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fix: update cargo.lock - #2381

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julio/fix-lock
Aug 20, 2026
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fix: update cargo.lock#2381
gh-worker-dd-mergequeue-cf854d[bot] merged 1 commit into
mainfrom
julio/fix-lock

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@hoolioh

@hoolioh hoolioh commented Aug 20, 2026

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What does this PR do?

Fix Cargo.lock

@hoolioh
hoolioh requested a review from a team as a code owner August 20, 2026 10:42
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🎯 Code Coverage (details)
Patch Coverage: 100.00%
Overall Coverage: 76.47% (-0.01%)

This comment will be updated automatically if new data arrives.
🔗 Commit SHA: 4af12f9 | Docs | View more details | Give us feedback!

@dd-octo-sts

dd-octo-sts Bot commented Aug 20, 2026

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Artifact Size Benchmark Report

aarch64-alpine-linux-musl
Artifact Baseline Commit Change
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.a 89.47 MB 89.47 MB 0% (0 B) 👌
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.so 8.20 MB 8.20 MB 0% (0 B) 👌
aarch64-unknown-linux-gnu
Artifact Baseline Commit Change
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.a 100.65 MB 100.65 MB 0% (0 B) 👌
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.so 11.06 MB 11.06 MB 0% (0 B) 👌
libdatadog-x64-windows
Artifact Baseline Commit Change
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.dll 26.62 MB 26.62 MB 0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.lib 94.56 KB 94.56 KB 0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.pdb 180.69 MB 180.69 MB 0% (0 B) 👌
/libdatadog-x64-windows/debug/static/datadog_profiling_ffi.lib 772.58 MB 772.58 MB 0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.dll 8.72 MB 8.72 MB 0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.lib 94.56 KB 94.56 KB 0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.pdb 25.64 MB 25.64 MB 0% (0 B) 👌
/libdatadog-x64-windows/release/static/datadog_profiling_ffi.lib 51.06 MB 51.06 MB 0% (0 B) 👌
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 96.04 KB 96.04 KB 0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.pdb 185.60 MB 185.58 MB -0% (-16.00 KB) 👌
/libdatadog-x86-windows/debug/static/datadog_profiling_ffi.lib 759.08 MB 759.08 MB 0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.dll 6.74 MB 6.74 MB 0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.lib 96.04 KB 96.04 KB 0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.pdb 27.58 MB 27.57 MB --.02% (-8.00 KB) 💪
/libdatadog-x86-windows/release/static/datadog_profiling_ffi.lib 48.60 MB 48.60 MB 0% (0 B) 👌
x86_64-alpine-linux-musl
Artifact Baseline Commit Change
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.a 79.74 MB 79.74 MB 0% (0 B) 👌
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.so 9.15 MB 9.15 MB 0% (0 B) 👌
x86_64-unknown-linux-gnu
Artifact Baseline Commit Change
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.a 95.38 MB 95.38 MB 0% (0 B) 👌
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.so 11.16 MB 11.16 MB 0% (0 B) 👌

@pr-commenter

pr-commenter Bot commented Aug 20, 2026

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Benchmarks

Comparison

Benchmark execution time: 2026-08-20 11:18:19

Comparing candidate commit 4af12f9 in PR branch julio/fix-lock with baseline commit 1765c7c in branch main.

Found 2 performance improvements and 5 performance regressions! Performance is the same for 145 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:flagevaluation_evp/coalescer/typical/100flags_50users_10fields

  • 🟥 execution_time [+12.333µs; +12.567µs] or [+6.775%; +6.904%]
  • 🟥 throughput [-35502.882op/s; -34834.974op/s] or [-6.463%; -6.341%]

scenario:msgpack_decoder::v05/low_sharing/2000

  • 🟥 execution_time [+199.326µs; +200.708µs] or [+5.759%; +5.799%]
  • 🟥 throughput [-31683.842op/s; -31463.957op/s] or [-5.483%; -5.445%]

scenario:profile_add_sample2_frames_x1000

  • 🟥 execution_time [+30.808µs; +33.931µs] or [+4.440%; +4.890%]

scenario:vec_map/get_hit/8

  • 🟩 execution_time [-9.849ns; -9.494ns] or [-13.220%; -12.745%]
  • 🟩 throughput [+15729138.423op/s; +16250062.381op/s] or [+14.643%; +15.128%]

Benchmark execution time: 2026-08-20 11:25:13

Comparing candidate commit 4af12f9 in PR branch julio/fix-lock with baseline commit 1765c7c in branch main.

Found 4 performance improvements and 5 performance regressions! Performance is the same for 159 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:alloc_free/system/4096

  • 🟩 execution_time [-8.589ns; -8.406ns] or [-9.232%; -9.036%]

scenario:datadog_sample_span/complex_rule_partial_match/wall_time

  • 🟩 execution_time [-21.344ns; -21.115ns] or [-8.275%; -8.186%]

scenario:glob_matcher/ascii_wildcard_backtrack_match/wall_time

  • 🟥 execution_time [+2.809ns; +2.840ns] or [+7.626%; +7.711%]

scenario:glob_matcher/ascii_wildcard_heavy_backtrack/wall_time

  • 🟥 execution_time [+2.777ns; +2.815ns] or [+6.789%; +6.881%]

scenario:glob_matcher/ascii_wildcard_question_match/wall_time

  • 🟩 execution_time [-18.718ns; -18.693ns] or [-32.127%; -32.083%]

scenario:glob_matcher/ascii_wildcard_star_match/wall_time

  • 🟩 execution_time [-21.043ns; -21.009ns] or [-34.727%; -34.670%]

scenario:glob_matcher/unicode_exact_match/wall_time

  • 🟥 execution_time [+6.911ns; +6.961ns] or [+9.403%; +9.470%]

scenario:glob_matcher/unicode_pattern_wildcard_match/wall_time

  • 🟥 execution_time [+5.746ns; +5.864ns] or [+4.600%; +4.695%]

scenario:profiler_attached/fast_path_system/4096

  • 🟥 execution_time [+13.921ns; +14.083ns] or [+14.987%; +15.161%]

Candidate

Omitted due to size.

Baseline

Omitted due to size.

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