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chore(agents): retrieve container tags hash from /info endpoint#1700

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chore(agents): retrieve container tags hash from /info endpoint#1700
dubloom wants to merge 3 commits intomainfrom
dubloom/container-back-propagation

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@dubloom dubloom commented Mar 10, 2026

What does this PR do?

A brief description of the change being made with this pull request.

Motivation

What inspired you to submit this pull request?

Additional Notes

Anything else we should know when reviewing?

How to test the change?

Describe here in detail how the change can be validated.

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📚 Documentation Check Results

⚠️ 796 documentation warning(s) found

📦 libdd-data-pipeline - 796 warning(s)

Updated: 2026-03-12 16:13:00 UTC | Commit: 04b97ab | missing-docs job results

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Clippy Allow Annotation Report

Comparing clippy allow annotations between branches:

  • Base Branch: origin/main
  • PR Branch: origin/dubloom/container-back-propagation

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 28 28 No change (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 59 59 No change (0%)
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 9 9 No change (0%)
libdd-trace-utils 15 15 No change (0%)
Total 208 220 ⚠️ +12 (+5.8%)

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

⚠️ 1 issue(s) found, showing only errors (advisories, bans, sources)

📦 libdd-data-pipeline - 1 error(s)

Show output 
error[vulnerability]: Denial of Service via Stack Exhaustion
    ┌─ /home/runner/work/libdatadog/libdatadog/Cargo.lock:293:1
    │
293 │ time 0.3.41 registry+https://github.com/rust-lang/crates.io-index
    │ ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ security vulnerability detected
    │
    ├ ID: RUSTSEC-2026-0009
    ├ Advisory: https://rustsec.org/advisories/RUSTSEC-2026-0009
    ├ ## Impact
      
      When user-provided input is provided to any type that parses with the RFC 2822 format, a denial of
      service attack via stack exhaustion is possible. The attack relies on formally deprecated and
      rarely-used features that are part of the RFC 2822 format used in a malicious manner. Ordinary,
      non-malicious input will never encounter this scenario.
      
      ## Patches
      
      A limit to the depth of recursion was added in v0.3.47. From this version, an error will be returned
      rather than exhausting the stack.
      
      ## Workarounds
      
      Limiting the length of user input is the simplest way to avoid stack exhaustion, as the amount of
      the stack consumed would be at most a factor of the length of the input.
    ├ Announcement: https://github.com/time-rs/time/blob/main/CHANGELOG.md#0347-2026-02-05
    ├ Solution: Upgrade to >=0.3.47 (try `cargo update -p time`)
    ├ time v0.3.41
      └── tracing-appender v0.2.3
          └── libdd-log v1.0.0
              └── (dev) libdd-data-pipeline v2.0.0

advisories FAILED, bans ok, sources ok

Updated: 2026-03-12 16:16:01 UTC | Commit: 04b97ab | dependency-check job results

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Benchmarks

Comparison

Benchmark execution time: 2026-03-12 16:26:51

Comparing candidate commit 51c7f29 in PR branch dubloom/container-back-propagation with baseline commit 8fae837 in branch main.

Found 8 performance improvements and 16 performance regressions! Performance is the same for 33 metrics, 2 unstable metrics.

Explanation

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

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

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

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

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

More details about the CI and significant changes

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

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

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

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

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

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

scenario:concentrator/add_spans_to_concentrator

  • 🟩 execution_time [-2.398ms; -2.392ms] or [-18.399%; -18.354%]

scenario:credit_card/is_card_number/ 378282246310005

  • 🟥 execution_time [+4.817µs; +4.911µs] or [+7.090%; +7.228%]
  • 🟥 throughput [-991967.944op/s; -974206.101op/s] or [-6.739%; -6.619%]

scenario:credit_card/is_card_number/378282246310005

  • 🟥 execution_time [+5.049µs; +5.160µs] or [+7.802%; +7.974%]
  • 🟥 throughput [-1140596.390op/s; -1117820.990op/s] or [-7.382%; -7.234%]

scenario:credit_card/is_card_number/37828224631000521389798

  • 🟥 execution_time [+6.465µs; +6.497µs] or [+14.136%; +14.207%]
  • 🟥 throughput [-2721947.438op/s; -2706725.051op/s] or [-12.448%; -12.378%]

scenario:credit_card/is_card_number/x371413321323331

  • 🟩 execution_time [-596.178ns; -592.657ns] or [-8.991%; -8.938%]
  • 🟩 throughput [+14809575.704op/s; +14892819.470op/s] or [+9.820%; +9.875%]

scenario:credit_card/is_card_number_no_luhn/ 378282246310005

  • 🟥 execution_time [+4.929µs; +4.970µs] or [+9.223%; +9.300%]
  • 🟥 throughput [-1592022.482op/s; -1579803.606op/s] or [-8.508%; -8.443%]

scenario:credit_card/is_card_number_no_luhn/378282246310005

  • 🟥 execution_time [+4.661µs; +4.744µs] or [+9.278%; +9.442%]
  • 🟥 throughput [-1716689.867op/s; -1689408.988op/s] or [-8.625%; -8.488%]

scenario:credit_card/is_card_number_no_luhn/37828224631000521389798

  • 🟥 execution_time [+6.529µs; +6.557µs] or [+14.289%; +14.349%]
  • 🟥 throughput [-2747713.305op/s; -2734819.983op/s] or [-12.555%; -12.496%]

scenario:credit_card/is_card_number_no_luhn/x371413321323331

  • 🟩 execution_time [-595.852ns; -591.664ns] or [-8.986%; -8.923%]
  • 🟩 throughput [+14780709.917op/s; +14881977.304op/s] or [+9.801%; +9.868%]

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

  • 🟩 execution_time [-19.982µs; -19.778µs] or [-9.708%; -9.609%]
  • 🟩 throughput [+516912.898op/s; +521836.445op/s] or [+10.639%; +10.741%]

scenario:normalization/normalize_name/normalize_name/bad-name

  • 🟩 throughput [+2198258.988op/s; +2304758.138op/s] or [+4.119%; +4.319%]

scenario:normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000...

  • 🟥 execution_time [+41.151µs; +41.420µs] or [+8.328%; +8.382%]
  • 🟥 throughput [-156522.533op/s; -155558.547op/s] or [-7.734%; -7.687%]

scenario:normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters

  • 🟥 execution_time [+22.496µs; +22.559µs] or [+13.422%; +13.460%]
  • 🟥 throughput [-707911.522op/s; -705941.518op/s] or [-11.865%; -11.832%]

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 51c7f29 1773331729 dubloom/container-back-propagation
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 534.395µs 535.426µs ± 0.871µs 535.251µs ± 0.387µs 535.812µs 536.402µs 536.852µs 544.868µs 1.80% 6.495 67.239 0.16% 0.062µs 1 200
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000... throughput 1835305.711op/s 1867675.607op/s ± 3005.949op/s 1868281.741op/s ± 1351.792op/s 1869324.538op/s 1870600.496op/s 1871088.925op/s 1871274.581op/s 0.16% -6.364 65.338 0.16% 212.553op/s 1 200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて execution_time 380.292µs 380.889µs ± 0.263µs 380.883µs ± 0.166µs 381.044µs 381.349µs 381.553µs 381.621µs 0.19% 0.233 -0.107 0.07% 0.019µs 1 200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて throughput 2620398.481op/s 2625437.743op/s ± 1811.194op/s 2625478.315op/s ± 1141.610op/s 2626646.547op/s 2628365.215op/s 2629154.001op/s 2629559.843op/s 0.16% -0.229 -0.110 0.07% 128.071op/s 1 200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters execution_time 189.688µs 190.132µs ± 0.165µs 190.128µs ± 0.110µs 190.253µs 190.405µs 190.508µs 190.557µs 0.23% 0.115 -0.304 0.09% 0.012µs 1 200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters throughput 5247773.632op/s 5259506.908op/s ± 4554.129op/s 5259619.186op/s ± 3052.587op/s 5262392.327op/s 5267029.055op/s 5268780.119op/s 5271819.758op/s 0.23% -0.110 -0.305 0.09% 322.026op/s 1 200
normalization/normalize_service/normalize_service/[empty string] execution_time 37.367µs 37.511µs ± 0.059µs 37.509µs ± 0.040µs 37.548µs 37.620µs 37.653µs 37.682µs 0.46% 0.326 -0.061 0.16% 0.004µs 1 200
normalization/normalize_service/normalize_service/[empty string] throughput 26537693.476op/s 26658856.470op/s ± 41728.418op/s 26660570.707op/s ± 28310.166op/s 26688461.199op/s 26715335.224op/s 26751528.938op/s 26761261.354op/s 0.38% -0.318 -0.068 0.16% 2950.645op/s 1 200
normalization/normalize_service/normalize_service/test_ASCII execution_time 45.806µs 45.921µs ± 0.124µs 45.904µs ± 0.043µs 45.951µs 46.032µs 46.103µs 47.422µs 3.31% 9.025 106.192 0.27% 0.009µs 1 200
normalization/normalize_service/normalize_service/test_ASCII throughput 21087288.723op/s 21776893.091op/s ± 57367.791op/s 21784754.785op/s ± 20398.748op/s 21801859.493op/s 21820643.716op/s 21828491.217op/s 21831206.448op/s 0.21% -8.810 102.676 0.26% 4056.515op/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 [535.306µs; 535.547µs] or [-0.023%; +0.023%] None None None
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000... throughput [1867259.012op/s; 1868092.203op/s] or [-0.022%; +0.022%] None None None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて execution_time [380.853µs; 380.925µs] or [-0.010%; +0.010%] None None None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて throughput [2625186.729op/s; 2625688.757op/s] or [-0.010%; +0.010%] None None None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters execution_time [190.109µs; 190.155µs] or [-0.012%; +0.012%] None None None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters throughput [5258875.749op/s; 5260138.066op/s] or [-0.012%; +0.012%] None None None
normalization/normalize_service/normalize_service/[empty string] execution_time [37.503µs; 37.519µs] or [-0.022%; +0.022%] None None None
normalization/normalize_service/normalize_service/[empty string] throughput [26653073.313op/s; 26664639.628op/s] or [-0.022%; +0.022%] None None None
normalization/normalize_service/normalize_service/test_ASCII execution_time [45.903µs; 45.938µs] or [-0.037%; +0.037%] None None None
normalization/normalize_service/normalize_service/test_ASCII throughput [21768942.466op/s; 21784843.715op/s] or [-0.037%; +0.037%] None None None

Group 2

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 51c7f29 1773331729 dubloom/container-back-propagation
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 188.132ns 190.421ns ± 1.995ns 190.264ns ± 1.516ns 191.411ns 194.092ns 196.084ns 200.482ns 5.37% 1.399 3.166 1.05% 0.141ns 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 [190.144ns; 190.697ns] or [-0.145%; +0.145%] None None None

Group 3

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 51c7f29 1773331729 dubloom/container-back-propagation
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 2.454µs 2.494µs ± 0.019µs 2.491µs ± 0.010µs 2.506µs 2.532µs 2.538µs 2.543µs 2.11% 0.383 -0.322 0.78% 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 [2.492µs; 2.497µs] or [-0.108%; +0.108%] None None None

Group 4

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 51c7f29 1773331729 dubloom/container-back-propagation
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 239.993ns 250.817ns ± 13.296ns 245.450ns ± 3.732ns 252.170ns 281.845ns 296.563ns 300.263ns 22.33% 1.997 3.480 5.29% 0.940ns 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 [248.974ns; 252.659ns] or [-0.735%; +0.735%] None None None

Group 5

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 51c7f29 1773331729 dubloom/container-back-propagation
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 4.161ms 4.166ms ± 0.007ms 4.165ms ± 0.001ms 4.167ms 4.170ms 4.173ms 4.265ms 2.40% 12.095 159.015 0.18% 0.001ms 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
profile_add_sample_frames_x1000 execution_time [4.165ms; 4.167ms] or [-0.025%; +0.025%] None None None

Group 6

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 51c7f29 1773331729 dubloom/container-back-propagation
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 1.181µs 3.194µs ± 1.399µs 2.988µs ± 0.028µs 3.012µs 3.651µs 13.745µs 14.739µs 393.22% 7.335 55.076 43.68% 0.099µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
write only interface execution_time [3.000µs; 3.388µs] or [-6.069%; +6.069%] None None None

Group 7

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 51c7f29 1773331729 dubloom/container-back-propagation
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 3.913µs ± 0.003µs 3.913µs ± 0.002µs 3.915µs 3.918µs 3.919µs 3.920µs 0.18% -0.560 3.908 0.07% 0.000µs 1 200
credit_card/is_card_number/ throughput 255102957.039op/s 255564605.714op/s ± 191208.613op/s 255560144.733op/s ± 121439.276op/s 255689203.526op/s 255835014.371op/s 255887566.610op/s 256641025.649op/s 0.42% 0.573 3.974 0.07% 13520.491op/s 1 200
credit_card/is_card_number/ 3782-8224-6310-005 execution_time 79.031µs 79.575µs ± 0.395µs 79.521µs ± 0.243µs 79.773µs 80.250µs 80.845µs 81.523µs 2.52% 1.412 3.129 0.50% 0.028µs 1 200
credit_card/is_card_number/ 3782-8224-6310-005 throughput 12266484.110op/s 12567103.955op/s ± 62014.033op/s 12575347.948op/s ± 38569.618op/s 12612946.266op/s 12641603.645op/s 12652462.550op/s 12653209.276op/s 0.62% -1.367 2.900 0.49% 4385.054op/s 1 200
credit_card/is_card_number/ 378282246310005 execution_time 72.301µs 72.801µs ± 0.331µs 72.721µs ± 0.224µs 73.022µs 73.414µs 73.735µs 73.871µs 1.58% 0.723 -0.029 0.45% 0.023µs 1 200
credit_card/is_card_number/ 378282246310005 throughput 13537044.269op/s 13736327.280op/s ± 62273.839op/s 13751110.072op/s ± 42296.680op/s 13784707.595op/s 13816475.943op/s 13825646.646op/s 13831053.481op/s 0.58% -0.704 -0.075 0.45% 4403.425op/s 1 200
credit_card/is_card_number/37828224631 execution_time 3.891µs 3.912µs ± 0.004µs 3.912µs ± 0.001µs 3.914µs 3.917µs 3.921µs 3.952µs 1.02% 4.321 49.111 0.10% 0.000µs 1 200
credit_card/is_card_number/37828224631 throughput 253033507.594op/s 255600473.852op/s ± 262108.294op/s 255626136.832op/s ± 95448.576op/s 255711698.810op/s 255829649.352op/s 255914027.309op/s 256985208.727op/s 0.53% -4.222 48.213 0.10% 18533.855op/s 1 200
credit_card/is_card_number/378282246310005 execution_time 69.237µs 69.823µs ± 0.397µs 69.763µs ± 0.241µs 69.983µs 70.589µs 71.014µs 71.499µs 2.49% 1.205 1.698 0.57% 0.028µs 1 200
credit_card/is_card_number/378282246310005 throughput 13986153.902op/s 14322475.135op/s ± 80857.869op/s 14334268.121op/s ± 49322.641op/s 14384560.363op/s 14418119.287op/s 14436865.123op/s 14443176.432op/s 0.76% -1.167 1.559 0.56% 5717.515op/s 1 200
credit_card/is_card_number/37828224631000521389798 execution_time 52.149µs 52.213µs ± 0.032µs 52.213µs ± 0.021µs 52.231µs 52.270µs 52.292µs 52.308µs 0.18% 0.331 -0.068 0.06% 0.002µs 1 200
credit_card/is_card_number/37828224631000521389798 throughput 19117466.075op/s 19152271.645op/s ± 11700.028op/s 19152444.483op/s ± 7699.325op/s 19160798.922op/s 19170925.184op/s 19174062.134op/s 19175943.779op/s 0.12% -0.327 -0.073 0.06% 827.317op/s 1 200
credit_card/is_card_number/x371413321323331 execution_time 6.028µs 6.036µs ± 0.005µs 6.036µs ± 0.002µs 6.038µs 6.042µs 6.069µs 6.073µs 0.62% 4.147 25.263 0.09% 0.000µs 1 200
credit_card/is_card_number/x371413321323331 throughput 164663017.880op/s 165666652.277op/s ± 145635.046op/s 165676080.541op/s ± 63172.360op/s 165743713.700op/s 165821050.283op/s 165869731.760op/s 165885916.997op/s 0.13% -4.120 25.042 0.09% 10297.953op/s 1 200
credit_card/is_card_number_no_luhn/ execution_time 3.894µs 3.913µs ± 0.003µs 3.913µs ± 0.002µs 3.915µs 3.917µs 3.920µs 3.921µs 0.22% -1.031 7.245 0.08% 0.000µs 1 200
credit_card/is_card_number_no_luhn/ throughput 255011128.303op/s 255561077.673op/s ± 195354.296op/s 255571848.765op/s ± 137953.024op/s 255696359.173op/s 255825202.926op/s 255854990.259op/s 256820513.810op/s 0.49% 1.050 7.373 0.08% 13813.635op/s 1 200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 execution_time 64.083µs 64.469µs ± 0.144µs 64.450µs ± 0.098µs 64.565µs 64.715µs 64.814µs 64.858µs 0.63% 0.326 -0.246 0.22% 0.010µs 1 200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 throughput 15418286.246op/s 15511385.436op/s ± 34593.430op/s 15515958.587op/s ± 23704.645op/s 15535925.228op/s 15560926.984op/s 15578103.776op/s 15604874.963op/s 0.57% -0.315 -0.252 0.22% 2446.125op/s 1 200
credit_card/is_card_number_no_luhn/ 378282246310005 execution_time 58.139µs 58.393µs ± 0.145µs 58.364µs ± 0.086µs 58.463µs 58.666µs 58.761µs 58.948µs 1.00% 0.790 0.591 0.25% 0.010µs 1 200
credit_card/is_card_number_no_luhn/ 378282246310005 throughput 16964015.792op/s 17125437.960op/s ± 42364.307op/s 17133874.243op/s ± 25300.563op/s 17155727.198op/s 17184453.713op/s 17197528.664op/s 17200192.443op/s 0.39% -0.776 0.554 0.25% 2995.609op/s 1 200
credit_card/is_card_number_no_luhn/37828224631 execution_time 3.895µs 3.912µs ± 0.003µs 3.912µs ± 0.002µs 3.914µs 3.916µs 3.917µs 3.918µs 0.15% -1.037 7.330 0.07% 0.000µs 1 200
credit_card/is_card_number_no_luhn/37828224631 throughput 255255073.819op/s 255624129.166op/s ± 167256.885op/s 255633590.254op/s ± 112261.606op/s 255739429.137op/s 255858838.315op/s 255899187.617op/s 256708596.072op/s 0.42% 1.054 7.445 0.07% 11826.848op/s 1 200
credit_card/is_card_number_no_luhn/378282246310005 execution_time 54.563µs 54.944µs ± 0.296µs 54.869µs ± 0.182µs 55.074µs 55.527µs 55.867µs 55.992µs 2.05% 1.103 0.825 0.54% 0.021µs 1 200
credit_card/is_card_number_no_luhn/378282246310005 throughput 17859590.841op/s 18200904.860op/s ± 97452.496op/s 18225307.671op/s ± 60323.942op/s 18282025.048op/s 18307830.375op/s 18320910.897op/s 18327417.706op/s 0.56% -1.077 0.742 0.53% 6890.932op/s 1 200
credit_card/is_card_number_no_luhn/37828224631000521389798 execution_time 52.160µs 52.237µs ± 0.037µs 52.236µs ± 0.029µs 52.264µs 52.299µs 52.318µs 52.330µs 0.18% 0.178 -0.706 0.07% 0.003µs 1 200
credit_card/is_card_number_no_luhn/37828224631000521389798 throughput 19109541.165op/s 19143562.688op/s ± 13629.269op/s 19143722.245op/s ± 10598.422op/s 19154916.987op/s 19163942.277op/s 19168293.018op/s 19171905.490op/s 0.15% -0.175 -0.707 0.07% 963.735op/s 1 200
credit_card/is_card_number_no_luhn/x371413321323331 execution_time 6.028µs 6.037µs ± 0.008µs 6.036µs ± 0.003µs 6.039µs 6.046µs 6.075µs 6.080µs 0.73% 3.365 12.856 0.13% 0.001µs 1 200
credit_card/is_card_number_no_luhn/x371413321323331 throughput 164464917.807op/s 165638090.062op/s ± 221883.510op/s 165667562.292op/s ± 70290.559op/s 165747867.986op/s 165833636.229op/s 165872853.454op/s 165898647.040op/s 0.14% -3.351 12.773 0.13% 15689.533op/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 [3.913µs; 3.913µs] or [-0.010%; +0.010%] None None None
credit_card/is_card_number/ throughput [255538106.040op/s; 255591105.389op/s] or [-0.010%; +0.010%] None None None
credit_card/is_card_number/ 3782-8224-6310-005 execution_time [79.520µs; 79.630µs] or [-0.069%; +0.069%] None None None
credit_card/is_card_number/ 3782-8224-6310-005 throughput [12558509.407op/s; 12575698.504op/s] or [-0.068%; +0.068%] None None None
credit_card/is_card_number/ 378282246310005 execution_time [72.755µs; 72.847µs] or [-0.063%; +0.063%] None None None
credit_card/is_card_number/ 378282246310005 throughput [13727696.725op/s; 13744957.835op/s] or [-0.063%; +0.063%] None None None
credit_card/is_card_number/37828224631 execution_time [3.912µs; 3.913µs] or [-0.014%; +0.014%] None None None
credit_card/is_card_number/37828224631 throughput [255564148.163op/s; 255636799.541op/s] or [-0.014%; +0.014%] None None None
credit_card/is_card_number/378282246310005 execution_time [69.768µs; 69.878µs] or [-0.079%; +0.079%] None None None
credit_card/is_card_number/378282246310005 throughput [14311269.012op/s; 14333681.258op/s] or [-0.078%; +0.078%] None None None
credit_card/is_card_number/37828224631000521389798 execution_time [52.209µs; 52.218µs] or [-0.008%; +0.008%] None None None
credit_card/is_card_number/37828224631000521389798 throughput [19150650.134op/s; 19153893.157op/s] or [-0.008%; +0.008%] None None None
credit_card/is_card_number/x371413321323331 execution_time [6.035µs; 6.037µs] or [-0.012%; +0.012%] None None None
credit_card/is_card_number/x371413321323331 throughput [165646468.660op/s; 165686835.894op/s] or [-0.012%; +0.012%] None None None
credit_card/is_card_number_no_luhn/ execution_time [3.913µs; 3.913µs] or [-0.011%; +0.011%] None None None
credit_card/is_card_number_no_luhn/ throughput [255534003.446op/s; 255588151.899op/s] or [-0.011%; +0.011%] None None None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 execution_time [64.449µs; 64.489µs] or [-0.031%; +0.031%] None None None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 throughput [15506591.120op/s; 15516179.753op/s] or [-0.031%; +0.031%] None None None
credit_card/is_card_number_no_luhn/ 378282246310005 execution_time [58.373µs; 58.413µs] or [-0.034%; +0.034%] None None None
credit_card/is_card_number_no_luhn/ 378282246310005 throughput [17119566.675op/s; 17131309.246op/s] or [-0.034%; +0.034%] None None None
credit_card/is_card_number_no_luhn/37828224631 execution_time [3.912µs; 3.912µs] or [-0.009%; +0.009%] None None None
credit_card/is_card_number_no_luhn/37828224631 throughput [255600948.970op/s; 255647309.362op/s] or [-0.009%; +0.009%] None None None
credit_card/is_card_number_no_luhn/378282246310005 execution_time [54.903µs; 54.985µs] or [-0.075%; +0.075%] None None None
credit_card/is_card_number_no_luhn/378282246310005 throughput [18187398.881op/s; 18214410.839op/s] or [-0.074%; +0.074%] None None None
credit_card/is_card_number_no_luhn/37828224631000521389798 execution_time [52.232µs; 52.242µs] or [-0.010%; +0.010%] None None None
credit_card/is_card_number_no_luhn/37828224631000521389798 throughput [19141673.803op/s; 19145451.574op/s] or [-0.010%; +0.010%] None None None
credit_card/is_card_number_no_luhn/x371413321323331 execution_time [6.036µs; 6.038µs] or [-0.019%; +0.019%] None None None
credit_card/is_card_number_no_luhn/x371413321323331 throughput [165607339.141op/s; 165668840.982op/s] or [-0.019%; +0.019%] None None None

Group 8

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 51c7f29 1773331729 dubloom/container-back-propagation
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 86.215µs 86.509µs ± 0.241µs 86.477µs ± 0.050µs 86.544µs 86.633µs 86.856µs 89.654µs 3.67% 11.248 143.787 0.28% 0.017µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
sql/obfuscate_sql_string execution_time [86.476µs; 86.543µs] or [-0.039%; +0.039%] None None None

Group 9

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 51c7f29 1773331729 dubloom/container-back-propagation
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 185.547µs 185.947µs ± 0.211µs 185.916µs ± 0.145µs 186.095µs 186.325µs 186.478µs 186.518µs 0.32% 0.501 -0.344 0.11% 0.015µs 1 200
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... throughput 5361407.091op/s 5377869.866op/s ± 6098.363op/s 5378783.697op/s ± 4183.803op/s 5382498.148op/s 5386344.734op/s 5389152.131op/s 5389477.315op/s 0.20% -0.496 -0.350 0.11% 431.219op/s 1 200
normalization/normalize_name/normalize_name/bad-name execution_time 17.884µs 17.980µs ± 0.045µs 17.980µs ± 0.028µs 18.007µs 18.050µs 18.093µs 18.189µs 1.16% 0.470 1.826 0.25% 0.003µs 1 200
normalization/normalize_name/normalize_name/bad-name throughput 54978004.178op/s 55616784.300op/s ± 137971.394op/s 55617352.614op/s ± 85300.073op/s 55702607.058op/s 55865262.216op/s 55898927.640op/s 55915639.745op/s 0.54% -0.443 1.740 0.25% 9756.051op/s 1 200
normalization/normalize_name/normalize_name/good execution_time 10.264µs 10.375µs ± 0.054µs 10.371µs ± 0.036µs 10.408µs 10.474µs 10.507µs 10.545µs 1.67% 0.443 -0.129 0.52% 0.004µs 1 200
normalization/normalize_name/normalize_name/good throughput 94834330.890op/s 96387496.943op/s ± 504937.186op/s 96420357.707op/s ± 337591.311op/s 96757204.306op/s 97142355.449op/s 97338528.738op/s 97426968.523op/s 1.04% -0.417 -0.163 0.52% 35704.451op/s 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... execution_time [185.918µs; 185.977µs] or [-0.016%; +0.016%] None None None
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... throughput [5377024.692op/s; 5378715.041op/s] or [-0.016%; +0.016%] None None None
normalization/normalize_name/normalize_name/bad-name execution_time [17.974µs; 17.986µs] or [-0.034%; +0.034%] None None None
normalization/normalize_name/normalize_name/bad-name throughput [55597662.792op/s; 55635905.808op/s] or [-0.034%; +0.034%] None None None
normalization/normalize_name/normalize_name/good execution_time [10.368µs; 10.383µs] or [-0.073%; +0.073%] None None None
normalization/normalize_name/normalize_name/good throughput [96317517.506op/s; 96457476.381op/s] or [-0.073%; +0.073%] None None None

Group 10

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 51c7f29 1773331729 dubloom/container-back-propagation
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 158.789µs 160.287µs ± 0.321µs 160.258µs ± 0.140µs 160.405µs 160.677µs 160.996µs 162.948µs 1.68% 2.678 25.056 0.20% 0.023µs 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 [160.243µs; 160.332µs] or [-0.028%; +0.028%] None None None

Group 11

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 51c7f29 1773331729 dubloom/container-back-propagation
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 33.040µs 33.935µs ± 1.280µs 33.130µs ± 0.045µs 35.519µs 36.216µs 36.450µs 37.001µs 11.69% 0.974 -0.932 3.76% 0.091µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
redis/obfuscate_redis_string execution_time [33.757µs; 34.112µs] or [-0.523%; +0.523%] None None None

Group 12

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 51c7f29 1773331729 dubloom/container-back-propagation
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 10.607ms 10.638ms ± 0.014ms 10.636ms ± 0.008ms 10.646ms 10.662ms 10.676ms 10.703ms 0.63% 0.912 2.088 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 [10.636ms; 10.640ms] or [-0.019%; +0.019%] None None None

Group 13

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 51c7f29 1773331729 dubloom/container-back-propagation
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 17.684µs 25.436µs ± 9.477µs 18.084µs ± 0.250µs 33.560µs 42.067µs 50.049µs 73.154µs 304.53% 1.175 2.052 37.17% 0.670µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
two way interface execution_time [24.123µs; 26.750µs] or [-5.164%; +5.164%] None None None

Group 14

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 51c7f29 1773331729 dubloom/container-back-propagation
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 3.099ms 3.128ms ± 0.019ms 3.122ms ± 0.008ms 3.134ms 3.165ms 3.195ms 3.201ms 2.53% 1.658 3.050 0.59% 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 [3.125ms; 3.130ms] or [-0.082%; +0.082%] None None None

Group 15

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 51c7f29 1773331729 dubloom/container-back-propagation
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
benching deserializing traces from msgpack to their internal representation execution_time 48.343ms 48.568ms ± 0.962ms 48.410ms ± 0.035ms 48.468ms 48.630ms 54.378ms 57.082ms 17.91% 7.864 62.733 1.98% 0.068ms 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 [48.434ms; 48.701ms] or [-0.275%; +0.275%] None None None

Group 16

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 51c7f29 1773331729 dubloom/container-back-propagation
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
sdk_test_data/rules-based execution_time 144.500µs 146.600µs ± 1.998µs 146.240µs ± 0.590µs 146.895µs 148.800µs 153.614µs 165.445µs 13.13% 5.797 45.375 1.36% 0.141µs 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 [146.323µs; 146.877µs] or [-0.189%; +0.189%] None None None

Group 17

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 51c7f29 1773331729 dubloom/container-back-propagation
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 13.912ms 13.975ms ± 0.035ms 13.970ms ± 0.016ms 13.988ms 14.021ms 14.105ms 14.162ms 1.37% 2.272 8.697 0.25% 0.002ms 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
benching serializing traces from their internal representation to msgpack execution_time [13.970ms; 13.980ms] or [-0.034%; +0.034%] None None None

Group 18

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 51c7f29 1773331729 dubloom/container-back-propagation
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 714.918µs 716.475µs ± 0.829µs 716.399µs ± 0.451µs 716.872µs 717.789µs 719.396µs 720.818µs 0.62% 1.344 4.666 0.12% 0.059µs 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 [716.360µs; 716.590µs] or [-0.016%; +0.016%] None None None

Group 19

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 51c7f29 1773331729 dubloom/container-back-propagation
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 4.948µs 5.024µs ± 0.038µs 5.025µs ± 0.026µs 5.051µs 5.081µs 5.086µs 5.092µs 1.34% -0.039 -1.094 0.75% 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 [5.019µs; 5.030µs] or [-0.105%; +0.105%] None None None

Baseline

Omitted due to size.

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codecov-commenter commented Mar 12, 2026

Codecov Report

❌ Patch coverage is 85.13514% with 11 lines in your changes missing coverage. Please review.
✅ Project coverage is 71.34%. Comparing base (04394ec) to head (51c7f29).
⚠️ Report is 15 commits behind head on main.

Additional details and impacted files 
@@           Coverage Diff            @@
##             main    #1700    +/-   ##
========================================
  Coverage   71.33%   71.34%            
========================================
  Files         427      429     +2     
  Lines       62960    63859   +899     
========================================
+ Hits        44914    45561   +647     
- Misses      18046    18298   +252
Components Coverage Δ
libdd-crashtracker 62.40% <ø> (-0.55%) ⬇️
libdd-crashtracker-ffi 17.18% <ø> (+0.61%) ⬆️
libdd-alloc 98.77% <ø> (ø)
libdd-data-pipeline 88.20% <100.00%> (+0.18%) ⬆️
libdd-data-pipeline-ffi 76.94% <ø> (+1.22%) ⬆️
libdd-common 79.73% <ø> (-0.01%) ⬇️
libdd-common-ffi 73.40% <ø> (ø)
libdd-telemetry 62.48% <ø> (ø)
libdd-telemetry-ffi 16.75% <ø> (ø)
libdd-dogstatsd-client 82.64% <ø> (ø)
datadog-ipc 80.35% <ø> (ø)
libdd-profiling 81.59% <ø> (ø)
libdd-profiling-ffi 63.65% <ø> (ø)
datadog-sidecar 32.55% <0.00%> (-1.94%) ⬇️
datdog-sidecar-ffi 8.28% <0.00%> (-8.27%) ⬇️
spawn-worker 54.69% <ø> (ø)
libdd-tinybytes 93.16% <ø> (ø)
libdd-trace-normalization 81.71% <ø> (ø)
libdd-trace-obfuscation 91.80% <ø> (-2.90%) ⬇️
libdd-trace-protobuf 68.25% <ø> (ø)
libdd-trace-utils 89.08% <ø> (ø)
datadog-tracer-flare 88.95% <ø> (ø)
libdd-log 74.69% <ø> (ø)
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dd-octo-sts bot commented Mar 12, 2026

Artifact Size Benchmark Report

aarch64-alpine-linux-musl
Artifact Baseline Commit Change
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.so 8.70 MB 8.70 MB 0% (0 B) 👌
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.a 98.65 MB 98.66 MB +0% (+9.20 KB) 👌
aarch64-unknown-linux-gnu
Artifact Baseline Commit Change
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.a 114.30 MB 114.31 MB +.01% (+13.01 KB) 🔍
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.so 11.29 MB 11.29 MB +0% (+160 B) 👌
libdatadog-x64-windows
Artifact Baseline Commit Change
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.dll 27.17 MB 27.17 MB +.01% (+4.00 KB) 🔍
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.lib 76.26 KB 76.26 KB 0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.pdb 186.03 MB 186.06 MB +.01% (+32.00 KB) 🔍
/libdatadog-x64-windows/debug/static/datadog_profiling_ffi.lib 917.20 MB 917.26 MB +0% (+62.38 KB) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.dll 9.93 MB 9.94 MB +.02% (+2.50 KB) 🔍
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.lib 76.26 KB 76.26 KB 0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.pdb 24.76 MB 24.77 MB +.03% (+8.00 KB) 🔍
/libdatadog-x64-windows/release/static/datadog_profiling_ffi.lib 51.43 MB 51.44 MB +.01% (+8.36 KB) 🔍
libdatadog-x86-windows
Artifact Baseline Commit Change
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.dll 22.97 MB 22.97 MB +.01% (+4.00 KB) 🔍
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.lib 77.44 KB 77.44 KB 0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.pdb 190.24 MB 190.25 MB +0% (+8.00 KB) 👌
/libdatadog-x86-windows/debug/static/datadog_profiling_ffi.lib 900.85 MB 900.91 MB +0% (+61.29 KB) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.dll 7.53 MB 7.53 MB +.02% (+2.00 KB) 🔍
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.lib 77.44 KB 77.44 KB 0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.pdb 26.52 MB 26.52 MB 0% (0 B) 👌
/libdatadog-x86-windows/release/static/datadog_profiling_ffi.lib 47.07 MB 47.07 MB +.01% (+7.41 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% (+8.76 KB) 👌
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.so 10.23 MB 10.23 MB +.03% (+4.00 KB) 🔍
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% (+14.07 KB) 🔍
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.so 11.98 MB 11.98 MB +0% (+88 B) 👌

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