fix(stats): fix precedence for http endpoint

[VianneyRuhlmann]

What does this PR do?

Fixes a change from !2323 which makes http.route take precedence over http.endpoint. This makes system-tests fail in dd-trace-py and doesn't seem to be the right default behavior.

Motivation

This is currently preventing us from bumping libdatadog in dd-trace-py.

Additional Notes

The OTLP semantics RFC doesn't mention this change, however if this is require this should be added behind a feature flag.

How to test the change?

Describe here in detail how the change can be validated.

[datadog-official]

✅ All CI checks and tests passed.

🎉 All green!

🧪 All tests passed
❄️ No new flaky tests detected

🎯 Code Coverage (details)
• Patch Coverage: 100.00%
• Overall Coverage: 78.64% (-0.02%)

_{This comment will be updated automatically if new data arrives.
🔗 Commit SHA: 175040f | Docs | View more details | Give us feedback!}

[pr-commenter]

Benchmarks

Comparison

Benchmark execution time: 2026-09-29 09:34:56

Comparing candidate commit 175040f in PR branch vianney/fix-http-endpoint-precedence with baseline commit e0ad8ac in branch main.

📊 Benchmarking dashboard

Found 0 performance improvements and 0 performance regressions! Performance is the same for 3 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 ----------------------------------'

Candidate

Candidate benchmark details

Group 1

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz	175040f	1790673858	vianney/fix-http-endpoint-precedence

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	2.063µs	2.077µs ± 0.007µs	2.076µs ± 0.003µs	2.079µs	2.090µs	2.104µs	2.116µs	1.97%	2.611	10.575	0.31%	0.000µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
write only interface	execution_time	[2.076µs; 2.078µs] or [-0.044%; +0.044%]	None	None	None

Group 2

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz	175040f	1790673858	vianney/fix-http-endpoint-precedence

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	9.518ms	9.541ms ± 0.016ms	9.536ms ± 0.009ms	9.551ms	9.569ms	9.594ms	9.604ms	0.71%	1.161	1.249	0.17%	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	[9.538ms; 9.543ms] or [-0.024%; +0.024%]	None	None	None

Group 3

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz	175040f	1790673858	vianney/fix-http-endpoint-precedence

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	21.021µs	21.729µs ± 0.216µs	21.702µs ± 0.119µs	21.840µs	22.114µs	22.243µs	22.929µs	5.65%	0.974	4.355	0.99%	0.015µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
two way interface	execution_time	[21.699µs; 21.759µs] or [-0.138%; +0.138%]	None	None	None

Baseline

Baseline benchmark details

Group 1

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz	e0ad8ac	1790613646	main

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	2.068µs	2.082µs ± 0.006µs	2.080µs ± 0.003µs	2.083µs	2.094µs	2.101µs	2.114µs	1.62%	1.879	5.481	0.30%	0.000µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
write only interface	execution_time	[2.081µs; 2.083µs] or [-0.042%; +0.042%]	None	None	None

Group 2

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz	e0ad8ac	1790613646	main

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	9.509ms	9.537ms ± 0.018ms	9.533ms ± 0.010ms	9.546ms	9.569ms	9.586ms	9.617ms	0.88%	1.197	1.794	0.18%	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	[9.534ms; 9.539ms] or [-0.026%; +0.026%]	None	None	None

Group 3

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz	e0ad8ac	1790613646	main

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	21.535µs	22.010µs ± 0.306µs	21.975µs ± 0.154µs	22.156µs	22.430µs	22.680µs	24.446µs	11.25%	3.063	19.989	1.39%	0.022µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
two way interface	execution_time	[21.968µs; 22.053µs] or [-0.192%; +0.192%]	None	None	None

[dd-octo-sts]

Artifact Size Benchmark Report

aarch64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.a	96.05 MB	96.05 MB	0% (0 B) 👌
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.so	9.02 MB	9.02 MB	0% (0 B) 👌

aarch64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.a	107.43 MB	107.43 MB	0% (0 B) 👌
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.so	12.19 MB	12.19 MB	0% (0 B) 👌

libdatadog-x64-windows

Artifact	Baseline	Commit	Change
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.dll	29.08 MB	29.08 MB	0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.lib	96.08 KB	96.08 KB	0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.pdb	191.55 MB	191.52 MB	--.01% (-32.00 KB) 💪
/libdatadog-x64-windows/debug/static/datadog_profiling_ffi.lib	815.49 MB	815.49 MB	0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.dll	9.72 MB	9.72 MB	0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.lib	96.08 KB	96.08 KB	0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.pdb	27.51 MB	27.51 MB	--.02% (-8.00 KB) 💪
/libdatadog-x64-windows/release/static/datadog_profiling_ffi.lib	55.62 MB	55.62 MB	0% (0 B) 👌

libdatadog-x86-windows

Artifact	Baseline	Commit	Change
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.dll	25.42 MB	25.42 MB	0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.lib	97.58 KB	97.58 KB	0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.pdb	196.76 MB	196.75 MB	-0% (-16.00 KB) 👌
/libdatadog-x86-windows/debug/static/datadog_profiling_ffi.lib	802.14 MB	802.14 MB	0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.dll	7.54 MB	7.54 MB	0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.lib	97.58 KB	97.58 KB	0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.pdb	29.62 MB	29.62 MB	0% (0 B) 👌
/libdatadog-x86-windows/release/static/datadog_profiling_ffi.lib	52.56 MB	52.56 MB	0% (0 B) 👌

x86_64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.a	86.06 MB	86.06 MB	0% (0 B) 👌
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.so	10.06 MB	10.06 MB	0% (0 B) 👌

x86_64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.a	101.90 MB	101.90 MB	0% (0 B) 👌
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.so	12.28 MB	12.28 MB	0% (0 B) 👌

[chatgpt-codex-connector]

💡 Codex Review

Here are some automated review suggestions for this pull request.

Reviewed commit: 55f2cce5d6

ℹ️ About Codex in GitHub

Codex has been enabled to automatically review pull requests in this repo. Reviews are triggered when you

• Open a pull request for review
• Mark a draft as ready
• Comment "@codex review".

If Codex has suggestions, it will comment; otherwise it will react with 👍.

When you sign up for Codex through ChatGPT, Codex can also answer questions or update the PR, like "@codex address that feedback".

[ekump]

Approving, but I think you need to address the empty route issue before merging.

[gh-worker-devflow-routing-ef8351]

View all feedbacks in Devflow UI.

2026-09-29 12:46:28 UTC ℹ️ Start processing command devflow:merge

---

2026-09-29 12:46:33 UTC ℹ️ MergeQueue: pull request added to the queue

The expected merge time in main is approximately 48m (p90).

---

2026-09-29 13:24:35 UTC ℹ️ MergeQueue: This merge request was merged