 86.921µs 87.192µs ± 0.130µs 87.168µs ± 0.042µs 87.220µs 87.358µs 87.754µs 88.254µs 1.24% 3.973 25.599 0.15% 0.009µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
sql/obfuscate_sql_string execution_time [87.174µs; 87.210µs] or [-0.021%; +0.021%] None None None

Group 3

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 27aef15 1752244136 shreya.malpani/sendData-with-endpoint
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 1.303µs 3.246µs ± 1.439µs 3.022µs ± 0.029µs 3.051µs 3.670µs 14.129µs 14.863µs 391.78% 7.298 54.562 44.23% 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 [3.047µs; 3.446µs] or [-6.145%; +6.145%] None None None

Group 4

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 27aef15 1752244136 shreya.malpani/sendData-with-endpoint
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 33.544µs 34.105µs ± 1.020µs 33.639µs ± 0.043µs 33.706µs 36.284µs 36.311µs 37.608µs 11.80% 1.733 1.160 2.98% 0.072µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
redis/obfuscate_redis_string execution_time [33.964µs; 34.247µs] or [-0.415%; +0.415%] None None None

Group 5

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 27aef15 1752244136 shreya.malpani/sendData-with-endpoint
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 8.266ms 8.283ms ± 0.010ms 8.281ms ± 0.006ms 8.288ms 8.300ms 8.309ms 8.335ms 0.65% 1.304 3.700 0.12% 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 [8.281ms; 8.284ms] 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 27aef15 1752244136 shreya.malpani/sendData-with-endpoint
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 71.908ms 72.111ms ± 0.153ms 72.056ms ± 0.082ms 72.185ms 72.387ms 72.577ms 73.032ms 1.36% 2.089 7.271 0.21% 0.011ms 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 [72.089ms; 72.132ms] or [-0.029%; +0.029%] None None None

Group 7

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 27aef15 1752244136 shreya.malpani/sendData-with-endpoint
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 534.749µs 535.847µs ± 0.563µs 535.784µs ± 0.268µs 536.076µs 536.485µs 537.046µs 541.336µs 1.04% 4.659 43.507 0.10% 0.040µs 1 200
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000... throughput 1847281.540op/s 1866206.325op/s ± 1951.921op/s 1866422.143op/s ± 933.475op/s 1867255.284op/s 1868474.487op/s 1869692.054op/s 1870036.017op/s 0.19% -4.584 42.577 0.10% 138.022op/s 1 200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて execution_time 381.963µs 383.358µs ± 1.137µs 383.237µs ± 0.371µs 383.610µs 384.100µs 391.032µs 392.246µs 2.35% 5.837 40.683 0.30% 0.080µs 1 200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて throughput 2549419.104op/s 2608551.191op/s ± 7603.677op/s 2609353.762op/s ± 2525.873op/s 2611870.161op/s 2615239.342op/s 2616648.519op/s 2618053.138op/s 0.33% -5.760 39.954 0.29% 537.661op/s 1 200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters execution_time 195.303µs 195.869µs ± 0.703µs 195.760µs ± 0.192µs 195.976µs 196.366µs 196.628µs 202.569µs 3.48% 7.601 66.881 0.36% 0.050µs 1 200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters throughput 4936580.135op/s 5105525.362op/s ± 17839.198op/s 5108290.855op/s ± 5005.832op/s 5112480.134op/s 5117676.411op/s 5119833.759op/s 5120260.477op/s 0.23% -7.481 65.406 0.35% 1261.422op/s 1 200
normalization/normalize_service/normalize_service/[empty string] execution_time 38.084µs 38.195µs ± 0.052µs 38.192µs ± 0.033µs 38.225µs 38.286µs 38.331µs 38.338µs 0.38% 0.462 0.145 0.14% 0.004µs 1 200
normalization/normalize_service/normalize_service/[empty string] throughput 26083691.476op/s 26181622.785op/s ± 35755.956op/s 26183690.988op/s ± 22741.349op/s 26206222.810op/s 26238545.984op/s 26249066.716op/s 26258080.453op/s 0.28% -0.454 0.135 0.14% 2528.328op/s 1 200
normalization/normalize_service/normalize_service/test_ASCII execution_time 45.907µs 46.041µs ± 0.077µs 46.033µs ± 0.045µs 46.079µs 46.151µs 46.283µs 46.549µs 1.12% 1.988 9.503 0.17% 0.005µs 1 200
normalization/normalize_service/normalize_service/test_ASCII throughput 21482774.515op/s 21719653.237op/s ± 36051.222op/s 21723323.306op/s ± 21057.889op/s 21743018.187op/s 21765386.904op/s 21776516.625op/s 21783339.037op/s 0.28% -1.951 9.215 0.17% 2549.206op/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 [535.769µs; 535.925µs] or [-0.015%; +0.015%] None None None
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000... throughput [1865935.808op/s; 1866476.843op/s] or [-0.014%; +0.014%] None None None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて execution_time [383.200µs; 383.515µs] or [-0.041%; +0.041%] None None None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて throughput [2607497.395op/s; 2609604.988op/s] or [-0.040%; +0.040%] None None None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters execution_time [195.771µs; 195.966µs] or [-0.050%; +0.050%] None None None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters throughput [5103053.021op/s; 5107997.704op/s] or [-0.048%; +0.048%] None None None
normalization/normalize_service/normalize_service/[empty string] execution_time [38.188µs; 38.202µs] or [-0.019%; +0.019%] None None None
normalization/normalize_service/normalize_service/[empty string] throughput [26176667.354op/s; 26186578.217op/s] or [-0.019%; +0.019%] None None None
normalization/normalize_service/normalize_service/test_ASCII execution_time [46.031µs; 46.052µs] or [-0.023%; +0.023%] None None None
normalization/normalize_service/normalize_service/test_ASCII throughput [21714656.885op/s; 21724649.590op/s] or [-0.023%; +0.023%] None None None

Group 8

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 27aef15 1752244136 shreya.malpani/sendData-with-endpoint
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 151.357µs 152.211µs ± 0.412µs 152.139µs ± 0.140µs 152.311µs 152.737µs 153.481µs 155.870µs 2.45% 4.221 31.804 0.27% 0.029µs 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 [152.154µs; 152.268µs] or [-0.037%; +0.037%] None None None

Group 9

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 27aef15 1752244136 shreya.malpani/sendData-with-endpoint
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 3.890µs 3.913µs ± 0.004µs 3.912µs ± 0.002µs 3.914µs 3.919µs 3.921µs 3.924µs 0.29% -0.415 6.666 0.09% 0.000µs 1 200
credit_card/is_card_number/ throughput 254869583.922op/s 255588543.022op/s ± 235502.295op/s 255605132.155op/s ± 139202.679op/s 255748061.457op/s 255853980.601op/s 255906608.251op/s 257043075.775op/s 0.56% 0.438 6.796 0.09% 16652.527op/s 1 200
credit_card/is_card_number/ 3782-8224-6310-005 execution_time 79.663µs 81.128µs ± 0.574µs 81.106µs ± 0.396µs 81.488µs 82.075µs 82.476µs 83.180µs 2.56% 0.306 0.259 0.71% 0.041µs 1 200
credit_card/is_card_number/ 3782-8224-6310-005 throughput 12022187.680op/s 12326767.450op/s ± 87082.964op/s 12329570.022op/s ± 59907.976op/s 12393193.718op/s 12469671.088op/s 12494265.836op/s 12552937.933op/s 1.81% -0.261 0.202 0.70% 6157.695op/s 1 200
credit_card/is_card_number/ 378282246310005 execution_time 75.233µs 75.648µs ± 0.161µs 75.619µs ± 0.073µs 75.741µs 75.953µs 76.112µs 76.363µs 0.98% 0.797 1.885 0.21% 0.011µs 1 200
credit_card/is_card_number/ 378282246310005 throughput 13095344.644op/s 13219100.058op/s ± 28152.042op/s 13224250.830op/s ± 12758.848op/s 13234469.854op/s 13261432.207op/s 13273488.464op/s 13291957.037op/s 0.51% -0.776 1.828 0.21% 1990.650op/s 1 200
credit_card/is_card_number/37828224631 execution_time 3.894µs 3.912µs ± 0.006µs 3.912µs ± 0.002µs 3.913µs 3.917µs 3.924µs 3.971µs 1.52% 6.375 54.626 0.16% 0.000µs 1 200
credit_card/is_card_number/37828224631 throughput 251828144.195op/s 255593974.716op/s ± 401779.771op/s 255647112.151op/s ± 116167.349op/s 255749202.022op/s 255894087.130op/s 255971039.443op/s 256828290.234op/s 0.46% -6.299 53.790 0.16% 28410.120op/s 1 200
credit_card/is_card_number/378282246310005 execution_time 72.411µs 72.862µs ± 0.134µs 72.831µs ± 0.056µs 72.910µs 73.119µs 73.242µs 73.587µs 1.04% 1.335 5.007 0.18% 0.009µs 1 200
credit_card/is_card_number/378282246310005 throughput 13589334.067op/s 13724556.294op/s ± 25132.964op/s 13730382.157op/s ± 10492.920op/s 13739038.854op/s 13752802.240op/s 13776301.320op/s 13810138.022op/s 0.58% -1.307 4.903 0.18% 1777.169op/s 1 200
credit_card/is_card_number/37828224631000521389798 execution_time 52.650µs 52.873µs ± 0.106µs 52.866µs ± 0.041µs 52.910µs 52.953µs 53.026µs 53.799µs 1.77% 5.460 44.281 0.20% 0.008µs 1 200
credit_card/is_card_number/37828224631000521389798 throughput 18587582.438op/s 18913252.515op/s ± 37561.564op/s 18915673.927op/s ± 14555.872op/s 18929221.277op/s 18950367.960op/s 18982374.846op/s 18993432.071op/s 0.41% -5.362 43.269 0.20% 2656.004op/s 1 200
credit_card/is_card_number/x371413321323331 execution_time 6.427µs 6.434µs ± 0.005µs 6.434µs ± 0.003µs 6.436µs 6.441µs 6.445µs 6.473µs 0.61% 2.915 20.029 0.07% 0.000µs 1 200
credit_card/is_card_number/x371413321323331 throughput 154487550.182op/s 155424093.860op/s ± 116442.772op/s 155434778.532op/s ± 69370.373op/s 155503919.383op/s 155563990.115op/s 155598494.510op/s 155603591.739op/s 0.11% -2.885 19.714 0.07% 8233.747op/s 1 200
credit_card/is_card_number_no_luhn/ execution_time 3.890µs 3.911µs ± 0.003µs 3.911µs ± 0.001µs 3.913µs 3.915µs 3.916µs 3.934µs 0.57% 0.390 27.675 0.08% 0.000µs 1 200
credit_card/is_card_number_no_luhn/ throughput 254224380.009op/s 255668789.048op/s ± 192840.538op/s 255676209.336op/s ± 92496.140op/s 255770579.893op/s 255860826.442op/s 255902399.363op/s 257071993.228op/s 0.55% -0.323 27.650 0.08% 13635.885op/s 1 200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 execution_time 64.969µs 65.097µs ± 0.095µs 65.077µs ± 0.050µs 65.139µs 65.261µs 65.431µs 65.629µs 0.85% 1.944 6.425 0.15% 0.007µs 1 200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 throughput 15237088.101op/s 15361641.035op/s ± 22273.110op/s 15366471.895op/s ± 11808.691op/s 15375617.731op/s 15387481.514op/s 15391471.232op/s 15391910.012op/s 0.17% -1.924 6.301 0.14% 1574.947op/s 1 200
credit_card/is_card_number_no_luhn/ 378282246310005 execution_time 58.159µs 58.300µs ± 0.093µs 58.278µs ± 0.054µs 58.352µs 58.460µs 58.577µs 58.783µs 0.87% 1.506 3.829 0.16% 0.007µs 1 200
credit_card/is_card_number_no_luhn/ 378282246310005 throughput 17011660.504op/s 17152729.133op/s ± 27264.148op/s 17159098.717op/s ± 15843.582op/s 17173512.005op/s 17185319.784op/s 17188951.751op/s 17194138.518op/s 0.20% -1.489 3.733 0.16% 1927.866op/s 1 200
credit_card/is_card_number_no_luhn/37828224631 execution_time 3.892µs 3.912µs ± 0.003µs 3.912µs ± 0.002µs 3.914µs 3.917µs 3.920µs 3.929µs 0.43% -0.250 10.127 0.08% 0.000µs 1 200
credit_card/is_card_number_no_luhn/37828224631 throughput 254524047.993op/s 255626651.431op/s ± 210567.661op/s 255619454.319op/s ± 113766.395op/s 255758990.814op/s 255887904.886op/s 255947361.677op/s 256954761.491op/s 0.52% 0.280 10.206 0.08% 14889.382op/s 1 200
credit_card/is_card_number_no_luhn/378282246310005 execution_time 55.005µs 55.351µs ± 0.166µs 55.330µs ± 0.093µs 55.432µs 55.680µs 55.827µs 56.088µs 1.37% 1.058 2.145 0.30% 0.012µs 1 200
credit_card/is_card_number_no_luhn/378282246310005 throughput 17829072.973op/s 18066562.978op/s ± 54052.360op/s 18073449.201op/s ± 30260.780op/s 18102826.309op/s 18147920.402op/s 18155104.062op/s 18180304.222op/s 0.59% -1.031 2.051 0.30% 3822.079op/s 1 200
credit_card/is_card_number_no_luhn/37828224631000521389798 execution_time 52.672µs 52.834µs ± 0.069µs 52.838µs ± 0.050µs 52.882µs 52.944µs 52.999µs 53.039µs 0.38% 0.168 -0.388 0.13% 0.005µs 1 200
credit_card/is_card_number_no_luhn/37828224631000521389798 throughput 18854217.306op/s 18927199.191op/s ± 24792.649op/s 18925610.997op/s ± 17796.990op/s 18947128.039op/s 18965309.320op/s 18969955.596op/s 18985276.918op/s 0.32% -0.162 -0.394 0.13% 1753.105op/s 1 200
credit_card/is_card_number_no_luhn/x371413321323331 execution_time 6.428µs 6.439µs ± 0.007µs 6.438µs ± 0.005µs 6.444µs 6.450µs 6.457µs 6.464µs 0.40% 0.547 0.112 0.10% 0.000µs 1 200
credit_card/is_card_number_no_luhn/x371413321323331 throughput 154710239.867op/s 155297394.474op/s ± 160081.584op/s 155323852.499op/s ± 117075.097op/s 155418257.763op/s 155530293.185op/s 155561092.380op/s 155572171.722op/s 0.16% -0.541 0.099 0.10% 11319.477op/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 [-0.013%; +0.013%] None None None
credit_card/is_card_number/ throughput [255555904.669op/s; 255621181.375op/s] or [-0.013%; +0.013%] None None None
credit_card/is_card_number/ 3782-8224-6310-005 execution_time [81.049µs; 81.208µs] or [-0.098%; +0.098%] None None None
credit_card/is_card_number/ 3782-8224-6310-005 throughput [12314698.589op/s; 12338836.312op/s] or [-0.098%; +0.098%] None None None
credit_card/is_card_number/ 378282246310005 execution_time [75.626µs; 75.671µs] or [-0.030%; +0.030%] None None None
credit_card/is_card_number/ 378282246310005 throughput [13215198.456op/s; 13223001.661op/s] or [-0.030%; +0.030%] None None None
credit_card/is_card_number/37828224631 execution_time [3.912µs; 3.913µs] or [-0.022%; +0.022%] None None None
credit_card/is_card_number/37828224631 throughput [255538291.904op/s; 255649657.528op/s] or [-0.022%; +0.022%] None None None
credit_card/is_card_number/378282246310005 execution_time [72.844µs; 72.881µs] or [-0.025%; +0.025%] None None None
credit_card/is_card_number/378282246310005 throughput [13721073.107op/s; 13728039.481op/s] or [-0.025%; +0.025%] None None None
credit_card/is_card_number/37828224631000521389798 execution_time [52.858µs; 52.888µs] or [-0.028%; +0.028%] None None None
credit_card/is_card_number/37828224631000521389798 throughput [18908046.843op/s; 18918458.186op/s] or [-0.028%; +0.028%] None None None
credit_card/is_card_number/x371413321323331 execution_time [6.433µs; 6.435µs] or [-0.010%; +0.010%] None None None
credit_card/is_card_number/x371413321323331 throughput [155407956.012op/s; 155440231.708op/s] or [-0.010%; +0.010%] 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 [255642063.204op/s; 255695514.892op/s] or [-0.010%; +0.010%] None None None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 execution_time [65.084µs; 65.110µs] or [-0.020%; +0.020%] None None None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 throughput [15358554.196op/s; 15364727.874op/s] or [-0.020%; +0.020%] None None None
credit_card/is_card_number_no_luhn/ 378282246310005 execution_time [58.287µs; 58.313µs] or [-0.022%; +0.022%] None None None
credit_card/is_card_number_no_luhn/ 378282246310005 throughput [17148950.584op/s; 17156507.682op/s] or [-0.022%; +0.022%] None None None
credit_card/is_card_number_no_luhn/37828224631 execution_time [3.912µs; 3.912µs] or [-0.011%; +0.011%] None None None
credit_card/is_card_number_no_luhn/37828224631 throughput [255597468.778op/s; 255655834.083op/s] or [-0.011%; +0.011%] None None None
credit_card/is_card_number_no_luhn/378282246310005 execution_time [55.328µs; 55.374µs] or [-0.042%; +0.042%] None None None
credit_card/is_card_number_no_luhn/378282246310005 throughput [18059071.841op/s; 18074054.116op/s] or [-0.041%; +0.041%] None None None
credit_card/is_card_number_no_luhn/37828224631000521389798 execution_time [52.825µs; 52.844µs] or [-0.018%; +0.018%] None None None
credit_card/is_card_number_no_luhn/37828224631000521389798 throughput [18923763.168op/s; 18930635.214op/s] or [-0.018%; +0.018%] None None None
credit_card/is_card_number_no_luhn/x371413321323331 execution_time [6.438µs; 6.440µs] or [-0.014%; +0.014%] None None None
credit_card/is_card_number_no_luhn/x371413321323331 throughput [155275208.706op/s; 155319580.242op/s] or [-0.014%; +0.014%] None None None

Group 10

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 27aef15 1752244136 shreya.malpani/sendData-with-endpoint
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 2.414µs 2.438µs ± 0.018µs 2.436µs ± 0.009µs 2.442µs 2.482µs 2.489µs 2.516µs 3.28% 1.499 2.690 0.73% 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 [2.435µs; 2.440µs] or [-0.101%; +0.101%] None None None

Group 11

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 27aef15 1752244136 shreya.malpani/sendData-with-endpoint
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 205.645µs 206.051µs ± 0.275µs 206.006µs ± 0.121µs 206.154µs 206.418µs 206.676µs 208.653µs 1.29% 4.518 38.482 0.13% 0.019µs 1 200
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... throughput 4792644.922op/s 4853184.190op/s ± 6440.787op/s 4854232.960op/s ± 2842.840op/s 4856763.542op/s 4859614.729op/s 4861863.333op/s 4862757.220op/s 0.18% -4.438 37.468 0.13% 455.432op/s 1 200
normalization/normalize_name/normalize_name/bad-name execution_time 18.214µs 18.395µs ± 0.147µs 18.332µs ± 0.059µs 18.498µs 18.662µs 18.796µs 18.944µs 3.34% 1.107 0.645 0.80% 0.010µs 1 200
normalization/normalize_name/normalize_name/bad-name throughput 52785967.982op/s 54366216.715op/s ± 431622.094op/s 54549922.516op/s ± 175316.251op/s 54656228.411op/s 54882987.866op/s 54898953.816op/s 54902771.344op/s 0.65% -1.074 0.529 0.79% 30520.291op/s 1 200
normalization/normalize_name/normalize_name/good execution_time 10.678µs 10.891µs ± 0.099µs 10.886µs ± 0.075µs 10.962µs 11.061µs 11.115µs 11.180µs 2.70% 0.298 -0.341 0.91% 0.007µs 1 200
normalization/normalize_name/normalize_name/good throughput 89448797.392op/s 91823084.140op/s ± 831612.618op/s 91863168.269op/s ± 637190.442op/s 92496210.085op/s 93112990.094op/s 93472241.783op/s 93654379.593op/s 1.95% -0.256 -0.376 0.90% 58803.892op/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 [206.013µs; 206.089µs] or [-0.019%; +0.019%] None None None
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... throughput [4852291.559op/s; 4854076.821op/s] or [-0.018%; +0.018%] None None None
normalization/normalize_name/normalize_name/bad-name execution_time [18.375µs; 18.415µs] or [-0.111%; +0.111%] None None None
normalization/normalize_name/normalize_name/bad-name throughput [54306398.044op/s; 54426035.386op/s] or [-0.110%; +0.110%] None None None
normalization/normalize_name/normalize_name/good execution_time [10.878µs; 10.905µs] or [-0.126%; +0.126%] None None None
normalization/normalize_name/normalize_name/good throughput [91707830.629op/s; 91938337.650op/s] or [-0.126%; +0.126%] None None None

Group 12

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 27aef15 1752244136 shreya.malpani/sendData-with-endpoint
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 244.556ns 253.762ns ± 12.416ns 247.373ns ± 2.062ns 258.313ns 284.444ns 290.940ns 292.638ns 18.30% 1.720 1.828 4.88% 0.878ns 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 [252.041ns; 255.483ns] or [-0.678%; +0.678%] None None None

Group 13

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 27aef15 1752244136 shreya.malpani/sendData-with-endpoint
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 5.007µs 5.079µs ± 0.045µs 5.085µs ± 0.033µs 5.115µs 5.147µs 5.154µs 5.170µs 1.67% -0.081 -1.340 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 [5.072µs; 5.085µs] or [-0.122%; +0.122%] None None None

Baseline

Omitted due to size.

ekump
ekump reviewed Jul 11, 2025
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datadog-trace-utils/src/send_data/mod.rs Outdated
}

/// Overrides the set target Endpoint.
/// Returns a copy of the SendData with the user-defined endpoint.
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nit: Clone and Copy are different.

Suggested change
/// Returns a copy of the SendData with the user-defined endpoint.
/// Returns a clone of the SendData with the user-defined endpoint.

ekump
ekump reviewed Jul 11, 2025
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ekump commented Jul 11, 2025 •
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Artifact Size Benchmark Report

aarch64-alpine-linux-musl
Artifact Baseline Commit Change
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.a 70.23 MB 70.23 MB 0% (0 B) 👌
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.so.debug 22.10 MB 22.10 MB 0% (0 B) 👌
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.so 9.24 MB 9.24 MB 0% (0 B) 👌
aarch64-unknown-linux-gnu
Artifact Baseline Commit Change
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.a 82.44 MB 82.44 MB 0% (0 B) 👌
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.so.debug 26.15 MB 26.15 MB 0% (0 B) 👌
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.so 9.09 MB 9.09 MB 0% (0 B) 👌
libdatadog-x64-windows
Artifact Baseline Commit Change
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.dll 18.37 MB 18.37 MB 0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.lib 64.26 KB 64.26 KB 0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.pdb 124.63 MB 124.82 MB +.15% (+192.00 KB) 🔍
/libdatadog-x64-windows/debug/static/datadog_profiling_ffi.lib 643.66 MB 644.68 MB +.15% (+1.02 MB) 🔍
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.dll 5.86 MB 5.86 MB 0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.lib 64.26 KB 64.26 KB 0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.pdb 17.33 MB 17.33 MB 0% (0 B) 👌
/libdatadog-x64-windows/release/static/datadog_profiling_ffi.lib 32.13 MB 32.13 MB 0% (0 B) 👌
libdatadog-x86-windows
Artifact Baseline Commit Change
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.dll 15.66 MB 15.66 MB +0% (+512 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.lib 65.25 KB 65.25 KB 0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.pdb 126.89 MB 127.14 MB +.19% (+256.00 KB) 🔍
/libdatadog-x86-windows/debug/static/datadog_profiling_ffi.lib 633.29 MB 634.31 MB +.16% (+1.01 MB) 🔍
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.dll 4.47 MB 4.47 MB 0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.lib 65.25 KB 65.25 KB 0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.pdb 18.47 MB 18.47 MB 0% (0 B) 👌
/libdatadog-x86-windows/release/static/datadog_profiling_ffi.lib 30.18 MB 30.18 MB 0% (0 B) 👌
x86_64-alpine-linux-musl
Artifact Baseline Commit Change
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.a 62.95 MB 62.95 MB -0% (-8 B) 👌
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.so 9.83 MB 9.83 MB 0% (0 B) 👌
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.so.debug 20.95 MB 20.95 MB 0% (0 B) 👌
x86_64-unknown-linux-gnu
Artifact Baseline Commit Change
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.a 77.42 MB 77.42 MB 0% (0 B) 👌
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.so 9.74 MB 9.74 MB 0% (0 B) 👌
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.so.debug 24.08 MB 24.08 MB -0% (-8 B) 👌

@shreyamalpani shreyamalpani merged commit ca19adc into main Jul 11, 2025
36 checks passed
@shreyamalpani shreyamalpani deleted the shreya.malpani/sendData-with-endpoint branch July 11, 2025 15:31
@ekump ekump mentioned this pull request Jul 11, 2025
Merged
This was referenced Jul 18, 2025
Merged
Merged
shreyamalpani added a commit to DataDog/datadog-lambda-extension that referenced this pull request Jul 21, 2025
@shreyamalpani
feat: dual shipping APM support (#735)
04a8b7d 
Adds support for dual shipping traces to endpoints configured using the
`apm_config` YAML or `DD_APM_CONFIG_ADDITIONAL_ENDPOINTS` env var
config.

#### Additional Notes:
- Bumped libdatadog (and serverless-components) to include
DataDog/libdatadog#1139
- Adds configuration option to set compression level for trace payloads
@bwoebi bwoebi mentioned this pull request Sep 29, 2025
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