feat(otel): add support for OTLP trace export by rachelyangdog · Pull Request #1641 · DataDog/libdatadog

rachelyangdog · 2026-03-02T21:42:48Z

What does this PR do?

Summary

This PR adds an OTLP HTTP/JSON trace export path to TraceExporter. When OTEL_TRACES_EXPORTER=otlp is set, the exporter converts Datadog msgpack trace payloads to OTLP and POSTs them to the configured OTLP endpoint instead of the Datadog agent. The caller (e.g. dd-trace-py) sends traces in the same format as before — no changes are required on the tracer side.

Not in scope

http/protobuf and grpc protocols (they are parsed from env but not yet implemented; http/json is the default and only supported format). This is currently a POC so we will add additional support later.

Motivation

We are seeing an increasing number of scenarios where users have applications instrumented with the OTel SDK sending data to OTel collectors, and they would like to get additional features offered by the DD SDK without needing to update their OTel collector deployments. Although there will be follow-up work, this provides the ability for users to write vendor-neutral API instrumentation and emit vendor-neutral telemetry data so DD SDK users don't have to feel locked in when setting up Datadog APM.

Additional Notes

Anything else we should know when reviewing?

How to test the change?

Describe here in detail how the change can be validated.

github-actions · 2026-03-02T21:46:36Z

Clippy Allow Annotation Report

Comparing clippy allow annotations between branches:

Base Branch: origin/main
PR Branch: origin/rachel.yang/OTLP-trace-export

Summary by Rule

Rule	Base Branch	PR Branch	Change
unwrap_used	2	2	No change (0%)
Total	2	2	No change (0%)

Annotation Counts by File

File	Base Branch	PR Branch	Change
`libdd-data-pipeline/src/trace_exporter/mod.rs`	2	2	No change (0%)

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 · 2026-03-02T22:08:49Z

Benchmarks

Comparison

Benchmark execution time: 2026-03-26 23:22:58

Comparing candidate commit 3b26275 in PR branch rachel.yang/OTLP-trace-export with baseline commit 8c88979 in branch main.

Found 6 performance improvements and 2 performance regressions! Performance is the same for 54 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:benching deserializing traces from msgpack to their internal representation

🟥 execution_time [+2.747ms; +3.085ms] or [+5.628%; +6.320%]

scenario:benching serializing traces from their internal representation to msgpack

🟩 execution_time [-986.457µs; -974.879µs] or [-6.669%; -6.591%]

scenario:credit_card/is_card_number/x371413321323331

🟩 execution_time [-597.599ns; -579.810ns] or [-9.284%; -9.008%]
🟩 throughput [+15400381.688op/s; +15918302.391op/s] or [+9.913%; +10.246%]

scenario:credit_card/is_card_number_no_luhn/x371413321323331

🟩 execution_time [-614.160ns; -598.114ns] or [-9.543%; -9.293%]
🟩 throughput [+15935376.640op/s; +16406821.224op/s] or [+10.256%; +10.559%]

scenario:profile_add_sample_frames_x1000

🟥 execution_time [+197.157µs; +198.260µs] or [+4.796%; +4.823%]

scenario:sql/obfuscate_sql_string

🟩 execution_time [-21.969µs; -21.665µs] or [-7.042%; -6.945%]

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	`3b26275`	1774566236	rachel.yang/OTLP-trace-export

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
redis/obfuscate_redis_string	execution_time	33.808µs	34.428µs ± 1.117µs	33.921µs ± 0.046µs	33.987µs	36.845µs	36.904µs	37.330µs	10.05%	1.707	0.939	3.24%	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	[34.274µs; 34.583µs] or [-0.450%; +0.450%]	None	None	None

Group 2

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3b26275`	1774566236	rachel.yang/OTLP-trace-export

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	190.409ns	192.861ns ± 1.745ns	192.763ns ± 1.312ns	193.751ns	196.134ns	198.226ns	199.584ns	3.54%	0.950	1.011	0.90%	0.123ns	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	[192.620ns; 193.103ns] or [-0.125%; +0.125%]	None	None	None

Group 3

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3b26275`	1774566236	rachel.yang/OTLP-trace-export

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	13.947µs	14.161µs ± 0.071µs	14.150µs ± 0.035µs	14.194µs	14.274µs	14.393µs	14.613µs	3.27%	1.803	8.640	0.50%	0.005µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
two way interface	execution_time	[14.151µs; 14.171µs] or [-0.070%; +0.070%]	None	None	None

Group 4

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3b26275`	1774566236	rachel.yang/OTLP-trace-export

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	289.564µs	290.135µs ± 0.702µs	290.047µs ± 0.157µs	290.209µs	290.502µs	291.839µs	298.439µs	2.89%	8.817	97.397	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	[290.037µs; 290.232µs] 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	`3b26275`	1774566236	rachel.yang/OTLP-trace-export

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	14.825ms	14.856ms ± 0.019ms	14.853ms ± 0.011ms	14.865ms	14.884ms	14.904ms	14.974ms	0.81%	2.043	9.306	0.13%	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	[14.854ms; 14.859ms] or [-0.017%; +0.017%]	None	None	None

Group 6

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3b26275`	1774566236	rachel.yang/OTLP-trace-export

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	161.863µs	162.521µs ± 0.360µs	162.470µs ± 0.134µs	162.606µs	162.932µs	163.769µs	166.008µs	2.18%	5.209	44.261	0.22%	0.025µs	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	[162.471µs; 162.570µs] or [-0.031%; +0.031%]	None	None	None

Group 7

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3b26275`	1774566236	rachel.yang/OTLP-trace-export

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	13.770ms	13.810ms ± 0.029ms	13.806ms ± 0.015ms	13.823ms	13.843ms	13.932ms	13.992ms	1.35%	2.673	11.638	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	[13.807ms; 13.814ms] or [-0.029%; +0.029%]	None	None	None

Group 8

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3b26275`	1774566236	rachel.yang/OTLP-trace-export

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	242.973ns	254.048ns ± 11.762ns	250.721ns ± 4.591ns	256.279ns	286.642ns	293.412ns	294.695ns	17.54%	2.016	3.592	4.62%	0.832ns	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
normalization/normalize_trace/test_trace	execution_time	[252.418ns; 255.678ns] or [-0.642%; +0.642%]	None	None	None

Group 9

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3b26275`	1774566236	rachel.yang/OTLP-trace-export

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	4.304ms	4.309ms ± 0.003ms	4.308ms ± 0.001ms	4.309ms	4.312ms	4.314ms	4.339ms	0.71%	5.752	55.796	0.07%	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	[4.308ms; 4.309ms] or [-0.009%; +0.009%]	None	None	None

Group 10

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3b26275`	1774566236	rachel.yang/OTLP-trace-export

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	51.499ms	51.721ms ± 0.661ms	51.614ms ± 0.058ms	51.668ms	51.800ms	56.363ms	57.247ms	10.91%	6.762	47.319	1.27%	0.047ms	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	[51.629ms; 51.812ms] or [-0.177%; +0.177%]	None	None	None

Group 11

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3b26275`	1774566236	rachel.yang/OTLP-trace-export

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	3.892µs	3.912µs ± 0.002µs	3.911µs ± 0.001µs	3.913µs	3.915µs	3.917µs	3.919µs	0.19%	-2.283	21.163	0.06%	0.000µs	1	200
credit_card/is_card_number/	throughput	255177804.142op/s	255643568.212op/s ± 158179.835op/s	255662864.969op/s ± 76864.199op/s	255729543.156op/s	255815173.110op/s	255844072.666op/s	256943064.853op/s	0.50%	2.316	21.477	0.06%	11185.003op/s	1	200
credit_card/is_card_number/ 3782-8224-6310-005	execution_time	78.976µs	79.655µs ± 0.379µs	79.627µs ± 0.234µs	79.832µs	80.336µs	80.727µs	80.930µs	1.64%	0.691	0.286	0.48%	0.027µs	1	200
credit_card/is_card_number/ 3782-8224-6310-005	throughput	12356407.028op/s	12554419.191op/s ± 59611.876op/s	12558633.133op/s ± 36888.811op/s	12601682.325op/s	12635338.772op/s	12654608.737op/s	12662044.016op/s	0.82%	-0.666	0.230	0.47%	4215.196op/s	1	200
credit_card/is_card_number/ 378282246310005	execution_time	72.323µs	72.983µs ± 0.356µs	72.943µs ± 0.239µs	73.196µs	73.534µs	74.068µs	74.229µs	1.76%	0.667	0.713	0.49%	0.025µs	1	200
credit_card/is_card_number/ 378282246310005	throughput	13471794.748op/s	13702086.749op/s ± 66534.118op/s	13709359.235op/s ± 45090.841op/s	13751251.127op/s	13801817.147op/s	13812990.744op/s	13826952.879op/s	0.86%	-0.634	0.630	0.48%	4704.673op/s	1	200
credit_card/is_card_number/37828224631	execution_time	3.895µs	3.912µs ± 0.003µs	3.912µs ± 0.001µs	3.913µs	3.916µs	3.918µs	3.919µs	0.18%	-1.041	8.956	0.06%	0.000µs	1	200
credit_card/is_card_number/37828224631	throughput	255198738.638op/s	255643170.068op/s ± 165975.192op/s	255648244.013op/s ± 87533.430op/s	255735086.860op/s	255861918.379op/s	255961872.801op/s	256747452.582op/s	0.43%	1.061	9.082	0.06%	11736.218op/s	1	200
credit_card/is_card_number/378282246310005	execution_time	69.048µs	69.633µs ± 0.288µs	69.546µs ± 0.182µs	69.821µs	70.167µs	70.354µs	70.948µs	2.02%	1.015	1.434	0.41%	0.020µs	1	200
credit_card/is_card_number/378282246310005	throughput	14094852.090op/s	14361155.795op/s ± 59232.133op/s	14379073.416op/s ± 37751.020op/s	14406930.479op/s	14431064.822op/s	14451144.441op/s	14482712.218op/s	0.72%	-0.985	1.311	0.41%	4188.344op/s	1	200
credit_card/is_card_number/37828224631000521389798	execution_time	52.232µs	52.308µs ± 0.034µs	52.307µs ± 0.019µs	52.322µs	52.373µs	52.407µs	52.447µs	0.27%	0.901	1.631	0.07%	0.002µs	1	200
credit_card/is_card_number/37828224631000521389798	throughput	19066947.030op/s	19117434.121op/s ± 12489.939op/s	19118038.105op/s ± 7076.077op/s	19125741.917op/s	19134861.773op/s	19140754.257op/s	19145452.691op/s	0.14%	-0.896	1.617	0.07%	883.172op/s	1	200
credit_card/is_card_number/x371413321323331	execution_time	5.708µs	5.848µs ± 0.064µs	5.849µs ± 0.043µs	5.887µs	5.967µs	6.008µs	6.041µs	3.28%	0.342	-0.099	1.09%	0.005µs	1	200
credit_card/is_card_number/x371413321323331	throughput	165528745.277op/s	171016153.316op/s ± 1864564.061op/s	170956527.861op/s ± 1272646.628op/s	172314535.904op/s	173522714.867op/s	174413795.159op/s	175205402.720op/s	2.49%	-0.284	-0.164	1.09%	131844.589op/s	1	200
credit_card/is_card_number_no_luhn/	execution_time	3.895µs	3.912µs ± 0.003µs	3.912µs ± 0.002µs	3.914µs	3.916µs	3.918µs	3.921µs	0.23%	-1.011	7.624	0.07%	0.000µs	1	200
credit_card/is_card_number_no_luhn/	throughput	255050183.143op/s	255628176.180op/s ± 174528.073op/s	255633944.190op/s ± 111632.127op/s	255742542.778op/s	255847753.360op/s	255919346.269op/s	256753588.350op/s	0.44%	1.029	7.736	0.07%	12340.998op/s	1	200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	execution_time	63.769µs	64.383µs ± 0.183µs	64.382µs ± 0.105µs	64.485µs	64.676µs	64.840µs	64.992µs	0.95%	0.101	0.668	0.28%	0.013µs	1	200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	throughput	15386521.250op/s	15532234.737op/s ± 44214.078op/s	15532208.129op/s ± 25368.957op/s	15558245.559op/s	15599711.892op/s	15641045.536op/s	15681564.522op/s	0.96%	-0.079	0.667	0.28%	3126.407op/s	1	200
credit_card/is_card_number_no_luhn/ 378282246310005	execution_time	57.811µs	58.288µs ± 0.240µs	58.313µs ± 0.119µs	58.406µs	58.646µs	58.950µs	59.023µs	1.22%	0.172	0.184	0.41%	0.017µs	1	200
credit_card/is_card_number_no_luhn/ 378282246310005	throughput	16942443.288op/s	17156486.739op/s ± 70675.110op/s	17148918.945op/s ± 35089.088op/s	17192847.986op/s	17273844.490op/s	17284436.878op/s	17297650.979op/s	0.87%	-0.145	0.144	0.41%	4997.485op/s	1	200
credit_card/is_card_number_no_luhn/37828224631	execution_time	3.894µs	3.911µs ± 0.003µs	3.911µs ± 0.002µs	3.913µs	3.916µs	3.919µs	3.922µs	0.26%	-0.464	6.241	0.07%	0.000µs	1	200
credit_card/is_card_number_no_luhn/37828224631	throughput	255001347.309op/s	255669042.472op/s ± 190989.656op/s	255676260.460op/s ± 106133.420op/s	255774762.964op/s	255932398.135op/s	256003454.990op/s	256814110.976op/s	0.45%	0.482	6.326	0.07%	13505.008op/s	1	200
credit_card/is_card_number_no_luhn/378282246310005	execution_time	54.516µs	54.826µs ± 0.227µs	54.740µs ± 0.111µs	54.970µs	55.253µs	55.646µs	55.806µs	1.95%	1.471	2.680	0.41%	0.016µs	1	200
credit_card/is_card_number_no_luhn/378282246310005	throughput	17919220.156op/s	18239740.795op/s ± 74910.736op/s	18268195.984op/s ± 36807.988op/s	18293397.456op/s	18314340.405op/s	18326667.252op/s	18343076.882op/s	0.41%	-1.440	2.525	0.41%	5296.989op/s	1	200
credit_card/is_card_number_no_luhn/37828224631000521389798	execution_time	52.153µs	52.290µs ± 0.061µs	52.287µs ± 0.030µs	52.320µs	52.359µs	52.415µs	52.672µs	0.73%	2.103	13.050	0.12%	0.004µs	1	200
credit_card/is_card_number_no_luhn/37828224631000521389798	throughput	18985503.678op/s	19124168.033op/s ± 22224.244op/s	19125039.408op/s ± 11104.237op/s	19135931.467op/s	19156266.150op/s	19172488.246op/s	19174476.854op/s	0.26%	-2.066	12.797	0.12%	1571.491op/s	1	200
credit_card/is_card_number_no_luhn/x371413321323331	execution_time	5.704µs	5.830µs ± 0.058µs	5.832µs ± 0.036µs	5.866µs	5.931µs	5.963µs	5.978µs	2.51%	0.092	-0.235	0.99%	0.004µs	1	200
credit_card/is_card_number_no_luhn/x371413321323331	throughput	167277127.569op/s	171546383.430op/s ± 1697900.219op/s	171469663.913op/s ± 1067624.087op/s	172575909.920op/s	174310919.286op/s	175261492.536op/s	175300613.001op/s	2.23%	-0.040	-0.248	0.99%	120059.676op/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	[255621646.008op/s; 255665490.415op/s] or [-0.009%; +0.009%]	None	None	None
credit_card/is_card_number/ 3782-8224-6310-005	execution_time	[79.602µs; 79.708µs] or [-0.066%; +0.066%]	None	None	None
credit_card/is_card_number/ 3782-8224-6310-005	throughput	[12546157.558op/s; 12562680.824op/s] or [-0.066%; +0.066%]	None	None	None
credit_card/is_card_number/ 378282246310005	execution_time	[72.934µs; 73.033µs] or [-0.068%; +0.068%]	None	None	None
credit_card/is_card_number/ 378282246310005	throughput	[13692865.760op/s; 13711307.738op/s] or [-0.067%; +0.067%]	None	None	None
credit_card/is_card_number/37828224631	execution_time	[3.911µs; 3.912µs] or [-0.009%; +0.009%]	None	None	None
credit_card/is_card_number/37828224631	throughput	[255620167.503op/s; 255666172.633op/s] or [-0.009%; +0.009%]	None	None	None
credit_card/is_card_number/378282246310005	execution_time	[69.593µs; 69.673µs] or [-0.057%; +0.057%]	None	None	None
credit_card/is_card_number/378282246310005	throughput	[14352946.791op/s; 14369364.799op/s] or [-0.057%; +0.057%]	None	None	None
credit_card/is_card_number/37828224631000521389798	execution_time	[52.304µs; 52.313µs] or [-0.009%; +0.009%]	None	None	None
credit_card/is_card_number/37828224631000521389798	throughput	[19115703.135op/s; 19119165.106op/s] or [-0.009%; +0.009%]	None	None	None
credit_card/is_card_number/x371413321323331	execution_time	[5.839µs; 5.857µs] or [-0.152%; +0.152%]	None	None	None
credit_card/is_card_number/x371413321323331	throughput	[170757742.670op/s; 171274563.962op/s] or [-0.151%; +0.151%]	None	None	None
credit_card/is_card_number_no_luhn/	execution_time	[3.912µs; 3.912µs] or [-0.009%; +0.009%]	None	None	None
credit_card/is_card_number_no_luhn/	throughput	[255603988.268op/s; 255652364.093op/s] or [-0.009%; +0.009%]	None	None	None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	execution_time	[64.357µs; 64.408µs] or [-0.039%; +0.039%]	None	None	None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	throughput	[15526107.091op/s; 15538362.383op/s] or [-0.039%; +0.039%]	None	None	None
credit_card/is_card_number_no_luhn/ 378282246310005	execution_time	[58.255µs; 58.321µs] or [-0.057%; +0.057%]	None	None	None
credit_card/is_card_number_no_luhn/ 378282246310005	throughput	[17146691.848op/s; 17166281.630op/s] or [-0.057%; +0.057%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631	execution_time	[3.911µs; 3.912µs] or [-0.010%; +0.010%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631	throughput	[255642573.143op/s; 255695511.802op/s] or [-0.010%; +0.010%]	None	None	None
credit_card/is_card_number_no_luhn/378282246310005	execution_time	[54.795µs; 54.858µs] or [-0.057%; +0.057%]	None	None	None
credit_card/is_card_number_no_luhn/378282246310005	throughput	[18229358.887op/s; 18250122.702op/s] or [-0.057%; +0.057%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631000521389798	execution_time	[52.281µs; 52.298µs] or [-0.016%; +0.016%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631000521389798	throughput	[19121087.966op/s; 19127248.099op/s] or [-0.016%; +0.016%]	None	None	None
credit_card/is_card_number_no_luhn/x371413321323331	execution_time	[5.822µs; 5.838µs] or [-0.137%; +0.137%]	None	None	None
credit_card/is_card_number_no_luhn/x371413321323331	throughput	[171311070.789op/s; 171781696.071op/s] or [-0.137%; +0.137%]	None	None	None

Group 12

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3b26275`	1774566236	rachel.yang/OTLP-trace-export

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	144.681µs	146.773µs ± 1.864µs	146.517µs ± 0.529µs	146.981µs	148.496µs	153.597µs	165.959µs	13.27%	6.793	60.569	1.27%	0.132µs	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	[146.514µs; 147.031µs] or [-0.176%; +0.176%]	None	None	None

Group 13

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3b26275`	1774566236	rachel.yang/OTLP-trace-export

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	3.425ms	3.452ms ± 0.017ms	3.448ms ± 0.010ms	3.461ms	3.485ms	3.504ms	3.511ms	1.83%	0.950	0.585	0.50%	0.001ms	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	[3.450ms; 3.454ms] or [-0.070%; +0.070%]	None	None	None

Group 14

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3b26275`	1774566236	rachel.yang/OTLP-trace-export

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	5.462µs	5.522µs ± 0.024µs	5.521µs ± 0.017µs	5.539µs	5.558µs	5.583µs	5.599µs	1.41%	0.342	0.123	0.44%	0.002µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
write only interface	execution_time	[5.519µs; 5.526µs] or [-0.061%; +0.061%]	None	None	None

Group 15

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3b26275`	1774566236	rachel.yang/OTLP-trace-export

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	5.030µs	5.098µs ± 0.044µs	5.082µs ± 0.024µs	5.152µs	5.165µs	5.167µs	5.169µs	1.71%	0.475	-1.427	0.87%	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	[5.092µs; 5.105µs] or [-0.120%; +0.120%]	None	None	None

Group 16

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3b26275`	1774566236	rachel.yang/OTLP-trace-export

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	495.326µs	497.392µs ± 2.229µs	496.402µs ± 0.544µs	498.923µs	502.515µs	504.223µs	506.629µs	2.06%	1.647	2.223	0.45%	0.158µs	1	200
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000...	throughput	1973830.516op/s	2010527.626op/s ± 8944.872op/s	2014497.443op/s ± 2209.066op/s	2016255.444op/s	2018073.824op/s	2018601.061op/s	2018871.514op/s	0.22%	-1.627	2.126	0.44%	632.498op/s	1	200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	execution_time	370.427µs	371.291µs ± 0.332µs	371.265µs ± 0.207µs	371.515µs	371.812µs	372.022µs	372.164µs	0.24%	0.153	-0.254	0.09%	0.023µs	1	200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	throughput	2686987.143op/s	2693310.086op/s ± 2404.783op/s	2693494.970op/s ± 1499.985op/s	2694794.778op/s	2697325.785op/s	2697808.862op/s	2699588.184op/s	0.23%	-0.148	-0.256	0.09%	170.044op/s	1	200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	execution_time	167.924µs	168.184µs ± 0.138µs	168.170µs ± 0.094µs	168.275µs	168.414µs	168.534µs	168.660µs	0.29%	0.535	0.271	0.08%	0.010µs	1	200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	throughput	5929087.289op/s	5945868.301op/s ± 4888.358op/s	5946360.509op/s ± 3311.230op/s	5949522.316op/s	5953095.547op/s	5954231.166op/s	5955077.389op/s	0.15%	-0.530	0.260	0.08%	345.659op/s	1	200
normalization/normalize_service/normalize_service/[empty string]	execution_time	36.941µs	37.178µs ± 0.088µs	37.179µs ± 0.056µs	37.236µs	37.326µs	37.369µs	37.386µs	0.56%	-0.218	0.004	0.24%	0.006µs	1	200
normalization/normalize_service/normalize_service/[empty string]	throughput	26747911.981op/s	26897589.888op/s ± 63671.115op/s	26896737.386op/s ± 40131.798op/s	26935155.878op/s	27022954.790op/s	27049697.131op/s	27070122.803op/s	0.64%	0.232	0.012	0.24%	4502.228op/s	1	200
normalization/normalize_service/normalize_service/test_ASCII	execution_time	46.315µs	46.435µs ± 0.114µs	46.420µs ± 0.031µs	46.459µs	46.539µs	46.631µs	47.824µs	3.02%	9.170	108.224	0.25%	0.008µs	1	200
normalization/normalize_service/normalize_service/test_ASCII	throughput	20910139.373op/s	21535816.199op/s ± 51767.014op/s	21542482.434op/s ± 14277.293op/s	21556591.922op/s	21573665.372op/s	21589024.142op/s	21591401.440op/s	0.23%	-8.979	105.060	0.24%	3660.481op/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	[497.083µs; 497.701µs] or [-0.062%; +0.062%]	None	None	None
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000...	throughput	[2009287.952op/s; 2011767.299op/s] or [-0.062%; +0.062%]	None	None	None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	execution_time	[371.245µs; 371.337µs] or [-0.012%; +0.012%]	None	None	None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	throughput	[2692976.806op/s; 2693643.366op/s] or [-0.012%; +0.012%]	None	None	None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	execution_time	[168.165µs; 168.203µs] or [-0.011%; +0.011%]	None	None	None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	throughput	[5945190.822op/s; 5946545.781op/s] or [-0.011%; +0.011%]	None	None	None
normalization/normalize_service/normalize_service/[empty string]	execution_time	[37.166µs; 37.190µs] or [-0.033%; +0.033%]	None	None	None
normalization/normalize_service/normalize_service/[empty string]	throughput	[26888765.684op/s; 26906414.092op/s] or [-0.033%; +0.033%]	None	None	None
normalization/normalize_service/normalize_service/test_ASCII	execution_time	[46.419µs; 46.450µs] or [-0.034%; +0.034%]	None	None	None
normalization/normalize_service/normalize_service/test_ASCII	throughput	[21528641.788op/s; 21542990.609op/s] or [-0.033%; +0.033%]	None	None	None

Group 17

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3b26275`	1774566236	rachel.yang/OTLP-trace-export

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	747.485µs	748.396µs ± 0.501µs	748.333µs ± 0.368µs	748.739µs	749.264µs	749.652µs	750.221µs	0.25%	0.700	0.260	0.07%	0.035µs	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	[748.327µs; 748.466µs] or [-0.009%; +0.009%]	None	None	None

Group 18

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3b26275`	1774566236	rachel.yang/OTLP-trace-export

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	2.404µs	2.442µs ± 0.019µs	2.437µs ± 0.010µs	2.452µs	2.489µs	2.498µs	2.498µs	2.53%	1.090	1.393	0.78%	0.001µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
tags/replace_trace_tags	execution_time	[2.439µs; 2.445µs] or [-0.108%; +0.108%]	None	None	None

Group 19

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3b26275`	1774566236	rachel.yang/OTLP-trace-export

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	185.539µs	186.058µs ± 0.466µs	185.966µs ± 0.232µs	186.223µs	186.897µs	187.737µs	189.457µs	1.88%	2.908	14.857	0.25%	0.033µs	1	200
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo...	throughput	5278252.307op/s	5374704.861op/s ± 13372.484op/s	5377321.979op/s ± 6721.507op/s	5384017.759op/s	5388528.099op/s	5389377.789op/s	5389705.339op/s	0.23%	-2.846	14.267	0.25%	945.577op/s	1	200
normalization/normalize_name/normalize_name/bad-name	execution_time	17.834µs	17.919µs ± 0.033µs	17.920µs ± 0.020µs	17.939µs	17.970µs	17.997µs	18.080µs	0.90%	0.480	2.343	0.18%	0.002µs	1	200
normalization/normalize_name/normalize_name/bad-name	throughput	55308886.186op/s	55807436.650op/s ± 103299.291op/s	55804238.731op/s ± 61355.225op/s	55865403.813op/s	55975199.704op/s	56034231.459op/s	56073145.769op/s	0.48%	-0.458	2.265	0.18%	7304.363op/s	1	200
normalization/normalize_name/normalize_name/good	execution_time	10.546µs	10.593µs ± 0.024µs	10.589µs ± 0.015µs	10.609µs	10.633µs	10.661µs	10.688µs	0.94%	0.817	0.957	0.22%	0.002µs	1	200
normalization/normalize_name/normalize_name/good	throughput	93560268.168op/s	94405591.337op/s ± 209786.826op/s	94440925.966op/s ± 131074.369op/s	94557852.715op/s	94693044.034op/s	94754942.859op/s	94819455.794op/s	0.40%	-0.802	0.907	0.22%	14834.169op/s	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo...	execution_time	[185.993µs; 186.122µs] or [-0.035%; +0.035%]	None	None	None
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo...	throughput	[5372851.564op/s; 5376558.159op/s] or [-0.034%; +0.034%]	None	None	None
normalization/normalize_name/normalize_name/bad-name	execution_time	[17.914µs; 17.923µs] or [-0.026%; +0.026%]	None	None	None
normalization/normalize_name/normalize_name/bad-name	throughput	[55793120.362op/s; 55821752.938op/s] or [-0.026%; +0.026%]	None	None	None
normalization/normalize_name/normalize_name/good	execution_time	[10.589µs; 10.596µs] or [-0.031%; +0.031%]	None	None	None
normalization/normalize_name/normalize_name/good	throughput	[94376516.900op/s; 94434665.773op/s] or [-0.031%; +0.031%]	None	None	None

Group 20

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3b26275`	1774566236	rachel.yang/OTLP-trace-export

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	4.268ms	4.275ms ± 0.011ms	4.272ms ± 0.002ms	4.275ms	4.290ms	4.294ms	4.398ms	2.96%	7.039	71.887	0.26%	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	[4.274ms; 4.277ms] or [-0.036%; +0.036%]	None	None	None

Group 21

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3b26275`	1774566236	rachel.yang/OTLP-trace-export

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	924.259µs	926.943µs ± 1.146µs	926.882µs ± 0.779µs	927.639µs	928.786µs	929.475µs	931.902µs	0.54%	0.439	1.050	0.12%	0.081µs	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	[926.784µs; 927.102µs] or [-0.017%; +0.017%]	None	None	None

Baseline

Omitted due to size.

dd-octo-sts · 2026-03-02T22:21:44Z

Artifact Size Benchmark Report

aarch64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.a	101.48 MB	101.90 MB	+.40% (+424.02 KB) 🔍
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.so	8.70 MB	8.76 MB	+.71% (+64.04 KB) 🔍

aarch64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.a	118.29 MB	118.84 MB	+.46% (+559.25 KB) 🔍
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.so	11.29 MB	11.36 MB	+.64% (+74.34 KB) 🔍

libdatadog-x64-windows

Artifact	Baseline	Commit	Change
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.dll	27.26 MB	27.39 MB	+.47% (+133.50 KB) 🔍
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.lib	80.34 KB	80.69 KB	+.43% (+360 B) 🔍
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.pdb	186.55 MB	187.19 MB	+.34% (+656.00 KB) 🔍
/libdatadog-x64-windows/debug/static/datadog_profiling_ffi.lib	921.18 MB	924.91 MB	+.40% (+3.73 MB) 🔍
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.dll	9.00 MB	9.06 MB	+.68% (+63.50 KB) 🔍
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.lib	80.34 KB	80.69 KB	+.43% (+360 B) 🔍
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.pdb	26.84 MB	26.98 MB	+.49% (+136.00 KB) 🔍
/libdatadog-x64-windows/release/static/datadog_profiling_ffi.lib	61.03 MB	61.27 MB	+.40% (+253.06 KB) 🔍

libdatadog-x86-windows

Artifact	Baseline	Commit	Change
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.dll	23.08 MB	23.20 MB	+.51% (+121.50 KB) 🔍
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.lib	81.59 KB	81.94 KB	+.43% (+364 B) 🔍
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.pdb	190.77 MB	191.48 MB	+.37% (+728.00 KB) 🔍
/libdatadog-x86-windows/debug/static/datadog_profiling_ffi.lib	904.47 MB	908.20 MB	+.41% (+3.73 MB) 🔍
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.dll	6.86 MB	6.90 MB	+.59% (+41.50 KB) 🔍
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.lib	81.59 KB	81.94 KB	+.43% (+364 B) 🔍
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.pdb	28.97 MB	29.11 MB	+.48% (+144.00 KB) 🔍
/libdatadog-x86-windows/release/static/datadog_profiling_ffi.lib	57.44 MB	57.67 MB	+.40% (+236.54 KB) 🔍

x86_64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.a	88.32 MB	88.71 MB	+.44% (+404.84 KB) 🔍
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.so	10.28 MB	10.32 MB	+.41% (+44.04 KB) 🔍

x86_64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.a	111.03 MB	111.53 MB	+.44% (+507.51 KB) 🔍
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.so	12.03 MB	12.07 MB	+.35% (+43.35 KB) 🔍

codecov-commenter · 2026-03-03T01:47:43Z

Codecov Report

❌ Patch coverage is 80.61224% with 133 lines in your changes missing coverage. Please review.
✅ Project coverage is 71.17%. Comparing base (8c88979) to head (3b26275).

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #1641      +/-   ##
==========================================
+ Coverage   71.00%   71.17%   +0.16%     
==========================================
  Files         411      414       +3     
  Lines       65052    65738     +686     
==========================================
+ Hits        46190    46788     +598     
- Misses      18862    18950      +88

Components	Coverage Δ
libdd-crashtracker	`65.31% <ø> (-0.02%)`	⬇️
libdd-crashtracker-ffi	`35.24% <ø> (ø)`
libdd-alloc	`98.77% <ø> (ø)`
libdd-data-pipeline	`87.55% <67.64%> (-0.06%)`	⬇️
libdd-data-pipeline-ffi	`75.77% <12.50%> (+2.43%)`	⬆️
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	`81.62% <ø> (ø)`
libdd-profiling-ffi	`64.94% <ø> (ø)`
datadog-sidecar	`30.79% <ø> (+0.46%)`	⬆️
datdog-sidecar-ffi	`9.37% <ø> (+2.17%)`	⬆️
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	`88.64% <84.88%> (-0.32%)`	⬇️
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.

paullegranddc

To test the otlp trace export, you can add test agent snapshot tests here

rachelyangdog · 2026-03-26T22:22:02Z

/merge

gh-worker-devflow-routing-ef8351 · 2026-03-26T22:22:05Z

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…ute (#1811) # 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. Co-authored-by: rachel.yang <rachel.yang@datadoghq.com>

## Description  Adds native OTLP trace export support to dd-trace-py using libdatadog's TraceExporter. When `OTEL_TRACES_EXPORTER=otlp `, traces are sent directly to an OTLP collector instead of the Datadog agent. - the [libdatadog PR](DataDog/libdatadog#1641) that adds support for OTLP trace export ## Testing  ## Risks  ## Additional Notes  - libdd-data-pipeline is pinned to an unreleased commit on DataDog/libdatadog@rachel.yang/OTLP-trace-export. This should be updated to a release tag once that branch merges. - Only http/json protocol is supported for OTLP traces (libdatadog limitation); gRPC is not yet available. Co-authored-by: rachel.yang <rachel.yang@datadoghq.com>

# 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>

# Release proposal for libdd-data-pipeline and its dependencies This PR contains version bumps based on public API changes and commits since last release. ## libdd-dogstatsd-client **Next version:** `3.0.0` **Semver bump:** `major` **Tag:** `libdd-dogstatsd-client-v3.0.0` ### ⚠️ major bump forced due to: - `libdd-common`: ^3.0.2 → ^4.1.0 ### Commits - fix(crypto): gate libdd-common TLS features in remaining internal crates + add CI guard (#1943) ## libdd-trace-obfuscation **Next version:** `3.0.0` **Semver bump:** `major` **Tag:** `libdd-trace-obfuscation-v3.0.0` ### ⚠️ major bump forced due to: - `libdd-common`: ^3.0.2 → ^4.1.0 - `libdd-trace-utils`: ^3.0.1 → ^4.0.0 ### Commits - feat!: integrate obfuscation to the stats exporter [APMSP-2764] (#1819) - feat!: added regex-lite feature (#1939) - chore: clippy (#1889) - fix(crypto): gate libdd-common TLS features in obfuscation and capabilities-impl (#1872) - feat(obfuscation)!: feature parity on span obfuscation [APMSP-2671] (#1788) - feat(obfuscation/sql): feature parity on sql obfuscation [APMSP-2667] (#1708) ## libdd-trace-stats **Next version:** `3.0.0` **Semver bump:** `major` **Tag:** `libdd-trace-stats-v3.0.0` ### ⚠️ major bump forced due to: - `libdd-trace-utils`: ^3.0.1 → ^4.0.0 ### Commits - perf: pre-compute string messagepack encoding (#1948) - feat!: integrate obfuscation to the stats exporter [APMSP-2764] (#1819) - feat(capablities)!: sleep & spawn capabilities (#1873) - feat: use ip quantization when aggregating peer tags for trace stats (#1944) - fix(crypto): gate libdd-common TLS features in remaining internal crates + add CI guard (#1943) - feat(shared_runtime)!: allow worker to be stopped after fork (#1893) - feat(sidecar)!: Add stats computation via SHM (#1821) - feat(stats): propagate service source from span meta to client stats payload (#1803) - fix(stats): align with css spec (#1790) ## libdd-data-pipeline **Next version:** `4.0.0` **Semver bump:** `major` **Tag:** `libdd-data-pipeline-v4.0.0` ### ⚠️ major bump forced due to: - `libdd-common`: ^3.0.2 → ^4.1.0 - `libdd-telemetry`: ^4.0.0 → ^5.0.0 - `libdd-trace-utils`: ^3.0.1 → ^4.0.0 ### Commits - fix(libdd-telemetry): restore previous Cargo.toml version (#1993) - fix(data-pipeline): remove default-features from of trace-obfuscation (#1981) - fix(trace_exporter: shared_runtime): unwrap_or being eager is not good (#1983) - perf: pre-compute string messagepack encoding (#1948) - feat!: integrate obfuscation to the stats exporter [APMSP-2764] (#1819) - feat(capablities)!: sleep & spawn capabilities (#1873) - fix(telemetry): avoid trigger loop in telemetry worker (#1950) - feat(telemetry)!: include dependencies and integrations in app-extended-heartbeat (#1962) - perf(trace-serializer): pre-allocate serialization buffer (#1949) - feat!: added regex-lite feature (#1939) - fix(crypto): gate libdd-common TLS features in remaining internal crates + add CI guard (#1943) - feat(telemetry): add session id support to trace export (#1822) - fix(path): missing bench path in data-pipeline (#1907) - feat(data-pipeline): port dd-trace-rs trace buffer implementation (#1826) - feat(info_fetcher): add timeout to info fetcher (#1890) - feat(shared_runtime)!: allow worker to be stopped after fork (#1893) - feat(sidecar)!: Add stats computation via SHM (#1821) - ci(libdd-shared-runtime): downgrade version so publish workflow succeeds (#1870) - feat(runtime)!: add shared runtime (#1602) - ci: compilation of libdd-data-pipeline to wasm32 (#1830) - feat(capabilities)!: trait architecture http (#1555) - feat(otel): add support for OTLP trace export (#1641) - fix(stats): align with css spec (#1790) --------- Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: iunanua <18325288+iunanua@users.noreply.github.com>

WIP: OTLP trace export

1e86c8d

rachelyangdog requested a review from a team as a code owner March 2, 2026 21:42

rachelyangdog marked this pull request as draft March 2, 2026 21:42

github-actions Bot added the data-pipeline label Mar 2, 2026

rachelyangdog added 2 commits March 2, 2026 16:48

linting

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linting on comments

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fix endpoint and mapping

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mabdinur reviewed Mar 6, 2026

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rachelyangdog marked this pull request as ready for review March 6, 2026 19:18

rachelyangdog added 2 commits March 6, 2026 14:34

implement feedback

2dd4b57

lint and private fields

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paullegranddc reviewed Mar 9, 2026

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Comment thread libdd-trace-utils/src/otlp_encoder/json_types.rs Outdated

paullegranddc reviewed Mar 9, 2026

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Comment thread libdd-data-pipeline/src/trace_exporter/mod.rs Outdated

send_with_retry and move to libdd_trace_utils

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rachelyangdog requested a review from a team as a code owner March 10, 2026 14:08

github-actions Bot added the mini-agent label Mar 10, 2026

rachelyangdog added 2 commits March 10, 2026 10:51

lint + nits

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lint

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paullegranddc reviewed Mar 11, 2026

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Comment thread libdd-data-pipeline/src/otlp/config.rs Outdated

Comment thread libdd-data-pipeline/src/otlp/exporter.rs Outdated

paullegranddc reviewed Mar 11, 2026

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Comment thread libdd-data-pipeline/src/trace_exporter/mod.rs Outdated

rachelyangdog added 5 commits March 11, 2026 19:27

config change and sampling update

f1f7921

Merge branch 'main' into rachel.yang/OTLP-trace-export

82435cb

linting issues

e1b519b

Merge branch 'main' into rachel.yang/OTLP-trace-export

8773444

merge refactor and update

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gh-worker-dd-devflow-36fce6 Bot added mergequeue-status: in_progress mergequeue-status: done and removed mergequeue-status: queued mergequeue-status: in_progress labels Mar 26, 2026

gh-worker-dd-devflow-36fce6 Bot added mergequeue-status: queued mergequeue-status: in_progress mergequeue-status: rejected and removed mergequeue-status: done mergequeue-status: queued mergequeue-status: in_progress labels Mar 26, 2026

Merge branch 'main' into rachel.yang/OTLP-trace-export

3b26275

gh-worker-dd-devflow-36fce6 Bot added mergequeue-status: waiting mergequeue-status: queued mergequeue-status: in_progress and removed mergequeue-status: rejected mergequeue-status: waiting mergequeue-status: queued labels Mar 26, 2026

gh-worker-dd-mergequeue-cf854d Bot merged commit ee83a45 into main Mar 27, 2026
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gh-worker-dd-devflow-36fce6 Bot removed the mergequeue-status: in_progress label Mar 27, 2026

gh-worker-dd-mergequeue-cf854d Bot deleted the rachel.yang/OTLP-trace-export branch March 27, 2026 00:12

gh-worker-dd-devflow-36fce6 Bot added the mergequeue-status: done label Mar 27, 2026

rachelyangdog mentioned this pull request Mar 27, 2026

feat(trace-export): map DD span resource to OTLP resource.name attribute #1811

Merged

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

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

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

chore(release): proposal for libdd-data-pipeline #2007

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What does this PR do?

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Motivation

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Clippy Allow Annotation Report

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Benchmarks

Comparison

Explanation

More details about the CI and significant changes

scenario:benching deserializing traces from msgpack to their internal representation

scenario:benching serializing traces from their internal representation to msgpack

scenario:credit_card/is_card_number/x371413321323331

scenario:credit_card/is_card_number_no_luhn/x371413321323331

scenario:profile_add_sample_frames_x1000

scenario:sql/obfuscate_sql_string

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Baseline

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Artifact Size Benchmark Report

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