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refactor(profiling): split upload function#1733

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KowalskiThomas wants to merge 2 commits intomainfrom
kowalski/temp-profiling-split-upload-function
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refactor(profiling): split upload function#1733
KowalskiThomas wants to merge 2 commits intomainfrom
kowalski/temp-profiling-split-upload-function

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@KowalskiThomas KowalskiThomas commented Mar 16, 2026 •
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What does this PR do?

This PR splits the Exporter creation process into two steps (two functions to call):

  1. Create the Tokio runtime with init_runtime
  2. Upload the Profile with send_blocking (send_blocking calls init_runtime if it hasn't been initialised from the outside)

This fixes a TSan-detected race condition where we try to cancel the Upload request (using the Cancellation Token) at the same time the runtime is being initialised.
Example runtime Profiler fix PR: DataDog/dd-trace-py#16467

The PR also updates the existing exporter.cpp example to use the new function (tested with cargo ffi-test --filter exporter).

Open questions

Currently, the PR maintains compatibility with existing usages -- not explicitly calling init_runtime will make send_blocking call it when it needs it. However, this is risky (for the reasons that made us make this PR in the first place).

  • Should we prevent people from doing this? Doing so will break compatibility with current usages.
  • ... Or should we instead keep the race? Doing so will guarantee backwards compatibility but also not force usages to be fixed.

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github-actions bot commented Mar 16, 2026 •
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📚 Documentation Check Results

⚠️ 649 documentation warning(s) found

📦 libdd-profiling - 649 warning(s)

Updated: 2026-03-31 09:30:20 UTC | Commit: c41f586 | missing-docs job results

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github-actions bot commented Mar 16, 2026 •
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Clippy Allow Annotation Report

Comparing clippy allow annotations between branches:

  • Base Branch: origin/main
  • PR Branch: origin/kowalski/temp-profiling-split-upload-function

Summary by Rule

Rule Base Branch PR Branch Change

Annotation Counts by File

File Base Branch PR Branch Change

Annotation Stats by Crate

Crate Base Branch PR Branch Change
clippy-annotation-reporter 5 5 No change (0%)
datadog-ffe-ffi 1 1 No change (0%)
datadog-ipc 20 21 ⚠️ +1 (+5.0%)
datadog-live-debugger 6 6 No change (0%)
datadog-live-debugger-ffi 10 10 No change (0%)
datadog-profiling-replayer 4 4 No change (0%)
datadog-remote-config 3 3 No change (0%)
datadog-sidecar 55 59 ⚠️ +4 (+7.3%)
libdd-common 10 10 No change (0%)
libdd-common-ffi 12 12 No change (0%)
libdd-crashtracker 0 12 ⚠️ +12 (N/A)
libdd-data-pipeline 5 5 No change (0%)
libdd-ddsketch 2 2 No change (0%)
libdd-dogstatsd-client 1 1 No change (0%)
libdd-profiling 13 13 No change (0%)
libdd-telemetry 19 19 No change (0%)
libdd-tinybytes 4 4 No change (0%)
libdd-trace-normalization 2 2 No change (0%)
libdd-trace-obfuscation 8 9 ⚠️ +1 (+12.5%)
libdd-trace-utils 15 15 No change (0%)
Total 195 213 ⚠️ +18 (+9.2%)

About This Report

This report tracks Clippy allow annotations for specific rules, showing how they've changed in this PR. Decreasing the number of these annotations generally improves code quality.

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🔒 Cargo Deny Results

✅ No issues found!

📦 libdd-profiling - ✅ No issues

Updated: 2026-03-31 09:33:05 UTC | Commit: c41f586 | dependency-check job results

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codecov-commenter commented Mar 16, 2026 •
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Codecov Report

❌ Patch coverage is 37.50000% with 5 lines in your changes missing coverage. Please review.
✅ Project coverage is 71.32%. Comparing base (29b010a) to head (6f118be).
⚠️ Report is 88 commits behind head on main.

Additional details and impacted files 
@@            Coverage Diff             @@
##             main    #1733      +/-   ##
==========================================
+ Coverage   71.17%   71.32%   +0.14%     
==========================================
  Files         427      424       -3     
  Lines       62807    66694    +3887     
==========================================
+ Hits        44703    47569    +2866     
- Misses      18104    19125    +1021
Components Coverage Δ
libdd-crashtracker 65.88% <ø> (+2.88%) ⬆️
libdd-crashtracker-ffi 34.47% <ø> (+17.91%) ⬆️
libdd-alloc 98.77% <ø> (ø)
libdd-data-pipeline 87.05% <ø> (-0.97%) ⬇️
libdd-data-pipeline-ffi 72.91% <ø> (-2.81%) ⬇️
libdd-common 80.19% <ø> (+0.45%) ⬆️
libdd-common-ffi 73.87% <ø> (+0.46%) ⬆️
libdd-telemetry 62.48% <ø> (ø)
libdd-telemetry-ffi 16.75% <ø> (ø)
libdd-dogstatsd-client 82.64% <ø> (ø)
datadog-ipc 70.31% <ø> (-10.44%) ⬇️
libdd-profiling 81.58% <37.50%> (-0.03%) ⬇️
libdd-profiling-ffi 64.77% <0.00%> (+1.11%) ⬆️
datadog-sidecar 30.18% <ø> (-1.82%) ⬇️
datdog-sidecar-ffi 6.52% <ø> (+0.08%) ⬆️
spawn-worker 54.69% <ø> (ø)
libdd-tinybytes 93.16% <ø> (ø)
libdd-trace-normalization 81.71% <ø> (ø)
libdd-trace-obfuscation 87.24% <ø> (-7.44%) ⬇️
libdd-trace-protobuf 68.25% <ø> (+0.25%) ⬆️
libdd-trace-utils 88.72% <ø> (-0.36%) ⬇️
datadog-tracer-flare 86.88% <ø> (-2.08%) ⬇️
libdd-log 74.69% <ø> (ø)
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@KowalskiThomas KowalskiThomas changed the title temp(profiling): split upload function refactor(profiling): split upload function Mar 20, 2026
@KowalskiThomas KowalskiThomas force-pushed the kowalski/temp-profiling-split-upload-function branch from c07829c to 7a18d4d Compare March 20, 2026 13:45
@KowalskiThomas KowalskiThomas added the profiling Relates to the profiling* modules. label Mar 20, 2026
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datadog-datadog-prod-us1-2 bot commented Mar 20, 2026 •
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✅ Tests

🎉 All green!

❄️ No new flaky tests detected
🧪 All tests passed

🎯 Code Coverage (details)
• Patch Coverage: 37.50%
• Overall Coverage: 71.32% (-0.01%)

This comment will be updated automatically if new data arrives.
🔗 Commit SHA: 6f118be | Docs | Datadog PR Page | Was this helpful? React with 👍/👎 or give us feedback!

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Benchmarks

Comparison

Benchmark execution time: 2026-03-31 09:46:30

Comparing candidate commit 6f118be in PR branch kowalski/temp-profiling-split-upload-function with baseline commit 15860bb in branch main.

Found 7 performance improvements and 20 performance regressions! Performance is the same for 31 metrics, 1 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 ----------------------------------'

scenario:benching serializing traces from their internal representation to msgpack

  • 🟩 execution_time [-817.721µs; -807.213µs] or [-5.517%; -5.446%]

scenario:concentrator/add_spans_to_concentrator

  • 🟩 execution_time [-4.139ms; -4.133ms] or [-27.735%; -27.693%]

scenario:credit_card/is_card_number/ 378282246310005

  • 🟥 execution_time [+5.381µs; +5.491µs] or [+7.951%; +8.113%]
  • 🟥 throughput [-1108600.197op/s; -1087851.616op/s] or [-7.503%; -7.362%]

scenario:credit_card/is_card_number/378282246310005

  • 🟥 execution_time [+4.879µs; +4.974µs] or [+7.531%; +7.677%]
  • 🟥 throughput [-1100398.942op/s; -1080739.089op/s] or [-7.129%; -7.001%]

scenario:credit_card/is_card_number/37828224631000521389798

  • 🟥 execution_time [+7.229µs; +7.254µs] or [+16.051%; +16.106%]
  • 🟥 throughput [-3081264.264op/s; -3070064.671op/s] or [-13.877%; -13.827%]

scenario:credit_card/is_card_number/x371413321323331

  • 🟥 execution_time [+336.846ns; +339.713ns] or [+5.905%; +5.955%]
  • 🟥 throughput [-9853181.251op/s; -9771649.118op/s] or [-5.621%; -5.574%]

scenario:credit_card/is_card_number_no_luhn/ 3782-8224-6310-005

  • 🟥 execution_time [+3.332µs; +3.445µs] or [+5.452%; +5.636%]
  • 🟥 throughput [-874802.440op/s; -845115.127op/s] or [-5.347%; -5.165%]

scenario:credit_card/is_card_number_no_luhn/ 378282246310005

  • 🟥 execution_time [+4.609µs; +4.659µs] or [+8.574%; +8.668%]
  • 🟥 throughput [-1484271.217op/s; -1468545.512op/s] or [-7.978%; -7.894%]

scenario:credit_card/is_card_number_no_luhn/378282246310005

  • 🟥 execution_time [+4.581µs; +4.655µs] or [+9.100%; +9.246%]
  • 🟥 throughput [-1680944.077op/s; -1656448.693op/s] or [-8.462%; -8.339%]

scenario:credit_card/is_card_number_no_luhn/37828224631000521389798

  • 🟥 execution_time [+7.235µs; +7.260µs] or [+16.067%; +16.123%]
  • 🟥 throughput [-3084698.493op/s; -3073180.058op/s] or [-13.890%; -13.838%]

scenario:credit_card/is_card_number_no_luhn/x371413321323331

  • 🟥 execution_time [+335.140ns; +338.225ns] or [+5.874%; +5.928%]
  • 🟥 throughput [-9808586.240op/s; -9721369.515op/s] or [-5.597%; -5.547%]

scenario:normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo...

  • 🟩 execution_time [-19.848µs; -19.714µs] or [-9.640%; -9.575%]
  • 🟩 throughput [+514514.420op/s; +517919.551op/s] or [+10.593%; +10.664%]

scenario:normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて

  • 🟥 execution_time [+20.199µs; +20.362µs] or [+5.301%; +5.343%]
  • 🟥 throughput [-133138.051op/s; -132074.764op/s] or [-5.073%; -5.033%]

scenario:profile_add_sample_frames_x1000

  • 🟩 execution_time [-220.416µs; -218.395µs] or [-5.008%; -4.963%]

scenario:sql/obfuscate_sql_string

  • 🟩 execution_time [-199.823µs; -199.661µs] or [-68.867%; -68.812%]

scenario:write only interface

  • 🟩 execution_time [-2.411µs; -2.019µs] or [-44.986%; -37.673%]

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 6f118be 1774949326 kowalski/temp-profiling-split-upload-function
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 1.214µs 3.144µs ± 1.413µs 2.970µs ± 0.030µs 3.001µs 3.326µs 13.613µs 14.987µs 404.59% 7.508 56.992 44.85% 0.100µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
write only interface execution_time [2.948µs; 3.340µs] or [-6.231%; +6.231%] None None None

Group 2

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 6f118be 1774949326 kowalski/temp-profiling-split-upload-function
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 4.176ms 4.181ms ± 0.007ms 4.181ms ± 0.002ms 4.183ms 4.185ms 4.189ms 4.267ms 2.07% 11.075 140.907 0.16% 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 [4.181ms; 4.182ms] or [-0.022%; +0.022%] None None None

Group 3

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 6f118be 1774949326 kowalski/temp-profiling-split-upload-function
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 90.191µs 90.413µs ± 0.156µs 90.388µs ± 0.063µs 90.467µs 90.574µs 91.059µs 91.683µs 1.43% 4.130 26.041 0.17% 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 [90.392µs; 90.435µs] or [-0.024%; +0.024%] None None None

Group 4

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 6f118be 1774949326 kowalski/temp-profiling-split-upload-function
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 2.326µs 2.383µs ± 0.018µs 2.381µs ± 0.006µs 2.388µs 2.427µs 2.435µs 2.444µs 2.63% 0.433 3.137 0.76% 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 [2.380µs; 2.385µs] or [-0.106%; +0.106%] None None None

Group 5

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 6f118be 1774949326 kowalski/temp-profiling-split-upload-function
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 3.896µs 3.917µs ± 0.004µs 3.916µs ± 0.002µs 3.919µs 3.923µs 3.927µs 3.932µs 0.41% 0.212 3.770 0.10% 0.000µs 1 200
credit_card/is_card_number/ throughput 254346952.746op/s 255327898.102op/s ± 264844.133op/s 255394202.552op/s ± 160203.421op/s 255513550.222op/s 255634815.918op/s 255697256.509op/s 256689221.616op/s 0.51% -0.194 3.815 0.10% 18727.308op/s 1 200
credit_card/is_card_number/ 3782-8224-6310-005 execution_time 78.901µs 79.641µs ± 0.350µs 79.609µs ± 0.226µs 79.857µs 80.255µs 80.525µs 80.794µs 1.49% 0.608 0.154 0.44% 0.025µs 1 200
credit_card/is_card_number/ 3782-8224-6310-005 throughput 12377132.403op/s 12556632.296op/s ± 54964.775op/s 12561376.281op/s ± 35526.182op/s 12595454.932op/s 12636675.107op/s 12649086.469op/s 12674120.793op/s 0.90% -0.585 0.112 0.44% 3886.596op/s 1 200
credit_card/is_card_number/ 378282246310005 execution_time 72.415µs 73.114µs ± 0.382µs 73.065µs ± 0.227µs 73.350µs 73.717µs 74.164µs 75.420µs 3.22% 1.479 6.180 0.52% 0.027µs 1 200
credit_card/is_card_number/ 378282246310005 throughput 13259063.223op/s 13677553.812op/s ± 70895.863op/s 13686414.205op/s ± 42646.785op/s 13724553.914op/s 13778114.684op/s 13792957.738op/s 13809388.308op/s 0.90% -1.388 5.585 0.52% 5013.095op/s 1 200
credit_card/is_card_number/37828224631 execution_time 3.895µs 3.916µs ± 0.004µs 3.916µs ± 0.002µs 3.919µs 3.923µs 3.926µs 3.927µs 0.30% -0.108 3.628 0.10% 0.000µs 1 200
credit_card/is_card_number/37828224631 throughput 254624633.622op/s 255345375.078op/s ± 254006.512op/s 255393665.654op/s ± 162719.399op/s 255526933.556op/s 255626319.782op/s 255703999.036op/s 256725777.953op/s 0.52% 0.124 3.702 0.10% 17960.973op/s 1 200
credit_card/is_card_number/378282246310005 execution_time 69.165µs 69.710µs ± 0.327µs 69.620µs ± 0.221µs 69.942µs 70.263µs 70.559µs 71.039µs 2.04% 0.902 0.734 0.47% 0.023µs 1 200
credit_card/is_card_number/378282246310005 throughput 14076861.423op/s 14345449.303op/s ± 67104.515op/s 14363609.812op/s ± 45381.176op/s 14394636.200op/s 14430685.844op/s 14450941.129op/s 14458143.424op/s 0.66% -0.875 0.641 0.47% 4745.006op/s 1 200
credit_card/is_card_number/37828224631000521389798 execution_time 52.198µs 52.278µs ± 0.053µs 52.265µs ± 0.034µs 52.312µs 52.366µs 52.436µs 52.486µs 0.42% 1.197 1.738 0.10% 0.004µs 1 200
credit_card/is_card_number/37828224631000521389798 throughput 19052624.142op/s 19128500.044op/s ± 19231.821op/s 19133349.945op/s ± 12560.942op/s 19144008.084op/s 19149414.715op/s 19152543.740op/s 19157732.295op/s 0.13% -1.191 1.710 0.10% 1359.895op/s 1 200
credit_card/is_card_number/x371413321323331 execution_time 6.032µs 6.043µs ± 0.008µs 6.042µs ± 0.004µs 6.046µs 6.053µs 6.080µs 6.099µs 0.94% 2.953 12.954 0.14% 0.001µs 1 200
credit_card/is_card_number/x371413321323331 throughput 163974008.683op/s 165479741.489op/s ± 230880.528op/s 165519564.428op/s ± 109717.509op/s 165626588.403op/s 165695296.765op/s 165731230.533op/s 165780567.032op/s 0.16% -2.927 12.750 0.14% 16325.719op/s 1 200
credit_card/is_card_number_no_luhn/ execution_time 3.903µs 3.916µs ± 0.003µs 3.916µs ± 0.003µs 3.918µs 3.922µs 3.925µs 3.925µs 0.25% 0.275 0.571 0.09% 0.000µs 1 200
credit_card/is_card_number_no_luhn/ throughput 254751875.864op/s 255356993.675op/s ± 222016.049op/s 255381747.741op/s ± 166959.909op/s 255546250.756op/s 255622904.172op/s 255671920.893op/s 256241868.235op/s 0.34% -0.268 0.581 0.09% 15698.905op/s 1 200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 execution_time 64.203µs 64.510µs ± 0.142µs 64.503µs ± 0.093µs 64.599µs 64.738µs 64.907µs 65.077µs 0.89% 0.592 1.090 0.22% 0.010µs 1 200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 throughput 15366319.765op/s 15501604.186op/s ± 34194.246op/s 15503116.375op/s ± 22478.763op/s 15525374.571op/s 15553438.548op/s 15566850.817op/s 15575636.589op/s 0.47% -0.574 1.046 0.22% 2417.898op/s 1 200
credit_card/is_card_number_no_luhn/ 378282246310005 execution_time 58.146µs 58.387µs ± 0.148µs 58.350µs ± 0.085µs 58.452µs 58.693µs 58.770µs 59.108µs 1.30% 1.196 2.101 0.25% 0.010µs 1 200
credit_card/is_card_number_no_luhn/ 378282246310005 throughput 16918180.336op/s 17127105.659op/s ± 43408.362op/s 17137938.384op/s ± 25013.670op/s 17159287.874op/s 17181169.353op/s 17192662.987op/s 17198032.545op/s 0.35% -1.175 2.002 0.25% 3069.435op/s 1 200
credit_card/is_card_number_no_luhn/37828224631 execution_time 3.899µs 3.916µs ± 0.004µs 3.916µs ± 0.003µs 3.918µs 3.923µs 3.925µs 3.930µs 0.35% 0.284 2.334 0.09% 0.000µs 1 200
credit_card/is_card_number_no_luhn/37828224631 throughput 254448515.222op/s 255330845.614op/s ± 242532.230op/s 255344296.643op/s ± 167745.397op/s 255515314.063op/s 255622445.215op/s 255672766.798op/s 256450008.917op/s 0.43% -0.271 2.353 0.09% 17149.618op/s 1 200
credit_card/is_card_number_no_luhn/378282246310005 execution_time 54.609µs 54.960µs ± 0.256µs 54.895µs ± 0.164µs 55.115µs 55.400µs 55.785µs 55.830µs 1.70% 1.088 0.999 0.46% 0.018µs 1 200
credit_card/is_card_number_no_luhn/378282246310005 throughput 17911390.188op/s 18195377.570op/s ± 84397.579op/s 18216590.762op/s ± 54559.415op/s 18262727.474op/s 18293684.801op/s 18301515.634op/s 18312158.307op/s 0.52% -1.063 0.913 0.46% 5967.810op/s 1 200
credit_card/is_card_number_no_luhn/37828224631000521389798 execution_time 52.191µs 52.276µs ± 0.049µs 52.272µs ± 0.032µs 52.306µs 52.358µs 52.416µs 52.448µs 0.34% 0.733 0.729 0.09% 0.003µs 1 200
credit_card/is_card_number_no_luhn/37828224631000521389798 throughput 19066628.931op/s 19129406.200op/s ± 17926.536op/s 19130717.151op/s ± 11892.348op/s 19142090.395op/s 19155627.139op/s 19158560.608op/s 19160575.200op/s 0.16% -0.727 0.713 0.09% 1267.598op/s 1 200
credit_card/is_card_number_no_luhn/x371413321323331 execution_time 6.032µs 6.043µs ± 0.009µs 6.041µs ± 0.004µs 6.045µs 6.054µs 6.082µs 6.105µs 1.07% 3.250 14.231 0.16% 0.001µs 1 200
credit_card/is_card_number_no_luhn/x371413321323331 throughput 163801914.691op/s 165493815.531op/s ± 256521.843op/s 165548439.485op/s ± 108039.625op/s 165648910.090op/s 165726731.573op/s 165756535.257op/s 165769923.166op/s 0.13% -3.223 14.017 0.15% 18138.833op/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 [3.916µs; 3.917µs] or [-0.014%; +0.014%] None None None
credit_card/is_card_number/ throughput [255291193.252op/s; 255364602.952op/s] or [-0.014%; +0.014%] None None None
credit_card/is_card_number/ 3782-8224-6310-005 execution_time [79.592µs; 79.689µs] or [-0.061%; +0.061%] None None None
credit_card/is_card_number/ 3782-8224-6310-005 throughput [12549014.707op/s; 12564249.885op/s] or [-0.061%; +0.061%] None None None
credit_card/is_card_number/ 378282246310005 execution_time [73.062µs; 73.167µs] or [-0.072%; +0.072%] None None None
credit_card/is_card_number/ 378282246310005 throughput [13667728.328op/s; 13687379.297op/s] or [-0.072%; +0.072%] None None None
credit_card/is_card_number/37828224631 execution_time [3.916µs; 3.917µs] or [-0.014%; +0.014%] None None None
credit_card/is_card_number/37828224631 throughput [255310172.219op/s; 255380577.938op/s] or [-0.014%; +0.014%] None None None
credit_card/is_card_number/378282246310005 execution_time [69.665µs; 69.755µs] or [-0.065%; +0.065%] None None None
credit_card/is_card_number/378282246310005 throughput [14336149.263op/s; 14354749.344op/s] or [-0.065%; +0.065%] None None None
credit_card/is_card_number/37828224631000521389798 execution_time [52.271µs; 52.285µs] or [-0.014%; +0.014%] None None None
credit_card/is_card_number/37828224631000521389798 throughput [19125834.698op/s; 19131165.389op/s] or [-0.014%; +0.014%] None None None
credit_card/is_card_number/x371413321323331 execution_time [6.042µs; 6.044µs] or [-0.019%; +0.019%] None None None
credit_card/is_card_number/x371413321323331 throughput [165447743.668op/s; 165511739.309op/s] or [-0.019%; +0.019%] None None None
credit_card/is_card_number_no_luhn/ execution_time [3.916µs; 3.917µs] or [-0.012%; +0.012%] None None None
credit_card/is_card_number_no_luhn/ throughput [255326224.386op/s; 255387762.964op/s] or [-0.012%; +0.012%] None None None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 execution_time [64.490µs; 64.530µs] or [-0.031%; +0.031%] None None None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 throughput [15496865.193op/s; 15506343.180op/s] or [-0.031%; +0.031%] None None None
credit_card/is_card_number_no_luhn/ 378282246310005 execution_time [58.367µs; 58.408µs] or [-0.035%; +0.035%] None None None
credit_card/is_card_number_no_luhn/ 378282246310005 throughput [17121089.678op/s; 17133121.641op/s] or [-0.035%; +0.035%] None None None
credit_card/is_card_number_no_luhn/37828224631 execution_time [3.916µs; 3.917µs] or [-0.013%; +0.013%] None None None
credit_card/is_card_number_no_luhn/37828224631 throughput [255297232.979op/s; 255364458.248op/s] or [-0.013%; +0.013%] None None None
credit_card/is_card_number_no_luhn/378282246310005 execution_time [54.925µs; 54.996µs] or [-0.065%; +0.065%] None None None
credit_card/is_card_number_no_luhn/378282246310005 throughput [18183680.877op/s; 18207074.263op/s] or [-0.064%; +0.064%] None None None
credit_card/is_card_number_no_luhn/37828224631000521389798 execution_time [52.269µs; 52.282µs] or [-0.013%; +0.013%] None None None
credit_card/is_card_number_no_luhn/37828224631000521389798 throughput [19126921.754op/s; 19131890.645op/s] or [-0.013%; +0.013%] None None None
credit_card/is_card_number_no_luhn/x371413321323331 execution_time [6.041µs; 6.044µs] or [-0.022%; +0.022%] None None None
credit_card/is_card_number_no_luhn/x371413321323331 throughput [165458264.070op/s; 165529366.991op/s] or [-0.021%; +0.021%] None None None

Group 6

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 6f118be 1774949326 kowalski/temp-profiling-split-upload-function
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 187.359ns 190.474ns ± 2.485ns 190.069ns ± 1.359ns 191.283ns 194.508ns 201.394ns 203.955ns 7.31% 2.363 8.770 1.30% 0.176ns 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 [190.130ns; 190.818ns] or [-0.181%; +0.181%] None None None

Group 7

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 6f118be 1774949326 kowalski/temp-profiling-split-upload-function
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 534.329µs 535.382µs ± 0.910µs 535.134µs ± 0.407µs 535.729µs 537.342µs 538.415µs 541.114µs 1.12% 2.501 9.314 0.17% 0.064µs 1 200
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000... throughput 1848039.817op/s 1867832.298op/s ± 3162.676op/s 1868691.141op/s ± 1422.123op/s 1869844.831op/s 1870895.211op/s 1871253.775op/s 1871506.956op/s 0.15% -2.475 9.114 0.17% 223.635op/s 1 200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて execution_time 400.439µs 401.345µs ± 0.433µs 401.281µs ± 0.245µs 401.575µs 402.136µs 402.660µs 403.476µs 0.55% 1.248 2.935 0.11% 0.031µs 1 200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて throughput 2478459.092op/s 2491623.133op/s ± 2683.433op/s 2492019.873op/s ± 1521.854op/s 2493356.056op/s 2495177.743op/s 2496019.598op/s 2497261.526op/s 0.21% -1.238 2.886 0.11% 189.747op/s 1 200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters execution_time 189.510µs 190.029µs ± 0.273µs 189.970µs ± 0.155µs 190.189µs 190.557µs 190.779µs 191.019µs 0.55% 0.986 1.237 0.14% 0.019µs 1 200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters throughput 5235067.975op/s 5262368.070op/s ± 7538.599op/s 5263991.895op/s ± 4286.991op/s 5267433.153op/s 5271925.837op/s 5275379.996op/s 5276779.963op/s 0.24% -0.976 1.210 0.14% 533.059op/s 1 200
normalization/normalize_service/normalize_service/[empty string] execution_time 37.341µs 37.543µs ± 0.077µs 37.543µs ± 0.048µs 37.590µs 37.679µs 37.709µs 37.843µs 0.80% 0.305 0.486 0.20% 0.005µs 1 200
normalization/normalize_service/normalize_service/[empty string] throughput 26425240.635op/s 26636526.536op/s ± 54364.170op/s 26636307.618op/s ± 34245.330op/s 26671167.955op/s 26720577.130op/s 26751262.266op/s 26779984.257op/s 0.54% -0.290 0.460 0.20% 3844.127op/s 1 200
normalization/normalize_service/normalize_service/test_ASCII execution_time 45.777µs 45.937µs ± 0.122µs 45.915µs ± 0.056µs 45.980µs 46.091µs 46.153µs 47.165µs 2.72% 5.339 50.042 0.26% 0.009µs 1 200
normalization/normalize_service/normalize_service/test_ASCII throughput 21201987.804op/s 21769067.716op/s ± 56893.460op/s 21779298.518op/s ± 26404.187op/s 21799707.582op/s 21824611.483op/s 21839060.861op/s 21845031.348op/s 0.30% -5.156 47.549 0.26% 4022.975op/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 [535.255µs; 535.508µs] or [-0.024%; +0.024%] None None None
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000... throughput [1867393.982op/s; 1868270.615op/s] or [-0.023%; +0.023%] None None None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて execution_time [401.285µs; 401.405µs] or [-0.015%; +0.015%] None None None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて throughput [2491251.235op/s; 2491995.031op/s] or [-0.015%; +0.015%] None None None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters execution_time [189.991µs; 190.067µs] or [-0.020%; +0.020%] None None None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters throughput [5261323.293op/s; 5263412.848op/s] or [-0.020%; +0.020%] None None None
normalization/normalize_service/normalize_service/[empty string] execution_time [37.532µs; 37.553µs] or [-0.028%; +0.028%] None None None
normalization/normalize_service/normalize_service/[empty string] throughput [26628992.185op/s; 26644060.887op/s] or [-0.028%; +0.028%] None None None
normalization/normalize_service/normalize_service/test_ASCII execution_time [45.920µs; 45.954µs] or [-0.037%; +0.037%] None None None
normalization/normalize_service/normalize_service/test_ASCII throughput [21761182.829op/s; 21776952.602op/s] or [-0.036%; +0.036%] None None None

Group 8

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 6f118be 1774949326 kowalski/temp-profiling-split-upload-function
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 3.295ms 3.318ms ± 0.014ms 3.316ms ± 0.007ms 3.324ms 3.348ms 3.358ms 3.380ms 1.92% 1.294 2.498 0.41% 0.001ms 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 [3.316ms; 3.320ms] or [-0.057%; +0.057%] None None None

Group 9

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 6f118be 1774949326 kowalski/temp-profiling-split-upload-function
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 735.025µs 736.330µs ± 0.656µs 736.248µs ± 0.345µs 736.606µs 737.358µs 738.010µs 740.773µs 0.61% 1.962 9.729 0.09% 0.046µs 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 [736.239µs; 736.421µs] or [-0.012%; +0.012%] None None None

Group 10

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 6f118be 1774949326 kowalski/temp-profiling-split-upload-function
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
two way interface execution_time 18.788µs 27.776µs ± 10.698µs 19.558µs ± 0.640µs 37.202µs 47.208µs 48.000µs 77.738µs 297.47% 0.961 0.787 38.42% 0.756µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
two way interface execution_time [26.294µs; 29.259µs] or [-5.338%; +5.338%] None None None

Group 11

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 6f118be 1774949326 kowalski/temp-profiling-split-upload-function
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 10.757ms 10.788ms ± 0.015ms 10.787ms ± 0.010ms 10.797ms 10.811ms 10.830ms 10.862ms 0.70% 1.198 3.349 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 [10.786ms; 10.790ms] or [-0.020%; +0.020%] None None None

Group 12

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 6f118be 1774949326 kowalski/temp-profiling-split-upload-function
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 161.181µs 162.147µs ± 0.377µs 162.092µs ± 0.154µs 162.282µs 162.647µs 163.868µs 164.493µs 1.48% 2.587 12.415 0.23% 0.027µs 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 [162.094µs; 162.199µs] or [-0.032%; +0.032%] None None None

Group 13

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 6f118be 1774949326 kowalski/temp-profiling-split-upload-function
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 13.947ms 14.010ms ± 0.024ms 14.008ms ± 0.014ms 14.023ms 14.046ms 14.084ms 14.168ms 1.14% 1.654 8.594 0.17% 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 [14.007ms; 14.013ms] 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 6f118be 1774949326 kowalski/temp-profiling-split-upload-function
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 4.938µs 4.993µs ± 0.036µs 4.973µs ± 0.014µs 5.031µs 5.055µs 5.059µs 5.090µs 2.35% 0.622 -1.159 0.72% 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 [4.988µs; 4.998µs] or [-0.101%; +0.101%] None None None

Group 15

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 6f118be 1774949326 kowalski/temp-profiling-split-upload-function
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 239.924ns 250.414ns ± 11.965ns 244.075ns ± 2.443ns 253.179ns 278.606ns 284.187ns 284.543ns 16.58% 1.457 0.888 4.77% 0.846ns 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 [248.756ns; 252.073ns] or [-0.662%; +0.662%] None None None

Group 16

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 6f118be 1774949326 kowalski/temp-profiling-split-upload-function
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 145.106µs 147.261µs ± 1.938µs 146.997µs ± 0.563µs 147.587µs 148.735µs 156.537µs 167.081µs 13.66% 6.601 58.102 1.31% 0.137µs 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 [146.992µs; 147.529µs] or [-0.182%; +0.182%] None None None

Group 17

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 6f118be 1774949326 kowalski/temp-profiling-split-upload-function
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 49.740ms 50.152ms ± 0.909ms 50.025ms ± 0.065ms 50.095ms 50.205ms 54.976ms 58.368ms 16.68% 7.913 64.557 1.81% 0.064ms 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 [50.026ms; 50.278ms] or [-0.251%; +0.251%] None None None

Group 18

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 6f118be 1774949326 kowalski/temp-profiling-split-upload-function
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 185.592µs 186.111µs ± 0.271µs 186.099µs ± 0.207µs 186.297µs 186.562µs 186.676µs 187.039µs 0.51% 0.354 -0.437 0.15% 0.019µs 1 200
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... throughput 5346470.681op/s 5373150.490op/s ± 7822.356op/s 5373478.954op/s ± 5980.220op/s 5379681.079op/s 5384118.348op/s 5386218.610op/s 5388161.831op/s 0.27% -0.348 -0.449 0.15% 553.124op/s 1 200
normalization/normalize_name/normalize_name/bad-name execution_time 17.876µs 17.970µs ± 0.054µs 17.961µs ± 0.024µs 17.989µs 18.082µs 18.161µs 18.227µs 1.48% 1.682 4.246 0.30% 0.004µs 1 200
normalization/normalize_name/normalize_name/bad-name throughput 54862879.683op/s 55648881.273op/s ± 167924.066op/s 55676851.554op/s ± 74426.329op/s 55745133.251op/s 55867241.032op/s 55913093.206op/s 55940900.084op/s 0.47% -1.652 4.112 0.30% 11874.025op/s 1 200
normalization/normalize_name/normalize_name/good execution_time 10.326µs 10.484µs ± 0.058µs 10.486µs ± 0.034µs 10.519µs 10.579µs 10.624µs 10.677µs 1.82% 0.130 0.485 0.55% 0.004µs 1 200
normalization/normalize_name/normalize_name/good throughput 93658464.044op/s 95382854.491op/s ± 528276.878op/s 95365179.498op/s ± 309662.720op/s 95685428.069op/s 96296952.625op/s 96513590.706op/s 96844853.805op/s 1.55% -0.089 0.449 0.55% 37354.816op/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 [186.073µs; 186.149µs] or [-0.020%; +0.020%] None None None
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... throughput [5372066.386op/s; 5374234.593op/s] or [-0.020%; +0.020%] None None None
normalization/normalize_name/normalize_name/bad-name execution_time [17.962µs; 17.978µs] or [-0.042%; +0.042%] None None None
normalization/normalize_name/normalize_name/bad-name throughput [55625608.613op/s; 55672153.934op/s] or [-0.042%; +0.042%] None None None
normalization/normalize_name/normalize_name/good execution_time [10.476µs; 10.492µs] or [-0.077%; +0.077%] None None None
normalization/normalize_name/normalize_name/good throughput [95309640.397op/s; 95456068.586op/s] or [-0.077%; +0.077%] None None None

Group 19

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 6f118be 1774949326 kowalski/temp-profiling-split-upload-function
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 33.494µs 34.104µs ± 0.899µs 33.710µs ± 0.103µs 33.882µs 36.000µs 36.077µs 37.341µs 10.77% 1.707 1.197 2.63% 0.064µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
redis/obfuscate_redis_string execution_time [33.979µs; 34.228µs] or [-0.366%; +0.366%] None None None

Baseline

Omitted due to size.

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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% (+2.95 KB) 👌
aarch64-unknown-linux-gnu
Artifact Baseline Commit Change
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.a 114.29 MB 114.31 MB +0% (+11.58 KB) 👌
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.so 11.29 MB 11.29 MB +0% (+192 B) 👌
libdatadog-x64-windows
Artifact Baseline Commit Change
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.dll 27.16 MB 27.17 MB +.01% (+3.00 KB) 🔍
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.lib 76.26 KB 76.55 KB +.37% (+294 B) 🔍
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.pdb 186.48 MB 186.46 MB -0% (-16.00 KB) 👌
/libdatadog-x64-windows/debug/static/datadog_profiling_ffi.lib 917.71 MB 917.74 MB +0% (+30.49 KB) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.dll 9.93 MB 9.93 MB +0% (+512 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.lib 76.26 KB 76.55 KB +.37% (+294 B) 🔍
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.pdb 24.76 MB 24.77 MB +.03% (+8.00 KB) 🔍
/libdatadog-x64-windows/release/static/datadog_profiling_ffi.lib 51.42 MB 51.43 MB +0% (+988 B) 👌
libdatadog-x86-windows
Artifact Baseline Commit Change
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.dll 22.97 MB 22.97 MB +.01% (+2.50 KB) 🔍
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.lib 77.44 KB 77.74 KB +.37% (+300 B) 🔍
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.pdb 190.28 MB 190.26 MB --.01% (-24.00 KB) 💪
/libdatadog-x86-windows/debug/static/datadog_profiling_ffi.lib 900.84 MB 900.87 MB +0% (+30.20 KB) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.dll 7.53 MB 7.53 MB +.01% (+1.00 KB) 🔍
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.lib 77.44 KB 77.74 KB +.37% (+300 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 47.06 MB 47.07 MB +0% (+1.30 KB) 👌
x86_64-alpine-linux-musl
Artifact Baseline Commit Change
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.a 86.54 MB 86.55 MB +0% (+2.59 KB) 👌
/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 107.17 MB +.01% (+11.29 KB) 🔍
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.so 11.98 MB 11.98 MB +0% (+96 B) 👌

@KowalskiThomas KowalskiThomas force-pushed the kowalski/temp-profiling-split-upload-function branch from 7a18d4d to 0ba86f7 Compare March 31, 2026 08:41
@github-actions github-actions bot removed the profiling Relates to the profiling* modules. label Mar 31, 2026
@KowalskiThomas KowalskiThomas marked this pull request as ready for review March 31, 2026 08:48
@KowalskiThomas KowalskiThomas requested review from a team as code owners March 31, 2026 08:48
@KowalskiThomas KowalskiThomas mentioned this pull request Mar 31, 2026
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LGTM

@KowalskiThomas KowalskiThomas force-pushed the kowalski/temp-profiling-split-upload-function branch from 1e58e48 to cdb4861 Compare March 31, 2026 09:27
@KowalskiThomas KowalskiThomas requested review from a team as code owners March 31, 2026 09:27
@KowalskiThomas KowalskiThomas force-pushed the kowalski/temp-profiling-split-upload-function branch from cdb4861 to 6f118be Compare March 31, 2026 09:28
@KowalskiThomas KowalskiThomas removed request for a team March 31, 2026 09:29
gh-worker-dd-mergequeue-cf854d bot pushed a commit that referenced this pull request Apr 1, 2026
@KowalskiThomas
chore: fix unused variable in ffi example (#1825)
cdf941e 
# What does this PR do?

This PR fixes an unused variable (`c`) which happens when the code is compiled with `NDEBUG` (which I think I accidentally did when I ran FFI tests for #1733). To work around this, I extracted the `c.load` from the `assert` and then always do `std::ignore = value` so that everything is always used. 

Co-authored-by: thomas.kowalski <thomas.kowalski@datadoghq.com>
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@taegyunkim taegyunkim taegyunkim approved these changes

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