Ekump/test oom benchmarks issue

[ekump]

DO NOT MERGE

What does this PR do?

A brief description of the change being made with this pull request.

Motivation

What inspired you to submit this pull request?

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]

Clippy Allow Annotation Report

Comparing clippy allow annotations between branches:

• Base Branch: origin/ekump/APMSP-3628-only-run-perf-bench-for-impacted-crates
• PR Branch: origin/ekump/test-oom-benchmarks-issue

Summary by Rule

Rule	Base Branch	PR Branch	Change

Annotation Counts by File

File	Base Branch	PR Branch	Change

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	22	22	No change (0%)
datadog-live-debugger	4	4	No change (0%)
datadog-live-debugger-ffi	10	10	No change (0%)
datadog-profiling-replayer	4	4	No change (0%)
datadog-sidecar	45	45	No change (0%)
libdd-common	13	13	No change (0%)
libdd-common-ffi	12	12	No change (0%)
libdd-data-pipeline	6	6	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-remote-config	3	3	No change (0%)
libdd-telemetry	20	20	No change (0%)
libdd-tinybytes	4	4	No change (0%)
libdd-trace-normalization	2	2	No change (0%)
libdd-trace-obfuscation	3	3	No change (0%)
libdd-trace-stats	1	1	No change (0%)
libdd-trace-utils	11	11	No change (0%)
Total	182	182	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.

[datadog-official]

✨ Fix all issues with BitsAI

⚠️ Warnings

🚦 2 Pipeline jobs failed

Required checks pass | allchecks     

pr-name | pr_name_lint     

ℹ️ Info

🎯 Code Coverage (details)
• Patch Coverage: 100.00%
• Overall Coverage: 74.34% (-0.07%)

Useful? React with 👍 / 👎

_{This comment will be updated automatically if new data arrives.
🔗 Commit SHA: a063c12 | Docs | Datadog PR Page | Give us feedback!}

[dd-octo-sts]

Artifact Size Benchmark Report

aarch64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.a	85.89 MB	85.89 MB	0% (0 B) 👌
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.so	7.88 MB	7.88 MB	0% (0 B) 👌

aarch64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.a	97.11 MB	97.11 MB	0% (0 B) 👌
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.so	10.61 MB	10.61 MB	0% (0 B) 👌

libdatadog-x64-windows

Artifact	Baseline	Commit	Change
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.dll	25.45 MB	25.45 MB	0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.lib	88.44 KB	88.44 KB	0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.pdb	184.54 MB	184.54 MB	0% (0 B) 👌
/libdatadog-x64-windows/debug/static/datadog_profiling_ffi.lib	946.77 MB	946.77 MB	0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.dll	8.32 MB	8.32 MB	0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.lib	88.44 KB	88.44 KB	0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.pdb	24.62 MB	24.62 MB	0% (0 B) 👌
/libdatadog-x64-windows/release/static/datadog_profiling_ffi.lib	49.03 MB	49.03 MB	0% (0 B) 👌

libdatadog-x86-windows

Artifact	Baseline	Commit	Change
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.dll	22.05 MB	22.05 MB	0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.lib	89.82 KB	89.82 KB	0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.pdb	188.76 MB	188.76 MB	0% (0 B) 👌
/libdatadog-x86-windows/debug/static/datadog_profiling_ffi.lib	935.45 MB	935.45 MB	0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.dll	6.43 MB	6.43 MB	0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.lib	89.82 KB	89.82 KB	0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.pdb	26.43 MB	26.43 MB	0% (0 B) 👌
/libdatadog-x86-windows/release/static/datadog_profiling_ffi.lib	46.66 MB	46.66 MB	0% (0 B) 👌

x86_64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.a	76.59 MB	76.59 MB	0% (0 B) 👌
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.so	8.78 MB	8.78 MB	0% (0 B) 👌

x86_64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.a	92.11 MB	92.11 MB	0% (0 B) 👌
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.so	10.70 MB	10.70 MB	0% (0 B) 👌

[pr-commenter]

Benchmarks

Comparison

Benchmark execution time: 2026-07-09 18:19:37

Comparing candidate commit a063c12 in PR branch ekump/test-oom-benchmarks-issue with baseline commit e026a3c in branch main.

Found 1 performance improvements and 2 performance regressions! Performance is the same for 126 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:normalization/normalize_trace/test_trace

• 🟩 execution_time [-48.995ns; -45.063ns] or [-16.211%; -14.910%]

scenario:vec_map/get_hit/16

• 🟥 execution_time [+11.258ns; +14.005ns] or [+4.774%; +5.939%]
• 🟥 throughput [-3712643.607op/s; -2984063.462op/s] or [-5.472%; -4.398%]

Benchmark execution time: 2026-07-09 18:25:52

Comparing candidate commit a063c12 in PR branch ekump/test-oom-benchmarks-issue with baseline commit e026a3c in branch main.

Found 4 performance improvements and 2 performance regressions! Performance is the same for 143 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:ddsketch_read/ordered_bins/clustered_near_zero

• 🟩 execution_time [-403.315ns; -400.390ns] or [-6.784%; -6.734%]

scenario:ddsketch_read/ordered_bins/collapsing

• 🟩 execution_time [-1.757µs; -1.744µs] or [-6.643%; -6.592%]

scenario:ddsketch_read/ordered_bins/large_values

• 🟩 execution_time [-544.285ns; -541.338ns] or [-7.140%; -7.101%]

scenario:ddsketch_read/ordered_bins/mixed

• 🟩 execution_time [-772.843ns; -768.020ns] or [-6.634%; -6.593%]

scenario:profiles_dictionary/profile_string_inserts/threads/1

• 🟥 execution_time [+14.136µs; +17.146µs] or [+4.676%; +5.672%]
• 🟥 throughput [-182678.405op/s; -150585.026op/s] or [-5.393%; -4.446%]

Candidate

Omitted due to size.

Baseline

Omitted due to size.