feat(trace-export): map DD span resource to OTLP resource.name attribute by rachelyangdog · Pull Request #1811 · DataDog/libdatadog

rachelyangdog · 2026-03-27T15:28:45Z

What does this PR do?

Adds resource.name as a per-span OTLP attribute when mapping Datadog spans to OTLP. The Datadog span resource field now maps to two places:

OtlpSpan.name (existing — the OTLP span name)
span.attributes["resource.name"] (new)
This follows the same conditional pattern as operation.name and span.type: the attribute is only emitted when the field is non-empty.

Motivation

Spec update to the OTLP trace export RFC: the Datadog resource field should be preserved as a resource.name attribute so downstream consumers can reconstruct the original Datadog resource name independently of the OTLP span name.

Additional Notes

This builds on top of feat(otel): add support for OTLP trace export (#1641). The dropped_attributes_count accounting in map_attributes is updated to include the new resource.name slot.

How to test the change?

Describe here in detail how the change can be validated.

github-actions · 2026-03-27T15:32:03Z

Clippy Allow Annotation Report

Comparing clippy allow annotations between branches:

Base Branch: origin/main
PR Branch: origin/rachel.yang/otlp-trace-resource

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.

zacharycmontoya

LGTM from the spec side. Thanks for the implementing the new mapping!

codecov-commenter · 2026-03-27T15:42:20Z

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 71.24%. Comparing base (a29b90b) to head (9845517).
⚠️ Report is 3 commits behind head on main.

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #1811      +/-   ##
==========================================
+ Coverage   71.16%   71.24%   +0.07%     
==========================================
  Files         414      414              
  Lines       65739    65963     +224     
==========================================
+ Hits        46786    46995     +209     
- Misses      18953    18968      +15

Components	Coverage Δ
libdd-crashtracker	`65.24% <ø> (-0.03%)`	⬇️
libdd-crashtracker-ffi	`34.47% <ø> (-0.77%)`	⬇️
libdd-alloc	`98.77% <ø> (ø)`
libdd-data-pipeline	`86.53% <ø> (-1.03%)`	⬇️
libdd-data-pipeline-ffi	`69.94% <ø> (-5.83%)`	⬇️
libdd-common	`79.79% <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	`72.48% <ø> (-0.08%)`	⬇️
libdd-profiling	`81.61% <ø> (-0.02%)`	⬇️
libdd-profiling-ffi	`64.94% <ø> (ø)`
datadog-sidecar	`31.62% <ø> (+0.83%)`	⬆️
datdog-sidecar-ffi	`13.26% <ø> (+3.89%)`	⬆️
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> (-0.13%)`	⬇️
libdd-trace-protobuf	`68.25% <ø> (ø)`
libdd-trace-utils	`88.72% <100.00%> (+0.08%)`	⬆️
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.
📦 JS Bundle Analysis: Save yourself from yourself by tracking and limiting bundle sizes in JS merges.

datadog-datadog-prod-us1 · 2026-03-27T15:42:28Z

✅ Tests

🎉 All green!

❄️ No new flaky tests detected
🧪 All tests passed

🎯 Code Coverage (details)
• Patch Coverage: 100.00%
• Overall Coverage: 71.24% (+0.08%)

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

🔗 Commit SHA: 9845517 | Docs | Datadog PR Page | Was this helpful? React with 👍/👎 or give us feedback!}

pr-commenter · 2026-03-27T15:43:48Z

Benchmarks

Comparison

Benchmark execution time: 2026-03-27 19:11:29

Comparing candidate commit 9845517 in PR branch rachel.yang/otlp-trace-resource with baseline commit 7824b52 in branch main.

Found 1 performance improvements and 0 performance regressions! Performance is the same for 61 metrics, 0 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:profile_serialize_compressed_pprof_timestamped_x1000

🟩 execution_time [-39.484µs; -38.854µs] or [-4.242%; -4.174%]

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	`9845517`	1774637605	rachel.yang/otlp-trace-resource

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	3.417ms	3.448ms ± 0.023ms	3.443ms ± 0.009ms	3.456ms	3.485ms	3.507ms	3.656ms	6.19%	4.318	32.973	0.66%	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	[3.445ms; 3.451ms] or [-0.092%; +0.092%]	None	None	None

Group 2

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`9845517`	1774637605	rachel.yang/otlp-trace-resource

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	243.030ns	253.610ns ± 12.208ns	248.895ns ± 4.359ns	255.370ns	283.911ns	288.750ns	290.168ns	16.58%	1.701	1.745	4.80%	0.863ns	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
normalization/normalize_trace/test_trace	execution_time	[251.918ns; 255.302ns] or [-0.667%; +0.667%]	None	None	None

Group 3

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`9845517`	1774637605	rachel.yang/otlp-trace-resource

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	726.877µs	727.640µs ± 0.430µs	727.599µs ± 0.292µs	727.905µs	728.391µs	728.761µs	730.018µs	0.33%	1.232	3.979	0.06%	0.030µs	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	[727.581µs; 727.700µs] or [-0.008%; +0.008%]	None	None	None

Group 4

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`9845517`	1774637605	rachel.yang/otlp-trace-resource

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	289.155µs	289.803µs ± 0.707µs	289.697µs ± 0.159µs	289.896µs	290.355µs	291.438µs	298.468µs	3.03%	9.489	111.564	0.24%	0.050µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
sql/obfuscate_sql_string	execution_time	[289.705µs; 289.901µs] or [-0.034%; +0.034%]	None	None	None

Group 5

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`9845517`	1774637605	rachel.yang/otlp-trace-resource

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	190.721ns	192.939ns ± 1.850ns	192.798ns ± 1.275ns	193.759ns	196.519ns	197.875ns	199.323ns	3.38%	1.023	0.770	0.96%	0.131ns	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	[192.683ns; 193.196ns] or [-0.133%; +0.133%]	None	None	None

Group 6

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`9845517`	1774637605	rachel.yang/otlp-trace-resource

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	14.035µs	14.696µs ± 0.858µs	14.118µs ± 0.044µs	15.434µs	16.298µs	16.640µs	16.759µs	18.70%	0.925	-0.807	5.82%	0.061µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
two way interface	execution_time	[14.577µs; 14.815µs] or [-0.809%; +0.809%]	None	None	None

Group 7

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`9845517`	1774637605	rachel.yang/otlp-trace-resource

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	495.560µs	496.522µs ± 0.901µs	496.309µs ± 0.310µs	496.665µs	498.316µs	500.637µs	501.355µs	1.02%	3.039	10.741	0.18%	0.064µs	1	200
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000...	throughput	1994594.870op/s	2014014.024op/s ± 3633.323op/s	2014874.926op/s ± 1259.300op/s	2015997.839op/s	2016895.365op/s	2017832.505op/s	2017920.253op/s	0.15%	-3.020	10.616	0.18%	256.915op/s	1	200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	execution_time	370.628µs	371.466µs ± 0.336µs	371.455µs ± 0.224µs	371.671µs	372.085µs	372.395µs	372.579µs	0.30%	0.478	0.429	0.09%	0.024µs	1	200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	throughput	2683993.596op/s	2692035.495op/s ± 2432.810op/s	2692115.665op/s ± 1622.301op/s	2693839.228op/s	2695578.331op/s	2696723.067op/s	2698122.236op/s	0.22%	-0.472	0.420	0.09%	172.026op/s	1	200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	execution_time	167.933µs	168.168µs ± 0.123µs	168.151µs ± 0.070µs	168.230µs	168.366µs	168.613µs	168.829µs	0.40%	1.314	4.419	0.07%	0.009µs	1	200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	throughput	5923162.804op/s	5946429.444op/s ± 4359.044op/s	5947048.038op/s ± 2460.909op/s	5948986.473op/s	5952832.690op/s	5954494.641op/s	5954755.766op/s	0.13%	-1.304	4.366	0.07%	308.231op/s	1	200
normalization/normalize_service/normalize_service/[empty string]	execution_time	36.909µs	37.106µs ± 0.124µs	37.127µs ± 0.115µs	37.216µs	37.281µs	37.327µs	37.345µs	0.59%	0.023	-1.444	0.33%	0.009µs	1	200
normalization/normalize_service/normalize_service/[empty string]	throughput	26777475.173op/s	26949901.773op/s ± 89707.814op/s	26934834.394op/s ± 83342.530op/s	27040679.751op/s	27073153.477op/s	27079694.089op/s	27093632.023op/s	0.59%	-0.017	-1.447	0.33%	6343.300op/s	1	200
normalization/normalize_service/normalize_service/test_ASCII	execution_time	46.304µs	46.443µs ± 0.053µs	46.443µs ± 0.036µs	46.477µs	46.536µs	46.572µs	46.591µs	0.32%	0.180	-0.056	0.11%	0.004µs	1	200
normalization/normalize_service/normalize_service/test_ASCII	throughput	21463536.221op/s	21531791.507op/s ± 24628.533op/s	21531588.171op/s ± 16874.294op/s	21549601.739op/s	21573333.467op/s	21584559.361op/s	21596306.056op/s	0.30%	-0.173	-0.058	0.11%	1741.500op/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	[496.398µs; 496.647µs] or [-0.025%; +0.025%]	None	None	None
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000...	throughput	[2013510.481op/s; 2014517.568op/s] or [-0.025%; +0.025%]	None	None	None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	execution_time	[371.420µs; 371.513µs] or [-0.013%; +0.013%]	None	None	None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	throughput	[2691698.331op/s; 2692372.659op/s] or [-0.013%; +0.013%]	None	None	None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	execution_time	[168.151µs; 168.185µs] or [-0.010%; +0.010%]	None	None	None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	throughput	[5945825.323op/s; 5947033.566op/s] or [-0.010%; +0.010%]	None	None	None
normalization/normalize_service/normalize_service/[empty string]	execution_time	[37.089µs; 37.123µs] or [-0.046%; +0.046%]	None	None	None
normalization/normalize_service/normalize_service/[empty string]	throughput	[26937469.133op/s; 26962334.413op/s] or [-0.046%; +0.046%]	None	None	None
normalization/normalize_service/normalize_service/test_ASCII	execution_time	[46.436µs; 46.450µs] or [-0.016%; +0.016%]	None	None	None
normalization/normalize_service/normalize_service/test_ASCII	throughput	[21528378.229op/s; 21535204.785op/s] or [-0.016%; +0.016%]	None	None	None

Group 8

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`9845517`	1774637605	rachel.yang/otlp-trace-resource

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	34.286µs	34.981µs ± 1.297µs	34.390µs ± 0.047µs	34.450µs	37.762µs	37.779µs	39.018µs	13.46%	1.723	1.045	3.70%	0.092µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
redis/obfuscate_redis_string	execution_time	[34.801µs; 35.161µs] or [-0.514%; +0.514%]	None	None	None

Group 9

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`9845517`	1774637605	rachel.yang/otlp-trace-resource

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	5.269µs	5.472µs ± 0.046µs	5.473µs ± 0.042µs	5.513µs	5.530µs	5.536µs	5.578µs	1.93%	-0.404	0.124	0.84%	0.003µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
write only interface	execution_time	[5.465µs; 5.478µs] or [-0.117%; +0.117%]	None	None	None

Group 10

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`9845517`	1774637605	rachel.yang/otlp-trace-resource

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	14.800ms	14.831ms ± 0.016ms	14.830ms ± 0.010ms	14.840ms	14.857ms	14.881ms	14.898ms	0.46%	1.129	2.677	0.11%	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	[14.829ms; 14.833ms] or [-0.015%; +0.015%]	None	None	None

Group 11

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`9845517`	1774637605	rachel.yang/otlp-trace-resource

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	2.303µs	2.380µs ± 0.019µs	2.381µs ± 0.006µs	2.391µs	2.400µs	2.408µs	2.410µs	1.21%	-2.196	5.882	0.79%	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	[2.378µs; 2.383µs] or [-0.109%; +0.109%]	None	None	None

Group 12

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`9845517`	1774637605	rachel.yang/otlp-trace-resource

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	4.191ms	4.195ms ± 0.008ms	4.195ms ± 0.001ms	4.196ms	4.198ms	4.202ms	4.304ms	2.60%	12.385	163.349	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	[4.194ms; 4.197ms] or [-0.027%; +0.027%]	None	None	None

Group 13

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`9845517`	1774637605	rachel.yang/otlp-trace-resource

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	3.912µs ± 0.002µs	3.911µs ± 0.001µs	3.913µs	3.915µs	3.917µs	3.919µs	0.20%	-1.640	14.181	0.06%	0.000µs	1	200
credit_card/is_card_number/	throughput	255161736.317op/s	255652613.004op/s ± 160333.363op/s	255663031.132op/s ± 93690.949op/s	255747780.087op/s	255837448.715op/s	255933017.834op/s	256847156.455op/s	0.46%	1.666	14.386	0.06%	11337.281op/s	1	200
credit_card/is_card_number/ 3782-8224-6310-005	execution_time	78.814µs	79.577µs ± 0.329µs	79.555µs ± 0.206µs	79.751µs	80.239µs	80.390µs	80.673µs	1.41%	0.664	0.509	0.41%	0.023µs	1	200
credit_card/is_card_number/ 3782-8224-6310-005	throughput	12395724.656op/s	12566591.023op/s ± 51886.719op/s	12569963.448op/s ± 32588.575op/s	12603086.192op/s	12636086.987op/s	12663742.551op/s	12688033.382op/s	0.94%	-0.638	0.468	0.41%	3668.945op/s	1	200
credit_card/is_card_number/ 378282246310005	execution_time	72.285µs	72.894µs ± 0.340µs	72.870µs ± 0.223µs	73.104µs	73.541µs	73.753µs	74.081µs	1.66%	0.596	0.309	0.47%	0.024µs	1	200
credit_card/is_card_number/ 378282246310005	throughput	13498776.439op/s	13718794.258op/s ± 63809.579op/s	13723089.785op/s ± 42089.955op/s	13763478.885op/s	13810116.834op/s	13825400.347op/s	13834098.063op/s	0.81%	-0.569	0.249	0.46%	4512.019op/s	1	200
credit_card/is_card_number/37828224631	execution_time	3.894µs	3.912µs ± 0.003µs	3.912µs ± 0.001µs	3.914µs	3.916µs	3.919µs	3.921µs	0.23%	-0.972	9.538	0.07%	0.000µs	1	200
credit_card/is_card_number/37828224631	throughput	255053566.735op/s	255616100.806op/s ± 172230.446op/s	255639196.218op/s ± 93656.645op/s	255713917.230op/s	255815107.990op/s	255917789.379op/s	256776561.411op/s	0.44%	0.993	9.679	0.07%	12178.532op/s	1	200
credit_card/is_card_number/378282246310005	execution_time	69.163µs	69.599µs ± 0.261µs	69.517µs ± 0.136µs	69.713µs	70.155µs	70.364µs	70.424µs	1.30%	1.182	1.056	0.37%	0.018µs	1	200
credit_card/is_card_number/378282246310005	throughput	14199781.659op/s	14368162.614op/s ± 53723.549op/s	14384924.690op/s ± 28004.048op/s	14405556.584op/s	14429978.265op/s	14443602.028op/s	14458557.156op/s	0.51%	-1.164	1.005	0.37%	3798.829op/s	1	200
credit_card/is_card_number/37828224631000521389798	execution_time	52.147µs	52.287µs ± 0.047µs	52.294µs ± 0.023µs	52.314µs	52.355µs	52.384µs	52.401µs	0.21%	-0.564	0.358	0.09%	0.003µs	1	200
credit_card/is_card_number/37828224631000521389798	throughput	19083665.972op/s	19125201.177op/s ± 17168.895op/s	19122804.108op/s ± 8570.681op/s	19131793.244op/s	19157899.083op/s	19166405.201op/s	19176547.083op/s	0.28%	0.569	0.362	0.09%	1214.024op/s	1	200
credit_card/is_card_number/x371413321323331	execution_time	5.701µs	5.824µs ± 0.065µs	5.823µs ± 0.044µs	5.867µs	5.935µs	5.970µs	5.987µs	2.82%	0.145	-0.469	1.12%	0.005µs	1	200
credit_card/is_card_number/x371413321323331	throughput	167031553.390op/s	171721750.030op/s ± 1922209.930op/s	171735486.023op/s ± 1291638.001op/s	173022696.536op/s	175197067.271op/s	175365927.024op/s	175393838.893op/s	2.13%	-0.094	-0.490	1.12%	135920.768op/s	1	200
credit_card/is_card_number_no_luhn/	execution_time	3.896µs	3.913µs ± 0.003µs	3.912µs ± 0.002µs	3.915µs	3.918µs	3.920µs	3.921µs	0.23%	-0.356	4.770	0.08%	0.000µs	1	200
credit_card/is_card_number_no_luhn/	throughput	255024893.363op/s	255562217.566op/s ± 197231.002op/s	255601980.916op/s ± 120132.988op/s	255690552.816op/s	255808864.101op/s	255837354.294op/s	256706095.223op/s	0.43%	0.372	4.851	0.08%	13946.338op/s	1	200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	execution_time	64.066µs	64.460µs ± 0.165µs	64.437µs ± 0.108µs	64.567µs	64.772µs	64.932µs	64.998µs	0.87%	0.647	0.526	0.26%	0.012µs	1	200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	throughput	15385072.082op/s	15513575.657op/s ± 39612.904op/s	15519153.748op/s ± 26114.324op/s	15542625.176op/s	15564531.235op/s	15593830.863op/s	15608981.408op/s	0.58%	-0.630	0.499	0.25%	2801.055op/s	1	200
credit_card/is_card_number_no_luhn/ 378282246310005	execution_time	57.779µs	58.056µs ± 0.187µs	58.020µs ± 0.110µs	58.141µs	58.412µs	58.656µs	58.810µs	1.36%	1.322	2.106	0.32%	0.013µs	1	200
credit_card/is_card_number_no_luhn/ 378282246310005	throughput	17003803.316op/s	17224916.765op/s ± 55263.005op/s	17235459.373op/s ± 32527.133op/s	17265335.504op/s	17287490.695op/s	17297784.323op/s	17307460.290op/s	0.42%	-1.299	2.018	0.32%	3907.685op/s	1	200
credit_card/is_card_number_no_luhn/37828224631	execution_time	3.892µs	3.912µs ± 0.003µs	3.912µs ± 0.001µs	3.913µs	3.916µs	3.918µs	3.918µs	0.17%	-1.834	15.940	0.07%	0.000µs	1	200
credit_card/is_card_number_no_luhn/37828224631	throughput	255223854.377op/s	255648113.638op/s ± 167443.553op/s	255648461.276op/s ± 82812.136op/s	255733245.322op/s	255855734.269op/s	255905828.641op/s	256932840.850op/s	0.50%	1.862	16.186	0.07%	11840.047op/s	1	200
credit_card/is_card_number_no_luhn/378282246310005	execution_time	54.592µs	54.968µs ± 0.160µs	54.968µs ± 0.087µs	55.049µs	55.255µs	55.366µs	55.472µs	0.92%	0.266	0.694	0.29%	0.011µs	1	200
credit_card/is_card_number_no_luhn/378282246310005	throughput	18027146.518op/s	18192451.308op/s ± 52855.625op/s	18192350.407op/s ± 28921.410op/s	18221951.297op/s	18286907.785op/s	18309944.572op/s	18317623.385op/s	0.69%	-0.243	0.676	0.29%	3737.457op/s	1	200
credit_card/is_card_number_no_luhn/37828224631000521389798	execution_time	52.196µs	52.318µs ± 0.039µs	52.316µs ± 0.026µs	52.345µs	52.376µs	52.417µs	52.431µs	0.22%	0.077	0.349	0.07%	0.003µs	1	200
credit_card/is_card_number_no_luhn/37828224631000521389798	throughput	19072523.070op/s	19113899.021op/s ± 14112.182op/s	19114687.328op/s ± 9569.143op/s	19123311.220op/s	19135518.947op/s	19146293.078op/s	19158672.827op/s	0.23%	-0.071	0.349	0.07%	997.882op/s	1	200
credit_card/is_card_number_no_luhn/x371413321323331	execution_time	5.709µs	5.832µs ± 0.056µs	5.834µs ± 0.036µs	5.870µs	5.936µs	5.965µs	5.969µs	2.30%	0.159	-0.359	0.97%	0.004µs	1	200
credit_card/is_card_number_no_luhn/x371413321323331	throughput	167545923.927op/s	171478021.729op/s ± 1658124.498op/s	171406459.222op/s ± 1065886.907op/s	172487750.581op/s	174242699.222op/s	174779005.845op/s	175162186.167op/s	2.19%	-0.113	-0.386	0.96%	117247.108op/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	[3.911µs; 3.912µs] or [-0.009%; +0.009%]	None	None	None
credit_card/is_card_number/	throughput	[255630392.342op/s; 255674833.666op/s] or [-0.009%; +0.009%]	None	None	None
credit_card/is_card_number/ 3782-8224-6310-005	execution_time	[79.532µs; 79.623µs] or [-0.057%; +0.057%]	None	None	None
credit_card/is_card_number/ 3782-8224-6310-005	throughput	[12559400.023op/s; 12573782.024op/s] or [-0.057%; +0.057%]	None	None	None
credit_card/is_card_number/ 378282246310005	execution_time	[72.847µs; 72.941µs] or [-0.065%; +0.065%]	None	None	None
credit_card/is_card_number/ 378282246310005	throughput	[13709950.864op/s; 13727637.652op/s] or [-0.064%; +0.064%]	None	None	None
credit_card/is_card_number/37828224631	execution_time	[3.912µs; 3.912µs] or [-0.009%; +0.009%]	None	None	None
credit_card/is_card_number/37828224631	throughput	[255592231.322op/s; 255639970.289op/s] or [-0.009%; +0.009%]	None	None	None
credit_card/is_card_number/378282246310005	execution_time	[69.563µs; 69.636µs] or [-0.052%; +0.052%]	None	None	None
credit_card/is_card_number/378282246310005	throughput	[14360717.047op/s; 14375608.181op/s] or [-0.052%; +0.052%]	None	None	None
credit_card/is_card_number/37828224631000521389798	execution_time	[52.281µs; 52.294µs] or [-0.012%; +0.012%]	None	None	None
credit_card/is_card_number/37828224631000521389798	throughput	[19122821.734op/s; 19127580.621op/s] or [-0.012%; +0.012%]	None	None	None
credit_card/is_card_number/x371413321323331	execution_time	[5.815µs; 5.833µs] or [-0.155%; +0.155%]	None	None	None
credit_card/is_card_number/x371413321323331	throughput	[171455350.220op/s; 171988149.839op/s] or [-0.155%; +0.155%]	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	[255534883.246op/s; 255589551.886op/s] or [-0.011%; +0.011%]	None	None	None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	execution_time	[64.437µs; 64.483µs] or [-0.035%; +0.035%]	None	None	None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	throughput	[15508085.690op/s; 15519065.625op/s] or [-0.035%; +0.035%]	None	None	None
credit_card/is_card_number_no_luhn/ 378282246310005	execution_time	[58.030µs; 58.082µs] or [-0.045%; +0.045%]	None	None	None
credit_card/is_card_number_no_luhn/ 378282246310005	throughput	[17217257.844op/s; 17232575.686op/s] or [-0.044%; +0.044%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631	execution_time	[3.911µs; 3.912µs] or [-0.009%; +0.009%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631	throughput	[255624907.572op/s; 255671319.704op/s] or [-0.009%; +0.009%]	None	None	None
credit_card/is_card_number_no_luhn/378282246310005	execution_time	[54.946µs; 54.990µs] or [-0.040%; +0.040%]	None	None	None
credit_card/is_card_number_no_luhn/378282246310005	throughput	[18185126.027op/s; 18199776.590op/s] or [-0.040%; +0.040%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631000521389798	execution_time	[52.313µs; 52.323µs] or [-0.010%; +0.010%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631000521389798	throughput	[19111943.209op/s; 19115854.834op/s] or [-0.010%; +0.010%]	None	None	None
credit_card/is_card_number_no_luhn/x371413321323331	execution_time	[5.824µs; 5.840µs] or [-0.134%; +0.134%]	None	None	None
credit_card/is_card_number_no_luhn/x371413321323331	throughput	[171248221.621op/s; 171707821.837op/s] or [-0.134%; +0.134%]	None	None	None

Group 14

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`9845517`	1774637605	rachel.yang/otlp-trace-resource

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	4.230ms	4.235ms ± 0.006ms	4.234ms ± 0.001ms	4.235ms	4.240ms	4.275ms	4.277ms	1.02%	5.226	28.995	0.15%	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	[4.234ms; 4.236ms] or [-0.021%; +0.021%]	None	None	None

Group 15

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`9845517`	1774637605	rachel.yang/otlp-trace-resource

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	5.059µs	5.121µs ± 0.036µs	5.133µs ± 0.021µs	5.149µs	5.173µs	5.179µs	5.179µs	0.90%	-0.235	-1.336	0.70%	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	[5.116µs; 5.126µs] or [-0.097%; +0.097%]	None	None	None

Group 16

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`9845517`	1774637605	rachel.yang/otlp-trace-resource

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	50.808ms	51.083ms ± 0.973ms	50.950ms ± 0.068ms	51.022ms	51.181ms	53.819ms	62.911ms	23.48%	10.097	112.595	1.90%	0.069ms	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	[50.948ms; 51.218ms] or [-0.264%; +0.264%]	None	None	None

Group 17

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`9845517`	1774637605	rachel.yang/otlp-trace-resource

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
profile_serialize_compressed_pprof_timestamped_x1000	execution_time	889.218µs	891.700µs ± 1.180µs	891.606µs ± 0.804µs	892.490µs	893.623µs	894.867µs	895.293µs	0.41%	0.225	-0.054	0.13%	0.083µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
profile_serialize_compressed_pprof_timestamped_x1000	execution_time	[891.536µs; 891.863µs] or [-0.018%; +0.018%]	None	None	None

Group 18

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`9845517`	1774637605	rachel.yang/otlp-trace-resource

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	13.734ms	13.785ms ± 0.029ms	13.781ms ± 0.014ms	13.796ms	13.831ms	13.906ms	13.978ms	1.43%	2.674	12.197	0.21%	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	[13.781ms; 13.789ms] or [-0.030%; +0.030%]	None	None	None

Group 19

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`9845517`	1774637605	rachel.yang/otlp-trace-resource

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	145.392µs	147.120µs ± 1.640µs	146.896µs ± 0.484µs	147.402µs	148.607µs	154.062µs	163.423µs	11.25%	6.218	52.319	1.11%	0.116µs	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	[146.892µs; 147.347µs] or [-0.155%; +0.155%]	None	None	None

Group 20

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`9845517`	1774637605	rachel.yang/otlp-trace-resource

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	185.680µs	186.081µs ± 0.201µs	186.034µs ± 0.140µs	186.236µs	186.385µs	186.549µs	187.074µs	0.56%	0.974	2.220	0.11%	0.014µs	1	200
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo...	throughput	5345476.117op/s	5374020.079op/s ± 5796.638op/s	5375375.218op/s ± 4046.490op/s	5378482.829op/s	5381493.973op/s	5383056.961op/s	5385604.575op/s	0.19%	-0.963	2.168	0.11%	409.884op/s	1	200
normalization/normalize_name/normalize_name/bad-name	execution_time	17.801µs	17.864µs ± 0.027µs	17.865µs ± 0.017µs	17.883µs	17.901µs	17.921µs	17.961µs	0.54%	-0.042	0.181	0.15%	0.002µs	1	200
normalization/normalize_name/normalize_name/bad-name	throughput	55674676.490op/s	55979174.891op/s ± 85009.770op/s	55976318.728op/s ± 51827.177op/s	56021182.598op/s	56128615.090op/s	56154448.836op/s	56177043.605op/s	0.36%	0.052	0.168	0.15%	6011.099op/s	1	200
normalization/normalize_name/normalize_name/good	execution_time	10.549µs	10.603µs ± 0.028µs	10.603µs ± 0.021µs	10.625µs	10.648µs	10.653µs	10.657µs	0.51%	-0.092	-0.982	0.26%	0.002µs	1	200
normalization/normalize_name/normalize_name/good	throughput	93838197.160op/s	94317423.782op/s ± 249063.586op/s	94316698.916op/s ± 187351.474op/s	94483992.355op/s	94717102.994op/s	94772953.304op/s	94791805.357op/s	0.50%	0.100	-0.981	0.26%	17611.455op/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	[186.053µs; 186.108µs] 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	[5373216.721op/s; 5374823.438op/s] or [-0.015%; +0.015%]	None	None	None
normalization/normalize_name/normalize_name/bad-name	execution_time	[17.860µs; 17.868µs] or [-0.021%; +0.021%]	None	None	None
normalization/normalize_name/normalize_name/bad-name	throughput	[55967393.354op/s; 55990956.427op/s] or [-0.021%; +0.021%]	None	None	None
normalization/normalize_name/normalize_name/good	execution_time	[10.599µs; 10.606µs] or [-0.037%; +0.037%]	None	None	None
normalization/normalize_name/normalize_name/good	throughput	[94282905.964op/s; 94351941.600op/s] or [-0.037%; +0.037%]	None	None	None

Group 21

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`9845517`	1774637605	rachel.yang/otlp-trace-resource

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	161.685µs	162.182µs ± 0.539µs	162.096µs ± 0.141µs	162.276µs	162.593µs	163.329µs	168.786µs	4.13%	9.441	111.371	0.33%	0.038µs	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	[162.107µs; 162.257µs] or [-0.046%; +0.046%]	None	None	None

Baseline

Omitted due to size.

dd-octo-sts · 2026-03-27T15:58:34Z

Artifact Size Benchmark Report

aarch64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.so	8.76 MB	8.76 MB	0% (0 B) 👌
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.a	101.90 MB	101.91 MB	+0% (+7.32 KB) 👌

aarch64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.so	11.36 MB	11.36 MB	+0% (+48 B) 👌
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.a	118.84 MB	118.85 MB	+0% (+7.21 KB) 👌

libdatadog-x64-windows

Artifact	Baseline	Commit	Change
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.dll	27.39 MB	27.39 MB	+0% (+512 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.lib	80.69 KB	80.69 KB	0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.pdb	187.21 MB	187.19 MB	-0% (-16.00 KB) 👌
/libdatadog-x64-windows/debug/static/datadog_profiling_ffi.lib	924.91 MB	924.91 MB	+0% (+1.20 KB) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.dll	9.06 MB	9.06 MB	+0% (+512 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.lib	80.69 KB	80.69 KB	0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.pdb	26.98 MB	26.98 MB	+.02% (+8.00 KB) 🔍
/libdatadog-x64-windows/release/static/datadog_profiling_ffi.lib	61.28 MB	61.28 MB	+0% (+3.61 KB) 👌

libdatadog-x86-windows

Artifact	Baseline	Commit	Change
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.dll	23.20 MB	23.20 MB	0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.lib	81.94 KB	81.94 KB	0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.pdb	191.48 MB	191.47 MB	-0% (-8.00 KB) 👌
/libdatadog-x86-windows/debug/static/datadog_profiling_ffi.lib	908.20 MB	908.20 MB	+0% (+1.15 KB) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.dll	6.90 MB	6.90 MB	+0% (+512 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.lib	81.94 KB	81.94 KB	0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.pdb	29.11 MB	29.11 MB	0% (0 B) 👌
/libdatadog-x86-windows/release/static/datadog_profiling_ffi.lib	57.68 MB	57.68 MB	+0% (+3.07 KB) 👌

x86_64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.a	88.72 MB	88.72 MB	+0% (+2.59 KB) 👌
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.so	10.32 MB	10.32 MB	0% (0 B) 👌

x86_64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.a	111.54 MB	111.55 MB	+0% (+10.33 KB) 👌
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.so	12.07 MB	12.07 MB	0% (0 B) 👌

ekump · 2026-03-27T18:44:20Z

        });
    }
+    let resource_name = span.resource.borrow();
+    let has_resource_name = !resource_name.is_empty();


is it possible that span.resource would ever actually be empty? If so, should the test cover this scenario too?

I think span.resource could theoretically be empty for a malformed span decoded off the wire, though in practice the datadog sdk always sets it. The guard is consistent with how operation.name and span.type are currently handled. I added a new test that covers the empty case.

ekump

one question with a conditional request for test coverage. LGTM when/if addressed.

rachelyangdog · 2026-03-27T19:02:03Z

/merge

gh-worker-devflow-routing-ef8351 · 2026-03-27T19:02:07Z

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2026-03-27 19:34:07 UTC ℹ️ MergeQueue: merge request added to the queue

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2026-03-27 20:08:18 UTC ℹ️ MergeQueue: This merge request was merged

# Release proposal for libdd-sampling and its dependencies This PR contains version bumps based on public API changes and commits since last release. ## libdd-tinybytes **Next version:** `1.1.1` **Semver bump:** `patch` **Tag:** `libdd-tinybytes-v1.1.1` ### Commits - perf: pre-compute string messagepack encoding (#1948) ## libdd-trace-protobuf **Next version:** `3.0.2` **Semver bump:** `patch` **Tag:** `libdd-trace-protobuf-v3.0.2` ### Commits - feat(obfuscation)!: feature parity on span obfuscation [APMSP-2671] (#1788) ## libdd-trace-utils **Next version:** `4.0.0` **Semver bump:** `major` **Tag:** `libdd-trace-utils-v4.0.0` ### ⚠️ major bump forced due to: - `libdd-common`: ^3.0.2 → ^4.1.0 ### Commits - feat(trace-utils)!: search all spans to populate tracer payload fields (#1954) - perf: pre-compute string messagepack encoding (#1948) - feat(capablities)!: sleep & spawn capabilities (#1873) - feat(libdd-trace-utils): check for empty value in header datadog-client-computed-stats (#1900) - chore(benchmarks): add allocation size tracking allocator (#1905) - fix(crypto): gate libdd-common TLS features in obfuscation and capabilities-impl (#1872) - fix(libdd-traceutils): Update cloud environment detection logic for Serverless [SVLS-8799] (#1857) - fix(spawn_worker): defer trampoline self-deletion to avoid Valgrind false positive (#1844) - feat(runtime)!: add shared runtime (#1602) - ci: compilation of libdd-data-pipeline to wasm32 (#1830) - feat(capabilities)!: trait architecture http (#1555) - feat(trace-export): map DD span resource to OTLP resource.name attribute (#1811) - feat(otel): add support for OTLP trace export (#1641) ## libdd-sampling **Next version:** `1.0.0` **Semver bump:** `major` **Tag:** `libdd-sampling-v1.0.0` **Warning:** this is an initial release. Please verify that the version and commits included are correct. [APMSP-2671]: https://datadoghq.atlassian.net/browse/APMSP-2671?atlOrigin=eyJpIjoiNWRkNTljNzYxNjVmNDY3MDlhMDU5Y2ZhYzA5YTRkZjUiLCJwIjoiZ2l0aHViLWNvbS1KU1cifQ [SVLS-8799]: https://datadoghq.atlassian.net/browse/SVLS-8799?atlOrigin=eyJpIjoiNWRkNTljNzYxNjVmNDY3MDlhMDU5Y2ZhYzA5YTRkZjUiLCJwIjoiZ2l0aHViLWNvbS1KU1cifQ --------- Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: iunanua <18325288+iunanua@users.noreply.github.com>

chore(trace-export): add resource name as attribute

09e4eec

rachelyangdog requested a review from a team as a code owner March 27, 2026 15:28

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add empty test case

9845517

gh-worker-dd-devflow-36fce6 Bot added mergequeue-status: waiting mergequeue-status: queued mergequeue-status: in_progress and removed mergequeue-status: waiting mergequeue-status: queued labels Mar 27, 2026

gh-worker-dd-mergequeue-cf854d Bot merged commit 9b42048 into main Mar 27, 2026
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gh-worker-dd-mergequeue-cf854d Bot deleted the rachel.yang/otlp-trace-resource branch March 27, 2026 20:08

gh-worker-dd-devflow-36fce6 Bot added mergequeue-status: done and removed mergequeue-status: in_progress labels Mar 27, 2026

dd-octo-sts Bot mentioned this pull request May 18, 2026

chore(release): proposal for libdd-sampling #2004

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scenario:profile_serialize_compressed_pprof_timestamped_x1000

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