chore(profiling): use weaker mem ordering for COUNTER by yannham · Pull Request #1750 · DataDog/libdatadog

yannham · 2026-03-17T15:23:41Z

What does this PR do?

This PR replaces a bunch of sequentially consistent atomic accesses on id generator by weaker relaxed accesses.

Motivation

The motivation to use the weakest memory ordering applicable is two folds:

Performance: relaxed accesses compile to normal, non-atomic loads and stores on standard platforms (x86_64 and arm64 in particular). Whether this particular change has any performance impact is less obvious.
Readability: I think my main motivation is that I find it easier, at least as a reader, to reason about weaker orderings. For example, a relaxed access indicates that there's no other unsynchronized data that this atomic protect or interact with, which enables local reasoning (you don't have to care about what other threads might be doing). A sequentially consistent access is the converse: they lead to a global order which involves all other seqcst accesses to this atomic, which is a strong and far-reaching assumption.

Additional Notes

This atomic is a counter, which is the poster child for Relaxed ordering (you usually only need the atomicity). This counter doesn't protect or interact with unsynchronized memory, so there's no reason to use a stronger ordering.

How to test the change?

Should see no difference in behavior except maybe for performance.

codecov-commenter · 2026-03-17T15:38:34Z

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 71.04%. Comparing base (c664ed7) to head (4970478).
⚠️ Report is 25 commits behind head on main.

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #1750      +/-   ##
==========================================
+ Coverage   71.01%   71.04%   +0.02%     
==========================================
  Files         411      411              
  Lines       64794    64794              
==========================================
+ Hits        46014    46031      +17     
+ Misses      18780    18763      -17

Components	Coverage Δ
libdd-crashtracker	`65.27% <ø> (+0.04%)`	⬆️
libdd-crashtracker-ffi	`34.98% <ø> (ø)`
libdd-alloc	`98.77% <ø> (ø)`
libdd-data-pipeline	`87.61% <ø> (ø)`
libdd-data-pipeline-ffi	`73.45% <ø> (ø)`
libdd-common	`79.78% <ø> (ø)`
libdd-common-ffi	`73.87% <ø> (ø)`
libdd-telemetry	`62.48% <ø> (ø)`
libdd-telemetry-ffi	`16.75% <ø> (ø)`
libdd-dogstatsd-client	`82.64% <ø> (ø)`
datadog-ipc	`72.56% <ø> (ø)`
libdd-profiling	`81.61% <100.00%> (ø)`
libdd-profiling-ffi	`64.94% <ø> (ø)`
datadog-sidecar	`31.63% <ø> (ø)`
datdog-sidecar-ffi	`13.34% <ø> (ø)`
spawn-worker	`54.69% <ø> (ø)`
libdd-tinybytes	`93.16% <ø> (ø)`
libdd-trace-normalization	`81.71% <ø> (ø)`
libdd-trace-obfuscation	`87.37% <ø> (ø)`
libdd-trace-protobuf	`68.25% <ø> (ø)`
libdd-trace-utils	`88.95% <ø> (ø)`
datadog-tracer-flare	`86.88% <ø> (ø)`
libdd-log	`74.69% <ø> (ø)`

🚀 New features to boost your workflow:

❄️ Test Analytics: Detect flaky tests, report on failures, and find test suite problems.
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github-actions · 2026-03-17T15:40:49Z

Clippy Allow Annotation Report

Comparing clippy allow annotations between branches:

Base Branch: origin/main
PR Branch: origin/yannham/mem-ordering-counter

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	20	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`	55	55	No change (0%)
`libdd-common`	10	10	No change (0%)
`libdd-common-ffi`	12	12	No change (0%)
`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	8	No change (0%)
`libdd-trace-utils`	15	15	No change (0%)
Total	195	195	No change (0%)

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.

pr-commenter · 2026-03-17T15:41:35Z

Benchmarks

Comparison

Benchmark execution time: 2026-03-17 15:41:03

Comparing candidate commit 79bbfd1 in PR branch yannham/mem-ordering-counter with baseline commit e44af12 in branch main.

Found 0 performance improvements and 0 performance regressions! Performance is the same for 59 metrics, 2 unstable metrics.

Explanation

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

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

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

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

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

More details about the CI and significant changes

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

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

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

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

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

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

Candidate

Candidate benchmark details

Group 1

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`79bbfd1`	1773760949	yannham/mem-ordering-counter

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	3.893µs	3.913µs ± 0.003µs	3.912µs ± 0.002µs	3.915µs	3.919µs	3.921µs	3.922µs	0.25%	-0.411	6.420	0.08%	0.000µs	1	200
credit_card/is_card_number/	throughput	254962975.007op/s	255569969.144op/s ± 208891.983op/s	255606569.089op/s ± 108342.287op/s	255694127.412op/s	255808386.631op/s	255888132.599op/s	256851818.709op/s	0.49%	0.432	6.533	0.08%	14770.894op/s	1	200
credit_card/is_card_number/ 3782-8224-6310-005	execution_time	80.312µs	80.784µs ± 0.257µs	80.742µs ± 0.156µs	80.937µs	81.233µs	81.425µs	81.823µs	1.34%	0.857	1.130	0.32%	0.018µs	1	200
credit_card/is_card_number/ 3782-8224-6310-005	throughput	12221519.375op/s	12378816.989op/s ± 39295.002op/s	12385097.013op/s ± 23966.936op/s	12405621.918op/s	12435356.081op/s	12450342.362op/s	12451364.368op/s	0.54%	-0.835	1.059	0.32%	2778.576op/s	1	200
credit_card/is_card_number/ 378282246310005	execution_time	73.002µs	73.513µs ± 0.285µs	73.530µs ± 0.180µs	73.671µs	74.018µs	74.368µs	74.476µs	1.29%	0.560	0.422	0.39%	0.020µs	1	200
credit_card/is_card_number/ 378282246310005	throughput	13427097.917op/s	13603191.222op/s ± 52632.940op/s	13599893.244op/s ± 33308.874op/s	13646225.224op/s	13677124.780op/s	13689842.644op/s	13698165.161op/s	0.72%	-0.536	0.364	0.39%	3721.711op/s	1	200
credit_card/is_card_number/37828224631	execution_time	3.894µs	3.913µs ± 0.003µs	3.913µs ± 0.002µs	3.915µs	3.918µs	3.919µs	3.924µs	0.29%	-0.921	7.669	0.08%	0.000µs	1	200
credit_card/is_card_number/37828224631	throughput	254809771.103op/s	255532100.423op/s ± 195999.157op/s	255538959.471op/s ± 116490.627op/s	255642966.054op/s	255800019.095op/s	255876531.275op/s	256785535.171op/s	0.49%	0.941	7.787	0.08%	13859.233op/s	1	200
credit_card/is_card_number/378282246310005	execution_time	70.151µs	70.613µs ± 0.257µs	70.568µs ± 0.157µs	70.751µs	71.121µs	71.385µs	71.490µs	1.31%	0.854	0.883	0.36%	0.018µs	1	200
credit_card/is_card_number/378282246310005	throughput	13988011.683op/s	14161888.883op/s ± 51466.849op/s	14170777.024op/s ± 31385.508op/s	14196667.042op/s	14232310.142op/s	14253059.666op/s	14255027.256op/s	0.59%	-0.830	0.828	0.36%	3639.256op/s	1	200
credit_card/is_card_number/37828224631000521389798	execution_time	53.046µs	53.128µs ± 0.028µs	53.127µs ± 0.018µs	53.144µs	53.170µs	53.211µs	53.245µs	0.22%	0.606	1.373	0.05%	0.002µs	1	200
credit_card/is_card_number/37828224631000521389798	throughput	18781177.127op/s	18822321.200op/s ± 10084.115op/s	18822661.449op/s ± 6287.061op/s	18829218.614op/s	18837649.828op/s	18841739.626op/s	18851559.034op/s	0.15%	-0.601	1.362	0.05%	713.055op/s	1	200
credit_card/is_card_number/x371413321323331	execution_time	6.430µs	6.439µs ± 0.005µs	6.438µs ± 0.003µs	6.442µs	6.448µs	6.453µs	6.461µs	0.35%	0.912	1.192	0.08%	0.000µs	1	200
credit_card/is_card_number/x371413321323331	throughput	154784160.262op/s	155304267.778op/s ± 122738.696op/s	155328090.867op/s ± 69415.005op/s	155387471.885op/s	155474039.078op/s	155498804.103op/s	155528622.171op/s	0.13%	-0.906	1.173	0.08%	8678.936op/s	1	200
credit_card/is_card_number_no_luhn/	execution_time	3.892µs	3.913µs ± 0.003µs	3.912µs ± 0.001µs	3.914µs	3.917µs	3.921µs	3.935µs	0.57%	0.494	19.427	0.08%	0.000µs	1	200
credit_card/is_card_number_no_luhn/	throughput	254156467.511op/s	255580523.153op/s ± 207903.428op/s	255602952.215op/s ± 91729.589op/s	255678103.269op/s	255809820.331op/s	255863590.440op/s	256970009.911op/s	0.53%	-0.443	19.421	0.08%	14700.992op/s	1	200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	execution_time	64.883µs	65.153µs ± 0.127µs	65.135µs ± 0.075µs	65.212µs	65.406µs	65.541µs	65.567µs	0.66%	0.950	0.883	0.19%	0.009µs	1	200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	throughput	15251549.047op/s	15348527.364op/s ± 29759.782op/s	15352752.671op/s ± 17762.071op/s	15370012.722op/s	15385675.551op/s	15397463.778op/s	15412291.302op/s	0.39%	-0.939	0.855	0.19%	2104.334op/s	1	200
credit_card/is_card_number_no_luhn/ 378282246310005	execution_time	58.203µs	58.396µs ± 0.115µs	58.374µs ± 0.077µs	58.462µs	58.611µs	58.720µs	58.887µs	0.88%	1.008	1.233	0.20%	0.008µs	1	200
credit_card/is_card_number_no_luhn/ 378282246310005	throughput	16981763.955op/s	17124425.683op/s ± 33659.197op/s	17131044.974op/s ± 22518.614op/s	17150803.350op/s	17166323.715op/s	17173287.278op/s	17181265.548op/s	0.29%	-0.995	1.184	0.20%	2380.065op/s	1	200
credit_card/is_card_number_no_luhn/37828224631	execution_time	3.893µs	3.912µs ± 0.003µs	3.912µs ± 0.002µs	3.914µs	3.917µs	3.919µs	3.927µs	0.37%	-0.545	10.640	0.08%	0.000µs	1	200
credit_card/is_card_number_no_luhn/37828224631	throughput	254673218.690op/s	255595606.664op/s ± 193473.699op/s	255618302.270op/s ± 102986.337op/s	255704679.106op/s	255823370.897op/s	255865307.261op/s	256879852.489op/s	0.49%	0.573	10.767	0.08%	13680.656op/s	1	200
credit_card/is_card_number_no_luhn/378282246310005	execution_time	55.179µs	55.502µs ± 0.167µs	55.467µs ± 0.100µs	55.587µs	55.823µs	56.078µs	56.249µs	1.41%	1.195	2.455	0.30%	0.012µs	1	200
credit_card/is_card_number_no_luhn/378282246310005	throughput	17777969.854op/s	18017397.006op/s ± 53999.531op/s	18028687.540op/s ± 32525.739op/s	18053658.967op/s	18083845.627op/s	18111630.475op/s	18122800.295op/s	0.52%	-1.168	2.348	0.30%	3818.343op/s	1	200
credit_card/is_card_number_no_luhn/37828224631000521389798	execution_time	53.061µs	53.132µs ± 0.041µs	53.127µs ± 0.021µs	53.151µs	53.217µs	53.258µs	53.301µs	0.33%	1.245	2.101	0.08%	0.003µs	1	200
credit_card/is_card_number_no_luhn/37828224631000521389798	throughput	18761413.193op/s	18820965.722op/s ± 14596.622op/s	18822802.979op/s ± 7567.020op/s	18830048.723op/s	18840198.103op/s	18845625.414op/s	18846329.423op/s	0.12%	-1.239	2.082	0.08%	1032.137op/s	1	200
credit_card/is_card_number_no_luhn/x371413321323331	execution_time	6.430µs	6.440µs ± 0.006µs	6.440µs ± 0.004µs	6.443µs	6.449µs	6.452µs	6.473µs	0.52%	1.264	4.557	0.09%	0.000µs	1	200
credit_card/is_card_number_no_luhn/x371413321323331	throughput	154480270.812op/s	155286031.791op/s ± 139292.760op/s	155289992.573op/s ± 96853.931op/s	155393718.209op/s	155476804.768op/s	155498280.829op/s	155511657.370op/s	0.14%	-1.251	4.469	0.09%	9849.486op/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 [-0.011%; +0.011%]	None	None	None
credit_card/is_card_number/	throughput	[255541018.724op/s; 255598919.563op/s] or [-0.011%; +0.011%]	None	None	None
credit_card/is_card_number/ 3782-8224-6310-005	execution_time	[80.748µs; 80.820µs] or [-0.044%; +0.044%]	None	None	None
credit_card/is_card_number/ 3782-8224-6310-005	throughput	[12373371.080op/s; 12384262.899op/s] or [-0.044%; +0.044%]	None	None	None
credit_card/is_card_number/ 378282246310005	execution_time	[73.474µs; 73.553µs] or [-0.054%; +0.054%]	None	None	None
credit_card/is_card_number/ 378282246310005	throughput	[13595896.802op/s; 13610485.641op/s] or [-0.054%; +0.054%]	None	None	None
credit_card/is_card_number/37828224631	execution_time	[3.913µs; 3.914µs] or [-0.011%; +0.011%]	None	None	None
credit_card/is_card_number/37828224631	throughput	[255504936.825op/s; 255559264.021op/s] or [-0.011%; +0.011%]	None	None	None
credit_card/is_card_number/378282246310005	execution_time	[70.577µs; 70.649µs] or [-0.051%; +0.051%]	None	None	None
credit_card/is_card_number/378282246310005	throughput	[14154756.073op/s; 14169021.693op/s] or [-0.050%; +0.050%]	None	None	None
credit_card/is_card_number/37828224631000521389798	execution_time	[53.124µs; 53.132µs] or [-0.007%; +0.007%]	None	None	None
credit_card/is_card_number/37828224631000521389798	throughput	[18820923.639op/s; 18823718.762op/s] or [-0.007%; +0.007%]	None	None	None
credit_card/is_card_number/x371413321323331	execution_time	[6.438µs; 6.440µs] or [-0.011%; +0.011%]	None	None	None
credit_card/is_card_number/x371413321323331	throughput	[155287257.375op/s; 155321278.181op/s] or [-0.011%; +0.011%]	None	None	None
credit_card/is_card_number_no_luhn/	execution_time	[3.912µs; 3.913µs] or [-0.011%; +0.011%]	None	None	None
credit_card/is_card_number_no_luhn/	throughput	[255551709.738op/s; 255609336.569op/s] or [-0.011%; +0.011%]	None	None	None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	execution_time	[65.136µs; 65.171µs] or [-0.027%; +0.027%]	None	None	None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	throughput	[15344402.945op/s; 15352651.784op/s] or [-0.027%; +0.027%]	None	None	None
credit_card/is_card_number_no_luhn/ 378282246310005	execution_time	[58.380µs; 58.412µs] or [-0.027%; +0.027%]	None	None	None
credit_card/is_card_number_no_luhn/ 378282246310005	throughput	[17119760.842op/s; 17129090.524op/s] or [-0.027%; +0.027%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631	execution_time	[3.912µs; 3.913µs] or [-0.010%; +0.010%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631	throughput	[255568793.070op/s; 255622420.258op/s] or [-0.010%; +0.010%]	None	None	None
credit_card/is_card_number_no_luhn/378282246310005	execution_time	[55.479µs; 55.526µs] or [-0.042%; +0.042%]	None	None	None
credit_card/is_card_number_no_luhn/378282246310005	throughput	[18009913.190op/s; 18024880.822op/s] or [-0.042%; +0.042%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631000521389798	execution_time	[53.127µs; 53.138µs] or [-0.011%; +0.011%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631000521389798	throughput	[18818942.771op/s; 18822988.673op/s] or [-0.011%; +0.011%]	None	None	None
credit_card/is_card_number_no_luhn/x371413321323331	execution_time	[6.439µs; 6.441µs] or [-0.012%; +0.012%]	None	None	None
credit_card/is_card_number_no_luhn/x371413321323331	throughput	[155266727.154op/s; 155305336.427op/s] or [-0.012%; +0.012%]	None	None	None

Group 2

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`79bbfd1`	1773760949	yannham/mem-ordering-counter

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	4.191ms	4.194ms ± 0.002ms	4.194ms ± 0.001ms	4.195ms	4.199ms	4.201ms	4.204ms	0.23%	1.435	2.770	0.05%	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	[4.194ms; 4.194ms] or [-0.007%; +0.007%]	None	None	None

Group 3

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`79bbfd1`	1773760949	yannham/mem-ordering-counter

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	86.982µs	87.225µs ± 0.133µs	87.210µs ± 0.046µs	87.254µs	87.387µs	87.595µs	88.371µs	1.33%	4.876	36.074	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	[87.206µs; 87.243µs] or [-0.021%; +0.021%]	None	None	None

Group 4

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`79bbfd1`	1773760949	yannham/mem-ordering-counter

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	741.307µs	744.052µs ± 2.014µs	743.524µs ± 1.423µs	745.557µs	747.499µs	748.796µs	749.166µs	0.76%	0.593	-0.857	0.27%	0.142µs	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	[743.773µs; 744.331µs] or [-0.038%; +0.038%]	None	None	None

Group 5

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`79bbfd1`	1773760949	yannham/mem-ordering-counter

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	495.293µs	496.428µs ± 0.720µs	496.367µs ± 0.387µs	496.755µs	497.328µs	497.919µs	502.385µs	1.21%	3.688	25.717	0.14%	0.051µs	1	200
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000...	throughput	1990503.749op/s	2014396.177op/s ± 2907.988op/s	2014637.348op/s ± 1568.505op/s	2016167.140op/s	2017625.902op/s	2018268.625op/s	2019007.837op/s	0.22%	-3.628	25.084	0.14%	205.626op/s	1	200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	execution_time	369.941µs	370.564µs ± 0.273µs	370.554µs ± 0.175µs	370.733µs	371.058µs	371.251µs	371.447µs	0.24%	0.340	0.130	0.07%	0.019µs	1	200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	throughput	2692176.640op/s	2698590.143op/s ± 1988.899op/s	2698662.795op/s ± 1275.941op/s	2699790.910op/s	2701467.315op/s	2703012.171op/s	2703135.014op/s	0.17%	-0.335	0.125	0.07%	140.636op/s	1	200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	execution_time	168.745µs	169.067µs ± 0.120µs	169.071µs ± 0.081µs	169.154µs	169.265µs	169.325µs	169.434µs	0.21%	0.023	-0.227	0.07%	0.008µs	1	200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	throughput	5902010.431op/s	5914804.901op/s ± 4197.168op/s	5914681.002op/s ± 2821.581op/s	5917465.530op/s	5921501.030op/s	5924467.346op/s	5926094.980op/s	0.19%	-0.019	-0.228	0.07%	296.785op/s	1	200
normalization/normalize_service/normalize_service/[empty string]	execution_time	36.801µs	36.991µs ± 0.117µs	37.010µs ± 0.106µs	37.088µs	37.158µs	37.192µs	37.269µs	0.70%	-0.037	-1.291	0.32%	0.008µs	1	200
normalization/normalize_service/normalize_service/[empty string]	throughput	26832076.510op/s	27033961.837op/s ± 85490.579op/s	27019741.887op/s ± 77402.929op/s	27118584.618op/s	27155917.653op/s	27172011.189op/s	27172971.257op/s	0.57%	0.043	-1.295	0.32%	6045.097op/s	1	200
normalization/normalize_service/normalize_service/test_ASCII	execution_time	46.184µs	46.312µs ± 0.247µs	46.279µs ± 0.037µs	46.317µs	46.372µs	47.745µs	48.492µs	4.78%	7.845	63.450	0.53%	0.017µs	1	200
normalization/normalize_service/normalize_service/test_ASCII	throughput	20622168.507op/s	21593483.561op/s ± 110692.170op/s	21608140.980op/s ± 17124.039op/s	21624046.037op/s	21638851.747op/s	21647467.899op/s	21652351.786op/s	0.20%	-7.783	62.597	0.51%	7827.118op/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	[496.328µs; 496.528µs] or [-0.020%; +0.020%]	None	None	None
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000...	throughput	[2013993.158op/s; 2014799.196op/s] or [-0.020%; +0.020%]	None	None	None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	execution_time	[370.526µs; 370.602µs] or [-0.010%; +0.010%]	None	None	None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	throughput	[2698314.500op/s; 2698865.785op/s] or [-0.010%; +0.010%]	None	None	None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	execution_time	[169.051µs; 169.084µs] or [-0.010%; +0.010%]	None	None	None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	throughput	[5914223.213op/s; 5915386.588op/s] or [-0.010%; +0.010%]	None	None	None
normalization/normalize_service/normalize_service/[empty string]	execution_time	[36.975µs; 37.007µs] or [-0.044%; +0.044%]	None	None	None
normalization/normalize_service/normalize_service/[empty string]	throughput	[27022113.665op/s; 27045810.009op/s] or [-0.044%; +0.044%]	None	None	None
normalization/normalize_service/normalize_service/test_ASCII	execution_time	[46.277µs; 46.346µs] or [-0.074%; +0.074%]	None	None	None
normalization/normalize_service/normalize_service/test_ASCII	throughput	[21578142.691op/s; 21608824.431op/s] or [-0.071%; +0.071%]	None	None	None

Group 6

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`79bbfd1`	1773760949	yannham/mem-ordering-counter

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	49.561ms	50.094ms ± 1.117ms	49.847ms ± 0.141ms	50.191ms	50.568ms	58.493ms	58.910ms	18.18%	7.056	51.852	2.22%	0.079ms	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	[49.939ms; 50.249ms] or [-0.309%; +0.309%]	None	None	None

Group 7

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`79bbfd1`	1773760949	yannham/mem-ordering-counter

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	13.248ms	13.279ms ± 0.016ms	13.278ms ± 0.010ms	13.290ms	13.306ms	13.322ms	13.336ms	0.44%	0.625	0.463	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	[13.277ms; 13.282ms] or [-0.017%; +0.017%]	None	None	None

Group 8

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`79bbfd1`	1773760949	yannham/mem-ordering-counter

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	190.389ns	192.929ns ± 2.045ns	192.696ns ± 1.373ns	194.012ns	196.389ns	200.108ns	202.389ns	5.03%	1.283	2.760	1.06%	0.145ns	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	[192.646ns; 193.213ns] or [-0.147%; +0.147%]	None	None	None

Group 9

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`79bbfd1`	1773760949	yannham/mem-ordering-counter

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/2598	execution_time	3.448ms	3.484ms ± 0.030ms	3.476ms ± 0.013ms	3.496ms	3.533ms	3.570ms	3.721ms	7.05%	3.214	18.888	0.86%	0.002ms	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
receiver_entry_point/report/2598	execution_time	[3.480ms; 3.488ms] or [-0.120%; +0.120%]	None	None	None

Group 10

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`79bbfd1`	1773760949	yannham/mem-ordering-counter

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	1.233µs	3.199µs ± 1.426µs	2.991µs ± 0.026µs	3.013µs	3.677µs	13.906µs	14.882µs	397.58%	7.381	55.531	44.46%	0.101µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
write only interface	execution_time	[3.001µs; 3.396µs] or [-6.178%; +6.178%]	None	None	None

Group 11

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`79bbfd1`	1773760949	yannham/mem-ordering-counter

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	236.618ns	247.395ns ± 13.298ns	242.286ns ± 3.720ns	247.872ns	282.201ns	294.371ns	295.850ns	22.11%	2.155	3.937	5.36%	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	[245.552ns; 249.238ns] or [-0.745%; +0.745%]	None	None	None

Group 12

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`79bbfd1`	1773760949	yannham/mem-ordering-counter

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	144.552µs	146.273µs ± 1.676µs	145.962µs ± 0.528µs	146.552µs	147.979µs	152.879µs	161.062µs	10.35%	5.200	37.308	1.14%	0.119µs	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	[146.041µs; 146.505µs] or [-0.159%; +0.159%]	None	None	None

Group 13

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`79bbfd1`	1773760949	yannham/mem-ordering-counter

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
benching serializing traces from their internal representation to msgpack	execution_time	14.212ms	14.255ms ± 0.035ms	14.248ms ± 0.010ms	14.261ms	14.288ms	14.374ms	14.569ms	2.26%	4.830	35.173	0.24%	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	[14.250ms; 14.259ms] or [-0.034%; +0.034%]	None	None	None

Group 14

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`79bbfd1`	1773760949	yannham/mem-ordering-counter

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	5.071µs	5.132µs ± 0.038µs	5.125µs ± 0.030µs	5.165µs	5.194µs	5.205µs	5.226µs	1.97%	0.433	-1.201	0.74%	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	[5.127µs; 5.137µs] or [-0.104%; +0.104%]	None	None	None

Group 15

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`79bbfd1`	1773760949	yannham/mem-ordering-counter

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
redis/obfuscate_redis_string	execution_time	34.006µs	34.653µs ± 1.116µs	34.138µs ± 0.068µs	34.264µs	37.009µs	37.033µs	39.062µs	14.42%	1.782	1.532	3.21%	0.079µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
redis/obfuscate_redis_string	execution_time	[34.499µs; 34.808µs] or [-0.446%; +0.446%]	None	None	None

Group 16

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`79bbfd1`	1773760949	yannham/mem-ordering-counter

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_timestamped_x1000	execution_time	4.227ms	4.232ms ± 0.008ms	4.232ms ± 0.001ms	4.233ms	4.235ms	4.243ms	4.338ms	2.51%	11.742	151.379	0.19%	0.001ms	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
profile_add_sample_timestamped_x1000	execution_time	[4.231ms; 4.233ms] or [-0.026%; +0.026%]	None	None	None

Group 17

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`79bbfd1`	1773760949	yannham/mem-ordering-counter

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	185.894µs	186.285µs ± 0.204µs	186.274µs ± 0.158µs	186.434µs	186.636µs	186.702µs	186.895µs	0.33%	0.286	-0.709	0.11%	0.014µs	1	200
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo...	throughput	5350591.488op/s	5368117.541op/s ± 5866.459op/s	5368445.112op/s ± 4536.067op/s	5372745.466op/s	5376244.293op/s	5378201.779op/s	5379414.835op/s	0.20%	-0.282	-0.714	0.11%	414.821op/s	1	200
normalization/normalize_name/normalize_name/bad-name	execution_time	17.923µs	18.017µs ± 0.059µs	18.001µs ± 0.028µs	18.041µs	18.149µs	18.187µs	18.240µs	1.33%	1.262	1.492	0.33%	0.004µs	1	200
normalization/normalize_name/normalize_name/bad-name	throughput	54824359.338op/s	55505135.224op/s ± 180147.551op/s	55552845.344op/s ± 86074.670op/s	55618879.852op/s	55723099.468op/s	55754693.793op/s	55793472.258op/s	0.43%	-1.243	1.432	0.32%	12738.356op/s	1	200
normalization/normalize_name/normalize_name/good	execution_time	10.230µs	10.323µs ± 0.034µs	10.323µs ± 0.023µs	10.345µs	10.381µs	10.404µs	10.411µs	0.85%	-0.007	0.039	0.33%	0.002µs	1	200
normalization/normalize_name/normalize_name/good	throughput	96056236.560op/s	96876182.635op/s ± 322070.160op/s	96868647.584op/s ± 213445.127op/s	97079096.339op/s	97404627.864op/s	97697423.471op/s	97755475.047op/s	0.92%	0.027	0.042	0.33%	22773.799op/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	[186.257µs; 186.313µs] or [-0.015%; +0.015%]	None	None	None
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo...	throughput	[5367304.507op/s; 5368930.576op/s] or [-0.015%; +0.015%]	None	None	None
normalization/normalize_name/normalize_name/bad-name	execution_time	[18.008µs; 18.025µs] or [-0.045%; +0.045%]	None	None	None
normalization/normalize_name/normalize_name/bad-name	throughput	[55480168.506op/s; 55530101.942op/s] or [-0.045%; +0.045%]	None	None	None
normalization/normalize_name/normalize_name/good	execution_time	[10.318µs; 10.327µs] or [-0.046%; +0.046%]	None	None	None
normalization/normalize_name/normalize_name/good	throughput	[96831546.808op/s; 96920818.462op/s] or [-0.046%; +0.046%]	None	None	None

Group 18

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`79bbfd1`	1773760949	yannham/mem-ordering-counter

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	2.419µs	2.479µs ± 0.015µs	2.481µs ± 0.006µs	2.488µs	2.494µs	2.499µs	2.511µs	1.21%	-2.131	5.573	0.61%	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	[2.477µs; 2.481µs] or [-0.084%; +0.084%]	None	None	None

Group 19

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`79bbfd1`	1773760949	yannham/mem-ordering-counter

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
benching string interning on wordpress profile	execution_time	160.382µs	161.159µs ± 0.596µs	161.110µs ± 0.145µs	161.234µs	161.583µs	162.241µs	168.650µs	4.68%	10.115	123.737	0.37%	0.042µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
benching string interning on wordpress profile	execution_time	[161.076µs; 161.241µs] or [-0.051%; +0.051%]	None	None	None

Group 20

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`79bbfd1`	1773760949	yannham/mem-ordering-counter

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	17.721µs	24.934µs ± 9.218µs	17.947µs ± 0.118µs	33.248µs	42.552µs	43.595µs	66.546µs	270.79%	1.085	0.903	36.88%	0.652µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
two way interface	execution_time	[23.656µs; 26.211µs] or [-5.124%; +5.124%]	None	None	None

Baseline

Omitted due to size.

github-actions · 2026-03-17T15:55:37Z

📚 Documentation Check Results

⚠️ 647 documentation warning(s) found

📦 `libdd-profiling` - 647 warning(s)

Updated: 2026-03-25 09:31:19 UTC | Commit: 8b7c3c8 | missing-docs job results

github-actions · 2026-03-17T15:58:58Z

🔒 Cargo Deny Results

⚠️ 3 issue(s) found, showing only errors (advisories, bans, sources)

📦 `libdd-profiling` - 3 error(s)

Show output

error[vulnerability]: AWS-LC X.509 Name Constraints Bypass via Wildcard/Unicode CN
   ┌─ /home/runner/work/libdatadog/libdatadog/Cargo.lock:13:1
   │
13 │ aws-lc-sys 0.38.0 registry+https://github.com/rust-lang/crates.io-index
   │ ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ security vulnerability detected
   │
   ├ ID: RUSTSEC-2026-0044
   ├ Advisory: https://rustsec.org/advisories/RUSTSEC-2026-0044
   ├ A logic error in CN (Common Name) validation allows certificates with
     wildcard or raw UTF-8 Unicode CN values to bypass name constraints
     enforcement. The `cn2dnsid` function does not recognize these CN patterns
     as valid DNS identifiers, causing `NAME_CONSTRAINTS_check_CN` to skip
     validation. However, `X509_check_host` accepts these CN values when no
     dNSName SAN is present, allowing certificates to bypass name constraints
     while still being used for hostname verification.
     
     Customers of AWS services do not need to take action. Applications using
     `aws-lc-sys` should upgrade to the most recent release of `aws-lc-sys`.
     
     ## Workarounds
     
     Applications that set `X509_CHECK_FLAG_NEVER_CHECK_SUBJECT` to disable CN
     fallback are not affected. Applications that only encounter certificates
     with dNSName SANs (standard for public WebPKI) are also not affected.
     
     Otherwise, there is no workaround and applications using `aws-lc-sys` should
     upgrade to the most recent releases of `aws-lc-sys`.
   ├ Solution: Upgrade to >=0.39.0 (try `cargo update -p aws-lc-sys`)
   ├ aws-lc-sys v0.38.0
     └── aws-lc-rs v1.16.1
         ├── rustls v0.23.37
         │   ├── hyper-rustls v0.27.7
         │   │   ├── libdd-common v3.0.1
         │   │   │   └── libdd-profiling v1.0.0
         │   │   │       └── (dev) libdd-profiling v1.0.0 (*)
         │   │   └── reqwest v0.13.2
         │   │       ├── libdd-common v3.0.1 (*)
         │   │       └── libdd-profiling v1.0.0 (*)
         │   ├── libdd-common v3.0.1 (*)
         │   ├── libdd-profiling v1.0.0 (*)
         │   ├── reqwest v0.13.2 (*)
         │   ├── rustls-platform-verifier v0.6.2
         │   │   ├── libdd-profiling v1.0.0 (*)
         │   │   └── reqwest v0.13.2 (*)
         │   └── tokio-rustls v0.26.0
         │       ├── hyper-rustls v0.27.7 (*)
         │       ├── libdd-common v3.0.1 (*)
         │       └── reqwest v0.13.2 (*)
         └── rustls-webpki v0.103.9
             ├── rustls v0.23.37 (*)
             └── rustls-platform-verifier v0.6.2 (*)

error[vulnerability]: CRL Distribution Point Scope Check Logic Error in AWS-LC
   ┌─ /home/runner/work/libdatadog/libdatadog/Cargo.lock:13:1
   │
13 │ aws-lc-sys 0.38.0 registry+https://github.com/rust-lang/crates.io-index
   │ ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ security vulnerability detected
   │
   ├ ID: RUSTSEC-2026-0048
   ├ Advisory: https://rustsec.org/advisories/RUSTSEC-2026-0048
   ├ A logic error in CRL distribution point matching in AWS-LC allows a revoked
     certificate to bypass revocation checks during certificate validation, when
     the application enables CRL checking and uses partitioned CRLs with Issuing
     Distribution Point (IDP) extensions.
     
     Customers of AWS services do not need to take action. `aws-lc-sys` contains
     code from AWS-LC. Applications using `aws-lc-sys` should upgrade to the most
     recent release of `aws-lc-sys`.
     
     ## Workarounds
     
     Applications can workaround this issue if they do not enable CRL checking
     (`X509_V_FLAG_CRL_CHECK`). Applications using complete (non-partitioned)
     CRLs without IDP extensions are also not affected.
     
     Otherwise, there is no workaround and applications using `aws-lc-sys` should
     upgrade to the most recent releases of `aws-lc-sys`.
   ├ Announcement: https://aws.amazon.com/security/security-bulletins/2026-010-AWS
   ├ Solution: Upgrade to >=0.39.0 (try `cargo update -p aws-lc-sys`)
   ├ aws-lc-sys v0.38.0
     └── aws-lc-rs v1.16.1
         ├── rustls v0.23.37
         │   ├── hyper-rustls v0.27.7
         │   │   ├── libdd-common v3.0.1
         │   │   │   └── libdd-profiling v1.0.0
         │   │   │       └── (dev) libdd-profiling v1.0.0 (*)
         │   │   └── reqwest v0.13.2
         │   │       ├── libdd-common v3.0.1 (*)
         │   │       └── libdd-profiling v1.0.0 (*)
         │   ├── libdd-common v3.0.1 (*)
         │   ├── libdd-profiling v1.0.0 (*)
         │   ├── reqwest v0.13.2 (*)
         │   ├── rustls-platform-verifier v0.6.2
         │   │   ├── libdd-profiling v1.0.0 (*)
         │   │   └── reqwest v0.13.2 (*)
         │   └── tokio-rustls v0.26.0
         │       ├── hyper-rustls v0.27.7 (*)
         │       ├── libdd-common v3.0.1 (*)
         │       └── reqwest v0.13.2 (*)
         └── rustls-webpki v0.103.9
             ├── rustls v0.23.37 (*)
             └── rustls-platform-verifier v0.6.2 (*)

error[vulnerability]: CRLs not considered authoritative by Distribution Point due to faulty matching logic
    ┌─ /home/runner/work/libdatadog/libdatadog/Cargo.lock:193:1
    │
193 │ rustls-webpki 0.103.9 registry+https://github.com/rust-lang/crates.io-index
    │ ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ security vulnerability detected
    │
    ├ ID: RUSTSEC-2026-0049
    ├ Advisory: https://rustsec.org/advisories/RUSTSEC-2026-0049
    ├ If a certificate had more than one `distributionPoint`, then only the first `distributionPoint` would be considered against each CRL's `IssuingDistributionPoint` `distributionPoint`, and then the certificate's subsequent `distributionPoint`s would be ignored.
      
      The impact was that correctly provided CRLs would not be consulted to check revocation. With `UnknownStatusPolicy::Deny` (the default) this would lead to incorrect but safe `Error::UnknownRevocationStatus`. With `UnknownStatusPolicy::Allow` this would lead to inappropriate acceptance of revoked certificates.
      
      This vulnerability is thought to be of limited impact. This is because both the certificate and CRL are signed -- an attacker would need to compromise a trusted issuing authority to trigger this bug.  An attacker with such capabilities could likely bypass revocation checking through other more impactful means (such as publishing a valid, empty CRL.)
      
      More likely, this bug would be latent in normal use, and an attacker could leverage faulty revocation checking to continue using a revoked credential.
      
      This vulnerability is identified as [GHSA-pwjx-qhcg-rvj4](https://github.com/rustls/webpki/security/advisories/GHSA-pwjx-qhcg-rvj4). Thank you to @1seal for the report.
    ├ Solution: Upgrade to >=0.103.10 (try `cargo update -p rustls-webpki`)
    ├ rustls-webpki v0.103.9
      ├── rustls v0.23.37
      │   ├── hyper-rustls v0.27.7
      │   │   ├── libdd-common v3.0.1
      │   │   │   └── libdd-profiling v1.0.0
      │   │   │       └── (dev) libdd-profiling v1.0.0 (*)
      │   │   └── reqwest v0.13.2
      │   │       ├── libdd-common v3.0.1 (*)
      │   │       └── libdd-profiling v1.0.0 (*)
      │   ├── libdd-common v3.0.1 (*)
      │   ├── libdd-profiling v1.0.0 (*)
      │   ├── reqwest v0.13.2 (*)
      │   ├── rustls-platform-verifier v0.6.2
      │   │   ├── libdd-profiling v1.0.0 (*)
      │   │   └── reqwest v0.13.2 (*)
      │   └── tokio-rustls v0.26.0
      │       ├── hyper-rustls v0.27.7 (*)
      │       ├── libdd-common v3.0.1 (*)
      │       └── reqwest v0.13.2 (*)
      └── rustls-platform-verifier v0.6.2 (*)

advisories FAILED, bans ok, sources ok

Updated: 2026-03-25 09:34:04 UTC | Commit: 8b7c3c8 | dependency-check job results

dd-octo-sts · 2026-03-17T16:00:40Z

Artifact Size Benchmark Report

aarch64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.a	101.43 MB	101.43 MB	0% (0 B) 👌
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.so	8.70 MB	8.70 MB	0% (0 B) 👌

aarch64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.a	118.21 MB	118.21 MB	0% (0 B) 👌
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.so	11.29 MB	11.29 MB	0% (0 B) 👌

libdatadog-x64-windows

Artifact	Baseline	Commit	Change
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.dll	27.26 MB	27.26 MB	0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.lib	80.34 KB	80.34 KB	0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.pdb	186.51 MB	186.49 MB	-0% (-16.00 KB) 👌
/libdatadog-x64-windows/debug/static/datadog_profiling_ffi.lib	921.90 MB	921.90 MB	0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.dll	8.99 MB	8.99 MB	0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.lib	80.34 KB	80.34 KB	0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.pdb	26.83 MB	26.83 MB	0% (0 B) 👌
/libdatadog-x64-windows/release/static/datadog_profiling_ffi.lib	60.99 MB	60.99 MB	0% (0 B) 👌

libdatadog-x86-windows

Artifact	Baseline	Commit	Change
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.dll	23.07 MB	23.07 MB	0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.lib	81.59 KB	81.59 KB	0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.pdb	190.76 MB	190.75 MB	-0% (-8.00 KB) 👌
/libdatadog-x86-windows/debug/static/datadog_profiling_ffi.lib	905.43 MB	905.43 MB	0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.dll	6.86 MB	6.86 MB	0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.lib	81.59 KB	81.59 KB	0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.pdb	28.94 MB	28.94 MB	0% (0 B) 👌
/libdatadog-x86-windows/release/static/datadog_profiling_ffi.lib	57.39 MB	57.39 MB	0% (0 B) 👌

x86_64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.a	88.29 MB	88.29 MB	0% (0 B) 👌
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.so	10.28 MB	10.28 MB	0% (0 B) 👌

x86_64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.a	110.96 MB	110.96 MB	0% (0 B) 👌
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.so	12.02 MB	12.02 MB	0% (0 B) 👌

morrisonlevi

Approved, though this API is hardly used and long-term I kind of hope it goes away. If you are interested in using this API, please reach out to me to synchronize for long-term vision.

yannham · 2026-03-24T15:40:14Z

/merge

yannham · 2026-03-24T15:42:06Z

@morrisonlevi Thanks for the heads-up. It was just a quick clean as I was going through the repo, but I don't plan to use this API.

gh-worker-devflow-routing-ef8351 · 2026-03-24T15:42:47Z

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gyuheon0h · 2026-03-24T17:49:00Z

FYI, github actions just got re-enabled, so youll probably have to re-push to retrigger CI for MQ

datadog-prod-us1-5 · 2026-03-25T09:44:51Z

✅ Tests

🎉 All green!

❄️ No new flaky tests detected
🧪 All tests passed

🎯 Code Coverage (details)
• Patch Coverage: 100.00%
• Overall Coverage: 71.04% (+0.03%)

_{This comment will be updated automatically if new data arrives.

🔗 Commit SHA: 4970478 | Docs | Datadog PR Page | Was this helpful? React with 👍/👎 or give us feedback!}

yannham · 2026-03-25T10:51:04Z

/merge

gh-worker-devflow-routing-ef8351 · 2026-03-25T10:51:08Z

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2026-03-25 10:51:08 UTC ℹ️ Start processing command /merge

2026-03-25 10:51:12 UTC ℹ️ MergeQueue: pull request added to the queue

The expected merge time in main is approximately 45m (p90).

2026-03-25 11:27:24 UTC ℹ️ MergeQueue: This merge request was merged

yannham requested a review from a team as a code owner March 17, 2026 15:23

bantonsson approved these changes Mar 20, 2026

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morrisonlevi approved these changes Mar 24, 2026

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gh-worker-dd-devflow-36fce6 bot added the mergequeue-status: waiting label Mar 24, 2026

gh-worker-dd-devflow-36fce6 bot added mergequeue-status: removed and removed mergequeue-status: waiting labels Mar 24, 2026

chore(profiling): use weaker mem ordering for COUNTER

4970478

yannham force-pushed the yannham/mem-ordering-counter branch from f905bed to 4970478 Compare March 25, 2026 09:29

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yannham commented Mar 17, 2026

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📦 libdd-profiling - 647 warning(s)

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🔒 Cargo Deny Results

📦 libdd-profiling - 3 error(s)

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📦 `libdd-profiling` - 647 warning(s)

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📦 `libdd-profiling` - 3 error(s)

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