libdatadog update to 64ad2ed5

[dd-octo-sts]

Summary

Automated update of the libdatadog submodule to the latest HEAD.

	SHA
Previous	$LIBDATADOG_PINNED_SHA
New	64ad2ed5c793ce0b2550239734bb48c9ce442116

Full CI result: ❌ 31 job(s) failed
CI pipeline: https://gitlab.ddbuild.io/DataDog/apm-reliability/dd-trace-php/-/pipelines/135765896

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(Claude did not produce a report — see tmp/artifacts/claude_output.txt in the CI pipeline.)

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/cc @bwoebi

[datadog-datadog-prod-us1-2]

 

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⚠️ Warnings

❌ Your PR has failed checks. Please review the issues below and take necessary action before merging.

🚦 35 Pipeline jobs failed

DataDog/apm-reliability/dd-trace-php | check libxml2 version — 🔧 Needs a code fix, caused by this PR

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DataDog/apm-reliability/dd-trace-php | test_extension_ci: [7.2, valgrind] — 🔧 Needs a code fix, caused by this PR

View more details · View in GitLab

DataDog/apm-reliability/dd-trace-php | test_extension_ci: [8.3] — 🔧 Needs a code fix, caused by this PR

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View all 35 failed jobs.

ℹ️ Info

No other issues found (see more)

🧪 All tests passed
❄️ No new flaky tests detected

🎯 Code Coverage (details)
• Patch Coverage: 100.00%
• Overall Coverage: 54.99% (-0.11%)

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_{This comment will be updated automatically if new data arrives.
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[pr-commenter]

Benchmarks [ tracer ]

Benchmark execution time: 2026-09-07 06:20:08

Comparing candidate commit 09eb848 in PR branch bot/libdatadog-latest with baseline commit 3b1267d in branch master.

Found 0 performance improvements and 2 performance regressions! Performance is the same for 191 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:HookBench/benchHookOverheadTraceFunction

• 🟥 execution_time [+4.396µs; +15.347µs] or [+2.206%; +7.701%]

scenario:SamplingRuleMatchingBench/benchRegexMatching4

• 🟥 execution_time [+53.271ns; +130.129ns] or [+3.592%; +8.774%]

[cataphract]

Blocked by #3725