feat(data-pipeline)!: add agentless stats export

[paullegranddc]

Motivation

Perform stats aggregation and export directly to the public intake when agentless tracing is enabled

Changes

• Add paramateres on the TraceExporterBuilder
  • agentless_stats_endpoint - the fully formed URL. The API key is derived from the agentless export parameter
• Refactor the stats exporter to add a path that wraps tje ClientStatsPayload into a top-level StatsPayloas
• Hardcode the agent_version to libdd version + a libdatadog suffix to be able to differentiate metrics origin

[datadog-datadog-prod-us1-2]

✅ All CI checks and tests passed.

🎉 All green!

🧪 All tests passed
❄️ No new flaky tests detected

🎯 Code Coverage (details)
• Patch Coverage: 94.55%
• Overall Coverage: 76.94% (+0.13%)

_{This comment will be updated automatically if new data arrives.
🔗 Commit SHA: 79c8499 | Docs | View more details | Give us feedback!}

[pr-commenter]

Benchmarks

Comparison

Benchmark execution time: 2026-08-31 20:16:55

Comparing candidate commit 79c8499 in PR branch paullgdc/stats/agentless_export with baseline commit c2df70c in branch main.

Found 0 performance improvements and 2 performance regressions! Performance is the same for 133 metrics, 1 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:msgpack_decoder::v05/high_sharing/10000

• 🟥 execution_time [+369.992µs; +372.854µs] or [+4.786%; +4.823%]
• 🟥 throughput [-59516.858op/s; -59065.766op/s] or [-4.601%; -4.566%]

Benchmark execution time: 2026-08-31 20:18:23

Comparing candidate commit 79c8499 in PR branch paullgdc/stats/agentless_export with baseline commit c2df70c in branch main.

Found 5 performance improvements and 1 performance regressions! Performance is the same for 102 metrics, 10 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:datadog_sample_span/unicode_uppercase_service_rule/wall_time

• 🟥 execution_time [+17.166ns; +17.372ns] or [+5.021%; +5.081%]

scenario:glob_matcher/ascii_pattern_unicode_subject/wall_time

• 🟩 execution_time [-16.971ns; -16.745ns] or [-10.764%; -10.621%]

scenario:glob_matcher/unicode_exact_match/wall_time

• 🟩 execution_time [-13.575ns; -13.498ns] or [-15.511%; -15.423%]

scenario:glob_matcher/unicode_pattern_ascii_subject/wall_time

• 🟩 execution_time [-14.261ns; -14.188ns] or [-13.110%; -13.043%]

scenario:glob_matcher/unicode_pattern_wildcard_match/wall_time

• 🟩 execution_time [-17.806ns; -17.519ns] or [-12.471%; -12.270%]

scenario:trace_buffer/2_senders/no_delay

• 🟩 throughput [+44524.431op/s; +54269.532op/s] or [+4.199%; +5.117%]

Candidate

Omitted due to size.

Baseline

Omitted due to size.

[dd-octo-sts]

Artifact Size Benchmark Report

aarch64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.so	8.39 MB	8.39 MB	0% (0 B) 👌
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.a	90.52 MB	90.75 MB	+.24% (+231.28 KB) 🔍

aarch64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.so	11.21 MB	11.29 MB	+.65% (+75.46 KB) 🔍
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.a	101.73 MB	101.96 MB	+.23% (+241.49 KB) 🔍

libdatadog-x64-windows

Artifact	Baseline	Commit	Change
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.dll	26.96 MB	27.03 MB	+.27% (+75.00 KB) 🔍
/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	181.32 MB	181.70 MB	+.21% (+392.00 KB) 🔍
/libdatadog-x64-windows/debug/static/datadog_profiling_ffi.lib	767.06 MB	766.69 MB	--.04% (-380.92 KB) 💪
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.dll	8.88 MB	8.91 MB	+.34% (+31.00 KB) 🔍
/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	25.98 MB	26.05 MB	+.27% (+72.00 KB) 🔍
/libdatadog-x64-windows/release/static/datadog_profiling_ffi.lib	51.68 MB	51.84 MB	+.31% (+164.74 KB) 🔍

libdatadog-x86-windows

Artifact	Baseline	Commit	Change
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.dll	23.50 MB	23.57 MB	+.28% (+69.50 KB) 🔍
/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	186.35 MB	186.76 MB	+.22% (+424.00 KB) 🔍
/libdatadog-x86-windows/debug/static/datadog_profiling_ffi.lib	752.11 MB	754.57 MB	+.32% (+2.45 MB) 🔍
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.dll	6.86 MB	6.88 MB	+.34% (+24.50 KB) 🔍
/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	27.92 MB	28.00 MB	+.27% (+80.00 KB) 🔍
/libdatadog-x86-windows/release/static/datadog_profiling_ffi.lib	49.18 MB	49.34 MB	+.31% (+157.38 KB) 🔍

x86_64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.a	80.72 MB	80.92 MB	+.24% (+199.53 KB) 🔍
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.so	9.30 MB	9.33 MB	+.29% (+28.00 KB) 🔍

x86_64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.a	96.47 MB	96.67 MB	+.21% (+207.87 KB) 🔍
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.so	11.33 MB	11.37 MB	+.31% (+36.28 KB) 🔍

[chatgpt-codex-connector]

💡 Codex Review

Here are some automated review suggestions for this pull request.

Reviewed commit: fc1ff2cd86

ℹ️ About Codex in GitHub

Your team has set up Codex to 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 👍.

Codex can also answer questions or update the PR. Try commenting "@codex address that feedback".

[paullegranddc]

@codex review

[chatgpt-codex-connector]

💡 Codex Review

Here are some automated review suggestions for this pull request.

Reviewed commit: 94541f2ccf

ℹ️ About Codex in GitHub

Your team has set up Codex to 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 👍.

Codex can also answer questions or update the PR. Try commenting "@codex address that feedback".

[ekump]

This doesn't include fuzz and benchmark jobs. Please create tickets for those under this milestone to update those as well. You'll need to update the images in benchmarking-platform. Also please update the macOS AMI in ci-platform-machine-images before merging this PR. Please attach performance changes to the description of the PR

[ekump]

made a commit to add missing test coverage for additional_metric_tags. LGTM

[paullegranddc]

/merge

[gh-worker-devflow-routing-ef8351]

View all feedbacks in Devflow UI.

2026-08-31 16:27:16 UTC ℹ️ Start processing command /merge

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2026-08-31 16:27:22 UTC ℹ️ MergeQueue: Pull request is not mergeable yet

It will be processed automatically as soon as GitHub reports it as mergeable. View in MergeQueue UI.

• Run /code blockers to see what is blocking it.
• Run /remove to cancel it.

---

2026-08-31 20:22:21 UTC ℹ️ MergeQueue: merge request added to the queue

The expected merge time in main is approximately 49m (p90).

---

2026-08-31 20:52:09 UTC ℹ️ MergeQueue: This merge request was merged

[paullegranddc]

/code blockers

[gh-worker-devflow-routing-ef8351]

View all feedbacks in Devflow UI.

2026-08-31 16:35:56 UTC ℹ️ Start processing command /code blockers

---

2026-08-31 16:35:57 UTC ℹ️ Devflow:

Checking merge blockers for #2309...

---

2026-08-31 16:36:00 UTC ℹ️ Devflow: /code blockers

Detected 1 merge blocker(s) to address:

🟠 Pending

• Required check dd-gitlab/default-pipeline is running