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fix(ffe): remove start_at/end_at from reason computation#1801

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leo.romanovsky/fix-ffe-reason
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fix(ffe): remove start_at/end_at from reason computation#1801
leoromanovsky wants to merge 4 commits intomainfrom
leo.romanovsky/fix-ffe-reason

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@leoromanovsky leoromanovsky commented Mar 26, 2026

Motivation

The datadog-ffe crate's reason determination treats start_at/end_at on allocations as targeting signals, producing TARGETING_MATCH for time-bounded allocations even when they have no rules. This diverges from the canonical Go implementation where time bounds are pre-filters only — not reason signals.

The UFC service in dd-source confirms: override allocations always have empty rules, empty shards, and nil start_at/end_at. Waterfall allocations may have time bounds, but the reason should still be determined solely from rules and shards.

Changes

  • eval_assignment.rs: Removed || self.start_at.is_some() || self.end_at.is_some() from the TARGETING_MATCH condition. Reason is now computed from rules and shards only, matching Go's canonical algorithm.
  • eval_assignment.rs (tests): Added reason field to TestResult struct and assertion to the fixture loop test.
  • 20 fixture JSON files: Added "reason" field to all test case results, using Go's verified fixtures as the source of truth.

Decisions

  • Canonical algorithm: !rules.is_empty() → TargetingMatch; shards present → Split; else → Static
  • start_at/end_at remain functional as time-window pre-filters — only the reason derivation changes
  • This fix propagates to Ruby and Python automatically (they use libdatadog via FFI)

@leoromanovsky
fix(05-01): remove start_at/end_at from reason computation
abad267 
- Remove || self.start_at.is_some() || self.end_at.is_some() from TARGETING_MATCH condition
- Add reason field to TestResult struct with serde(default) for backward compat
- Add reason assertion in test loop matching Ok/Err variants
- Add AssignmentReason and EvaluationError to test imports
@leoromanovsky
test(05-01): add reason values to all 20 fixture JSON files
f4a19b3 
- Copy reason values from Go reference fixtures for 19 files
- Derive reason for test-case-null-targeting-key.json (no Go equivalent)
- Fix empty_string_flag/bob: STATIC not SPLIT (Rust optimizes away insignificant shards)
- All 20 fixtures now assert reason field via test loop
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github-actions bot commented Mar 26, 2026

Clippy Allow Annotation Report

Comparing clippy allow annotations between branches:

  • Base Branch: origin/main
  • PR Branch: origin/leo.romanovsky/fix-ffe-reason

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 20 20 No change (0%)
datadog-live-debugger 6 6 No change (0%)
datadog-live-debugger-ffi 10 10 No change (0%)
datadog-profiling-replayer 4 4 No change (0%)
datadog-remote-config 3 3 No change (0%)
datadog-sidecar 55 55 No change (0%)
libdd-common 10 10 No change (0%)
libdd-common-ffi 12 12 No change (0%)
libdd-data-pipeline 5 5 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-telemetry 19 19 No change (0%)
libdd-tinybytes 4 4 No change (0%)
libdd-trace-normalization 2 2 No change (0%)
libdd-trace-obfuscation 8 8 No change (0%)
libdd-trace-utils 15 15 No change (0%)
Total 195 195 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.

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codecov-commenter commented Mar 26, 2026 •
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Codecov Report

❌ Patch coverage is 84.61538% with 2 lines in your changes missing coverage. Please review.
✅ Project coverage is 71.06%. Comparing base (db9b9f4) to head (09fd471).
⚠️ Report is 1 commits behind head on main.

Additional details and impacted files 
@@            Coverage Diff             @@
##             main    #1801      +/-   ##
==========================================
+ Coverage   71.01%   71.06%   +0.04%     
==========================================
  Files         411      411              
  Lines       64803    64939     +136     
==========================================
+ Hits        46023    46152     +129     
- Misses      18780    18787       +7
Components Coverage Δ
libdd-crashtracker 65.27% <ø> (-0.02%) ⬇️
libdd-crashtracker-ffi 34.98% <ø> (ø)
libdd-alloc 98.77% <ø> (ø)
libdd-data-pipeline 87.63% <100.00%> (+0.02%) ⬆️
libdd-data-pipeline-ffi 73.45% <ø> (ø)
libdd-common 79.78% <ø> (ø)
libdd-common-ffi 73.87% <ø> (ø)
libdd-telemetry 62.48% <ø> (ø)
libdd-telemetry-ffi 16.75% <ø> (ø)
libdd-dogstatsd-client 82.64% <ø> (ø)
datadog-ipc 72.56% <ø> (ø)
libdd-profiling 81.60% <ø> (+0.01%) ⬆️
libdd-profiling-ffi 64.94% <ø> (ø)
datadog-sidecar 31.63% <ø> (ø)
datdog-sidecar-ffi 13.34% <ø> (ø)
spawn-worker 54.69% <ø> (ø)
libdd-tinybytes 93.16% <ø> (ø)
libdd-trace-normalization 81.71% <ø> (ø)
libdd-trace-obfuscation 87.37% <ø> (ø)
libdd-trace-protobuf 68.25% <ø> (ø)
libdd-trace-utils 88.95% <ø> (ø)
datadog-tracer-flare 86.88% <ø> (ø)
libdd-log 74.69% <ø> (ø)
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pr-commenter bot commented Mar 26, 2026 •
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Benchmarks

Comparison

Benchmark execution time: 2026-03-26 03:25:47

Comparing candidate commit 09fd471 in PR branch leo.romanovsky/fix-ffe-reason with baseline commit b1d5bcf in branch main.

Found 0 performance improvements and 0 performance regressions! Performance is the same for 62 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 09fd471 1774494556 leo.romanovsky/fix-ffe-reason
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
benching deserializing traces from msgpack to their internal representation execution_time 49.243ms 49.632ms ± 2.061ms 49.358ms ± 0.054ms 49.432ms 49.522ms 62.775ms 71.293ms 44.44% 8.618 76.699 4.14% 0.146ms 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
benching deserializing traces from msgpack to their internal representation execution_time [49.346ms; 49.918ms] or [-0.575%; +0.575%] None None None

Group 2

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz 09fd471 1774494556 leo.romanovsky/fix-ffe-reason
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 13.462ms 13.492ms ± 0.018ms 13.489ms ± 0.008ms 13.499ms 13.519ms 13.546ms 13.598ms 0.81% 2.440 11.190 0.13% 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 [13.490ms; 13.494ms] or [-0.018%; +0.018%] None None None

Group 3

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz 09fd471 1774494556 leo.romanovsky/fix-ffe-reason
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000... execution_time 495.852µs 496.670µs ± 0.681µs 496.623µs ± 0.266µs 496.874µs 497.416µs 497.744µs 504.351µs 1.56% 7.286 79.310 0.14% 0.048µs 1 200
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000... throughput 1982747.235op/s 2013412.355op/s ± 2731.790op/s 2013598.502op/s ± 1080.223op/s 2014685.772op/s 2016044.466op/s 2016522.130op/s 2016731.477op/s 0.16% -7.171 77.575 0.14% 193.167op/s 1 200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて execution_time 371.096µs 371.913µs ± 0.360µs 371.858µs ± 0.222µs 372.082µs 372.600µs 372.822µs 372.870µs 0.27% 0.548 -0.096 0.10% 0.025µs 1 200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて throughput 2681902.047op/s 2688802.943op/s ± 2604.249op/s 2689196.364op/s ± 1603.119op/s 2690753.906op/s 2692030.463op/s 2694204.763op/s 2694718.609op/s 0.21% -0.543 -0.101 0.10% 184.148op/s 1 200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters execution_time 168.060µs 168.424µs ± 0.541µs 168.329µs ± 0.090µs 168.423µs 168.772µs 170.168µs 172.935µs 2.74% 6.305 46.314 0.32% 0.038µs 1 200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters throughput 5782534.218op/s 5937452.736op/s ± 18693.871op/s 5940764.226op/s ± 3189.067op/s 5943820.666op/s 5947213.323op/s 5949261.486op/s 5950259.978op/s 0.16% -6.224 45.258 0.31% 1321.856op/s 1 200
normalization/normalize_service/normalize_service/[empty string] execution_time 37.269µs 37.394µs ± 0.056µs 37.387µs ± 0.033µs 37.419µs 37.505µs 37.544µs 37.555µs 0.45% 0.618 0.438 0.15% 0.004µs 1 200
normalization/normalize_service/normalize_service/[empty string] throughput 26627778.417op/s 26742565.599op/s ± 40147.793op/s 26747113.023op/s ± 23301.902op/s 26770537.428op/s 26797585.013op/s 26827555.452op/s 26831895.444op/s 0.32% -0.609 0.427 0.15% 2838.878op/s 1 200
normalization/normalize_service/normalize_service/test_ASCII execution_time 46.284µs 46.470µs ± 0.152µs 46.453µs ± 0.062µs 46.517µs 46.593µs 46.706µs 48.220µs 3.80% 7.858 86.288 0.33% 0.011µs 1 200
normalization/normalize_service/normalize_service/test_ASCII throughput 20738245.874op/s 21519546.896op/s ± 68725.868op/s 21527050.244op/s ± 28626.248op/s 21555054.652op/s 21577583.786op/s 21598197.552op/s 21605507.592op/s 0.36% -7.601 82.284 0.32% 4859.653op/s 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000... execution_time [496.576µs; 496.764µs] or [-0.019%; +0.019%] None None None
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000... throughput [2013033.755op/s; 2013790.955op/s] or [-0.019%; +0.019%] None None None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて execution_time [371.863µs; 371.963µs] or [-0.013%; +0.013%] None None None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて throughput [2688442.019op/s; 2689163.867op/s] or [-0.013%; +0.013%] None None None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters execution_time [168.349µs; 168.499µs] or [-0.045%; +0.045%] None None None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters throughput [5934861.945op/s; 5940043.527op/s] or [-0.044%; +0.044%] None None None
normalization/normalize_service/normalize_service/[empty string] execution_time [37.386µs; 37.401µs] or [-0.021%; +0.021%] None None None
normalization/normalize_service/normalize_service/[empty string] throughput [26737001.501op/s; 26748129.697op/s] or [-0.021%; +0.021%] None None None
normalization/normalize_service/normalize_service/test_ASCII execution_time [46.449µs; 46.491µs] or [-0.045%; +0.045%] None None None
normalization/normalize_service/normalize_service/test_ASCII throughput [21510022.152op/s; 21529071.640op/s] or [-0.044%; +0.044%] None None None

Group 4

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz 09fd471 1774494556 leo.romanovsky/fix-ffe-reason
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
profile_add_sample_timestamped_x1000 execution_time 4.164ms 4.172ms ± 0.009ms 4.171ms ± 0.002ms 4.173ms 4.176ms 4.179ms 4.289ms 2.81% 11.643 149.799 0.21% 0.001ms 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
profile_add_sample_timestamped_x1000 execution_time [4.171ms; 4.173ms] or [-0.029%; +0.029%] None None None

Group 5

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz 09fd471 1774494556 leo.romanovsky/fix-ffe-reason
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
profile_add_sample_frames_x1000 execution_time 4.195ms 4.199ms ± 0.003ms 4.198ms ± 0.001ms 4.200ms 4.202ms 4.204ms 4.221ms 0.55% 3.448 27.232 0.06% 0.000ms 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
profile_add_sample_frames_x1000 execution_time [4.198ms; 4.199ms] or [-0.009%; +0.009%] None None None

Group 6

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz 09fd471 1774494556 leo.romanovsky/fix-ffe-reason
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
sql/obfuscate_sql_string execution_time 286.844µs 287.557µs ± 0.542µs 287.443µs ± 0.159µs 287.654µs 288.206µs 289.377µs 292.072µs 1.61% 5.440 39.535 0.19% 0.038µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
sql/obfuscate_sql_string execution_time [287.481µs; 287.632µs] or [-0.026%; +0.026%] None None None

Group 7

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz 09fd471 1774494556 leo.romanovsky/fix-ffe-reason
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
ip_address/quantize_peer_ip_address_benchmark execution_time 5.020µs 5.116µs ± 0.045µs 5.133µs ± 0.033µs 5.143µs 5.174µs 5.179µs 5.181µs 0.94% -0.420 -1.220 0.87% 0.003µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
ip_address/quantize_peer_ip_address_benchmark execution_time [5.110µs; 5.122µs] or [-0.121%; +0.121%] None None None

Group 8

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz 09fd471 1774494556 leo.romanovsky/fix-ffe-reason
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... execution_time 185.807µs 186.312µs ± 0.246µs 186.288µs ± 0.162µs 186.456µs 186.660µs 186.961µs 187.668µs 0.74% 1.055 3.914 0.13% 0.017µs 1 200
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... throughput 5328568.882op/s 5367347.223op/s ± 7066.895op/s 5368020.048op/s ± 4666.402op/s 5372313.408op/s 5377448.308op/s 5379403.969op/s 5381927.112op/s 0.26% -1.036 3.809 0.13% 499.705op/s 1 200
normalization/normalize_name/normalize_name/bad-name execution_time 17.803µs 17.905µs ± 0.035µs 17.907µs ± 0.021µs 17.928µs 17.955µs 17.974µs 17.984µs 0.43% -0.472 0.376 0.19% 0.002µs 1 200
normalization/normalize_name/normalize_name/bad-name throughput 55605164.084op/s 55851075.335op/s ± 108083.769op/s 55845197.116op/s ± 65532.915op/s 55902460.076op/s 56033734.947op/s 56163884.898op/s 56168744.124op/s 0.58% 0.485 0.394 0.19% 7642.677op/s 1 200
normalization/normalize_name/normalize_name/good execution_time 10.558µs 10.621µs ± 0.028µs 10.618µs ± 0.020µs 10.642µs 10.664µs 10.682µs 10.730µs 1.06% 0.110 0.281 0.27% 0.002µs 1 200
normalization/normalize_name/normalize_name/good throughput 93195517.794op/s 94151502.591op/s ± 250699.970op/s 94180947.654op/s ± 177708.488op/s 94315154.094op/s 94630055.010op/s 94684386.049op/s 94712990.718op/s 0.56% -0.092 0.253 0.27% 17727.165op/s 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... execution_time [186.278µs; 186.346µs] or [-0.018%; +0.018%] None None None
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... throughput [5366367.820op/s; 5368326.627op/s] or [-0.018%; +0.018%] None None None
normalization/normalize_name/normalize_name/bad-name execution_time [17.900µs; 17.910µs] or [-0.027%; +0.027%] None None None
normalization/normalize_name/normalize_name/bad-name throughput [55836095.964op/s; 55866054.705op/s] or [-0.027%; +0.027%] None None None
normalization/normalize_name/normalize_name/good execution_time [10.617µs; 10.625µs] or [-0.037%; +0.037%] None None None
normalization/normalize_name/normalize_name/good throughput [94116757.986op/s; 94186247.195op/s] or [-0.037%; +0.037%] None None None

Group 9

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz 09fd471 1774494556 leo.romanovsky/fix-ffe-reason
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
benching string interning on wordpress profile execution_time 173.923µs 174.719µs ± 0.353µs 174.664µs ± 0.138µs 174.835µs 175.238µs 175.673µs 177.756µs 1.77% 3.661 27.140 0.20% 0.025µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
benching string interning on wordpress profile execution_time [174.670µs; 174.767µs] or [-0.028%; +0.028%] None None None

Group 10

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz 09fd471 1774494556 leo.romanovsky/fix-ffe-reason
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
profile_add_sample2_frames_x1000 execution_time 746.725µs 747.997µs ± 0.678µs 747.949µs ± 0.342µs 748.330µs 748.974µs 750.068µs 753.114µs 0.69% 2.660 16.300 0.09% 0.048µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
profile_add_sample2_frames_x1000 execution_time [747.903µs; 748.091µs] or [-0.013%; +0.013%] None None None

Group 11

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz 09fd471 1774494556 leo.romanovsky/fix-ffe-reason
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
sdk_test_data/rules-based execution_time 144.923µs 146.582µs ± 1.970µs 146.237µs ± 0.575µs 146.904µs 148.257µs 152.909µs 166.338µs 13.75% 6.582 56.743 1.34% 0.139µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
sdk_test_data/rules-based execution_time [146.309µs; 146.855µs] or [-0.186%; +0.186%] None None None

Group 12

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz 09fd471 1774494556 leo.romanovsky/fix-ffe-reason
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 8.614µs 8.743µs ± 0.030µs 8.750µs ± 0.009µs 8.758µs 8.770µs 8.780µs 8.881µs 1.50% -1.448 6.518 0.34% 0.002µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
write only interface execution_time [8.739µs; 8.748µs] or [-0.048%; +0.048%] None None None

Group 13

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz 09fd471 1774494556 leo.romanovsky/fix-ffe-reason
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
single_flag_killswitch/rules-based execution_time 189.210ns 191.553ns ± 1.875ns 191.303ns ± 1.483ns 192.714ns 194.847ns 195.916ns 201.273ns 5.21% 1.099 2.545 0.98% 0.133ns 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
single_flag_killswitch/rules-based execution_time [191.293ns; 191.813ns] or [-0.136%; +0.136%] None None None

Group 14

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz 09fd471 1774494556 leo.romanovsky/fix-ffe-reason
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
redis/obfuscate_redis_string execution_time 34.079µs 34.753µs ± 1.063µs 34.265µs ± 0.077µs 34.445µs 36.988µs 37.045µs 38.740µs 13.06% 1.736 1.320 3.05% 0.075µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
redis/obfuscate_redis_string execution_time [34.606µs; 34.901µs] or [-0.424%; +0.424%] None None None

Group 15

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz 09fd471 1774494556 leo.romanovsky/fix-ffe-reason
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
benching serializing traces from their internal representation to msgpack execution_time 13.964ms 14.067ms ± 0.033ms 14.066ms ± 0.021ms 14.085ms 14.122ms 14.161ms 14.197ms 0.94% 0.610 1.497 0.24% 0.002ms 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
benching serializing traces from their internal representation to msgpack execution_time [14.062ms; 14.071ms] or [-0.033%; +0.033%] None None None

Group 16

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz 09fd471 1774494556 leo.romanovsky/fix-ffe-reason
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
normalization/normalize_trace/test_trace execution_time 242.868ns 254.710ns ± 12.732ns 250.140ns ± 5.004ns 257.277ns 287.705ns 291.625ns 296.205ns 18.42% 1.667 1.853 4.99% 0.900ns 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
normalization/normalize_trace/test_trace execution_time [252.945ns; 256.474ns] or [-0.693%; +0.693%] None None None

Group 17

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz 09fd471 1774494556 leo.romanovsky/fix-ffe-reason
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
receiver_entry_point/report/2598 execution_time 4.793ms 4.825ms ± 0.022ms 4.820ms ± 0.010ms 4.833ms 4.876ms 4.899ms 4.919ms 2.06% 1.586 2.667 0.46% 0.002ms 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
receiver_entry_point/report/2598 execution_time [4.822ms; 4.828ms] or [-0.064%; +0.064%] None None None

Group 18

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz 09fd471 1774494556 leo.romanovsky/fix-ffe-reason
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
profile_serialize_compressed_pprof_timestamped_x1000 execution_time 913.996µs 916.441µs ± 2.945µs 916.151µs ± 0.733µs 916.912µs 918.304µs 919.031µs 954.775µs 4.22% 11.119 142.115 0.32% 0.208µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
profile_serialize_compressed_pprof_timestamped_x1000 execution_time [916.033µs; 916.849µs] or [-0.045%; +0.045%] None None None

Group 19

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz 09fd471 1774494556 leo.romanovsky/fix-ffe-reason
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
tags/replace_trace_tags execution_time 2.306µs 2.371µs ± 0.016µs 2.373µs ± 0.005µs 2.379µs 2.390µs 2.401µs 2.415µs 1.78% -1.864 5.490 0.68% 0.001µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
tags/replace_trace_tags execution_time [2.369µs; 2.374µs] or [-0.095%; +0.095%] None None None

Group 20

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz 09fd471 1774494556 leo.romanovsky/fix-ffe-reason
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
credit_card/is_card_number/ execution_time 3.905µs 3.920µs ± 0.005µs 3.920µs ± 0.002µs 3.922µs 3.924µs 3.927µs 3.966µs 1.18% 5.623 45.561 0.14% 0.000µs 1 200
credit_card/is_card_number/ throughput 252125687.173op/s 255119986.934op/s ± 353167.365op/s 255103366.327op/s ± 142260.628op/s 255322098.130op/s 255418846.403op/s 255502723.783op/s 256074214.781op/s 0.38% -5.556 44.883 0.14% 24972.704op/s 1 200
credit_card/is_card_number/ 3782-8224-6310-005 execution_time 79.591µs 80.103µs ± 0.140µs 80.093µs ± 0.096µs 80.202µs 80.301µs 80.355µs 80.835µs 0.93% 0.328 3.509 0.17% 0.010µs 1 200
credit_card/is_card_number/ 3782-8224-6310-005 throughput 12370953.634op/s 12483894.036op/s ± 21802.992op/s 12485478.140op/s ± 14897.483op/s 12497505.859op/s 12513198.734op/s 12539302.083op/s 12564272.536op/s 0.63% -0.300 3.427 0.17% 1541.704op/s 1 200
credit_card/is_card_number/ 378282246310005 execution_time 68.264µs 68.349µs ± 0.068µs 68.342µs ± 0.028µs 68.371µs 68.426µs 68.451µs 69.113µs 1.13% 7.182 77.709 0.10% 0.005µs 1 200
credit_card/is_card_number/ 378282246310005 throughput 14469151.916op/s 14630731.618op/s ± 14448.094op/s 14632247.572op/s ± 5910.404op/s 14637907.825op/s 14644934.461op/s 14648752.628op/s 14648910.460op/s 0.11% -7.098 76.460 0.10% 1021.635op/s 1 200
credit_card/is_card_number/37828224631 execution_time 3.898µs 3.918µs ± 0.003µs 3.918µs ± 0.002µs 3.920µs 3.922µs 3.923µs 3.925µs 0.18% -1.841 14.215 0.07% 0.000µs 1 200
credit_card/is_card_number/37828224631 throughput 254789351.182op/s 255242788.763op/s ± 171284.091op/s 255250711.091op/s ± 108140.404op/s 255348707.773op/s 255444936.911op/s 255527660.932op/s 256529932.763op/s 0.50% 1.867 14.442 0.07% 12111.614op/s 1 200
credit_card/is_card_number/378282246310005 execution_time 64.877µs 65.030µs ± 0.081µs 65.030µs ± 0.067µs 65.097µs 65.151µs 65.197µs 65.214µs 0.28% 0.047 -0.913 0.12% 0.006µs 1 200
credit_card/is_card_number/378282246310005 throughput 15334145.977op/s 15377478.525op/s ± 19185.841op/s 15377432.850op/s ± 15878.758op/s 15393238.521op/s 15409684.447op/s 15411582.129op/s 15413684.269op/s 0.24% -0.043 -0.914 0.12% 1356.644op/s 1 200
credit_card/is_card_number/37828224631000521389798 execution_time 45.394µs 45.611µs ± 0.180µs 45.529µs ± 0.117µs 45.810µs 45.882µs 45.917µs 45.921µs 0.86% 0.310 -1.567 0.39% 0.013µs 1 200
credit_card/is_card_number/37828224631000521389798 throughput 21776307.239op/s 21925051.389op/s ± 86547.324op/s 21964239.094op/s ± 56397.546op/s 22008096.229op/s 22021102.713op/s 22026343.706op/s 22029243.821op/s 0.30% -0.306 -1.571 0.39% 6119.820op/s 1 200
credit_card/is_card_number/x371413321323331 execution_time 6.800µs 6.841µs ± 0.009µs 6.843µs ± 0.004µs 6.847µs 6.851µs 6.854µs 6.855µs 0.17% -1.781 3.822 0.14% 0.001µs 1 200
credit_card/is_card_number/x371413321323331 throughput 145877363.036op/s 146176712.047op/s ± 198317.498op/s 146128433.628op/s ± 87384.705op/s 146224159.892op/s 146599089.653op/s 146926628.351op/s 147061249.502op/s 0.64% 1.792 3.873 0.14% 14023.165op/s 1 200
credit_card/is_card_number_no_luhn/ execution_time 3.900µs 3.918µs ± 0.002µs 3.918µs ± 0.001µs 3.919µs 3.921µs 3.922µs 3.924µs 0.16% -2.047 17.236 0.06% 0.000µs 1 200
credit_card/is_card_number_no_luhn/ throughput 254848484.939op/s 255251906.305op/s ± 149593.373op/s 255253339.690op/s ± 81576.361op/s 255336691.883op/s 255438570.368op/s 255510988.455op/s 256421278.969op/s 0.46% 2.074 17.472 0.06% 10577.849op/s 1 200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 execution_time 65.005µs 65.727µs ± 0.231µs 65.817µs ± 0.074µs 65.876µs 65.922µs 65.952µs 66.002µs 0.28% -1.651 1.769 0.35% 0.016µs 1 200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 throughput 15151110.397op/s 15214695.372op/s ± 53686.249op/s 15193571.600op/s ± 17152.719op/s 15229252.348op/s 15357222.095op/s 15366208.868op/s 15383374.438op/s 1.25% 1.662 1.805 0.35% 3796.191op/s 1 200
credit_card/is_card_number_no_luhn/ 378282246310005 execution_time 53.419µs 53.474µs ± 0.029µs 53.472µs ± 0.018µs 53.488µs 53.526µs 53.562µs 53.569µs 0.18% 0.741 0.649 0.05% 0.002µs 1 200
credit_card/is_card_number_no_luhn/ 378282246310005 throughput 18667570.696op/s 18700701.851op/s ± 10010.874op/s 18701547.554op/s ± 6154.407op/s 18707725.355op/s 18714790.487op/s 18717849.118op/s 18719773.697op/s 0.10% -0.738 0.641 0.05% 707.876op/s 1 200
credit_card/is_card_number_no_luhn/37828224631 execution_time 3.899µs 3.918µs ± 0.003µs 3.917µs ± 0.002µs 3.919µs 3.922µs 3.924µs 3.925µs 0.19% -1.150 10.357 0.07% 0.000µs 1 200
credit_card/is_card_number_no_luhn/37828224631 throughput 254781187.452op/s 255256892.292op/s ± 172651.520op/s 255273103.740op/s ± 99276.972op/s 255358114.892op/s 255474815.800op/s 255518596.168op/s 256450961.686op/s 0.46% 1.173 10.517 0.07% 12208.306op/s 1 200
credit_card/is_card_number_no_luhn/378282246310005 execution_time 50.197µs 50.264µs ± 0.037µs 50.259µs ± 0.025µs 50.285µs 50.333µs 50.373µs 50.383µs 0.25% 0.812 0.382 0.07% 0.003µs 1 200
credit_card/is_card_number_no_luhn/378282246310005 throughput 19848025.959op/s 19894933.677op/s ± 14651.338op/s 19896881.164op/s ± 9747.743op/s 19906376.510op/s 19913998.147op/s 19918916.020op/s 19921345.722op/s 0.12% -0.808 0.373 0.07% 1036.006op/s 1 200
credit_card/is_card_number_no_luhn/37828224631000521389798 execution_time 45.390µs 45.684µs ± 0.155µs 45.714µs ± 0.100µs 45.811µs 45.872µs 45.914µs 45.917µs 0.44% -0.590 -0.903 0.34% 0.011µs 1 200
credit_card/is_card_number_no_luhn/37828224631000521389798 throughput 21778324.501op/s 21889858.813op/s ± 74216.180op/s 21875144.393op/s ± 47752.119op/s 21924760.251op/s 22019837.130op/s 22025377.436op/s 22031315.453op/s 0.71% 0.597 -0.897 0.34% 5247.876op/s 1 200
credit_card/is_card_number_no_luhn/x371413321323331 execution_time 6.820µs 6.843µs ± 0.006µs 6.844µs ± 0.003µs 6.847µs 6.852µs 6.854µs 6.855µs 0.16% -1.047 1.436 0.09% 0.000µs 1 200
credit_card/is_card_number_no_luhn/x371413321323331 throughput 145875410.218op/s 146129688.226op/s ± 132495.364op/s 146110125.447op/s ± 70481.070op/s 146179221.829op/s 146403776.135op/s 146529815.774op/s 146627727.855op/s 0.35% 1.053 1.453 0.09% 9368.837op/s 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
credit_card/is_card_number/ execution_time [3.919µs; 3.920µs] or [-0.019%; +0.019%] None None None
credit_card/is_card_number/ throughput [255071041.333op/s; 255168932.534op/s] or [-0.019%; +0.019%] None None None
credit_card/is_card_number/ 3782-8224-6310-005 execution_time [80.084µs; 80.123µs] or [-0.024%; +0.024%] None None None
credit_card/is_card_number/ 3782-8224-6310-005 throughput [12480872.351op/s; 12486915.721op/s] or [-0.024%; +0.024%] None None None
credit_card/is_card_number/ 378282246310005 execution_time [68.340µs; 68.359µs] or [-0.014%; +0.014%] None None None
credit_card/is_card_number/ 378282246310005 throughput [14628729.251op/s; 14632733.984op/s] or [-0.014%; +0.014%] None None None
credit_card/is_card_number/37828224631 execution_time [3.917µs; 3.918µs] or [-0.009%; +0.009%] None None None
credit_card/is_card_number/37828224631 throughput [255219050.435op/s; 255266527.091op/s] or [-0.009%; +0.009%] None None None
credit_card/is_card_number/378282246310005 execution_time [65.019µs; 65.042µs] or [-0.017%; +0.017%] None None None
credit_card/is_card_number/378282246310005 throughput [15374819.552op/s; 15380137.498op/s] or [-0.017%; +0.017%] None None None
credit_card/is_card_number/37828224631000521389798 execution_time [45.586µs; 45.636µs] or [-0.055%; +0.055%] None None None
credit_card/is_card_number/37828224631000521389798 throughput [21913056.762op/s; 21937046.015op/s] or [-0.055%; +0.055%] None None None
credit_card/is_card_number/x371413321323331 execution_time [6.840µs; 6.842µs] or [-0.019%; +0.019%] None None None
credit_card/is_card_number/x371413321323331 throughput [146149227.149op/s; 146204196.945op/s] or [-0.019%; +0.019%] None None None
credit_card/is_card_number_no_luhn/ execution_time [3.917µs; 3.918µs] or [-0.008%; +0.008%] None None None
credit_card/is_card_number_no_luhn/ throughput [255231174.102op/s; 255272638.507op/s] or [-0.008%; +0.008%] None None None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 execution_time [65.695µs; 65.759µs] or [-0.049%; +0.049%] None None None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 throughput [15207254.974op/s; 15222135.769op/s] or [-0.049%; +0.049%] None None None
credit_card/is_card_number_no_luhn/ 378282246310005 execution_time [53.470µs; 53.478µs] or [-0.007%; +0.007%] None None None
credit_card/is_card_number_no_luhn/ 378282246310005 throughput [18699314.440op/s; 18702089.262op/s] or [-0.007%; +0.007%] None None None
credit_card/is_card_number_no_luhn/37828224631 execution_time [3.917µs; 3.918µs] or [-0.009%; +0.009%] None None None
credit_card/is_card_number_no_luhn/37828224631 throughput [255232964.452op/s; 255280820.132op/s] or [-0.009%; +0.009%] None None None
credit_card/is_card_number_no_luhn/378282246310005 execution_time [50.259µs; 50.269µs] or [-0.010%; +0.010%] None None None
credit_card/is_card_number_no_luhn/378282246310005 throughput [19892903.143op/s; 19896964.212op/s] or [-0.010%; +0.010%] None None None
credit_card/is_card_number_no_luhn/37828224631000521389798 execution_time [45.662µs; 45.705µs] or [-0.047%; +0.047%] None None None
credit_card/is_card_number_no_luhn/37828224631000521389798 throughput [21879573.164op/s; 21900144.461op/s] or [-0.047%; +0.047%] None None None
credit_card/is_card_number_no_luhn/x371413321323331 execution_time [6.842µs; 6.844µs] or [-0.013%; +0.013%] None None None
credit_card/is_card_number_no_luhn/x371413321323331 throughput [146111325.643op/s; 146148050.809op/s] or [-0.013%; +0.013%] None None None

Group 21

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz 09fd471 1774494556 leo.romanovsky/fix-ffe-reason
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 19.702µs 19.844µs ± 0.043µs 19.836µs ± 0.021µs 19.864µs 19.924µs 19.969µs 20.022µs 0.94% 0.917 2.387 0.22% 0.003µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
two way interface execution_time [19.838µs; 19.850µs] or [-0.030%; +0.030%] None None None

Baseline

Omitted due to size.

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dd-octo-sts bot commented Mar 26, 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 101.44 MB 101.44 MB -0% (-248 B) 👌
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.so 8.70 MB 8.70 MB 0% (0 B) 👌
aarch64-unknown-linux-gnu
Artifact Baseline Commit Change
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.a 118.22 MB 118.22 MB -0% (-264 B) 👌
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.so 11.29 MB 11.29 MB 0% (0 B) 👌
libdatadog-x64-windows
Artifact Baseline Commit Change
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.dll 27.26 MB 27.26 MB 0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.lib 80.34 KB 80.34 KB 0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.pdb 186.53 MB 186.54 MB +0% (+8.00 KB) 👌
/libdatadog-x64-windows/debug/static/datadog_profiling_ffi.lib 921.92 MB 921.92 MB -0% (-106 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.dll 8.99 MB 8.99 MB 0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.lib 80.34 KB 80.34 KB 0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.pdb 26.83 MB 26.83 MB 0% (0 B) 👌
/libdatadog-x64-windows/release/static/datadog_profiling_ffi.lib 61.00 MB 61.00 MB -0% (-102 B) 👌
libdatadog-x86-windows
Artifact Baseline Commit Change
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.dll 23.08 MB 23.08 MB 0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.lib 81.59 KB 81.59 KB 0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.pdb 190.75 MB 190.76 MB +0% (+16.00 KB) 👌
/libdatadog-x86-windows/debug/static/datadog_profiling_ffi.lib 905.45 MB 905.45 MB -0% (-110 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.dll 6.86 MB 6.86 MB 0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.lib 81.59 KB 81.59 KB 0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.pdb 28.94 MB 28.94 MB 0% (0 B) 👌
/libdatadog-x86-windows/release/static/datadog_profiling_ffi.lib 57.39 MB 57.39 MB -0% (-116 B) 👌
x86_64-alpine-linux-musl
Artifact Baseline Commit Change
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.a 88.30 MB 88.30 MB -0% (-192 B) 👌
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.so 10.28 MB 10.28 MB 0% (0 B) 👌
x86_64-unknown-linux-gnu
Artifact Baseline Commit Change
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.a 110.97 MB 110.97 MB +0% (+240 B) 👌
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.so 12.02 MB 12.02 MB 0% (0 B) 👌

@leoromanovsky
refactor(09-08): use ffe-system-test-data submodule for UFC fixtures
c7d5789 
- Add ffe-system-test-data as git submodule at datadog-ffe/ffe-system-test-data
- Update models.rs, eval_assignment.rs, and benches/eval.rs to read from submodule
- Delete old local fixtures at datadog-ffe/tests/data/
- Add known_reason_overrides for Rust shard optimization discrepancy (empty_string_flag/bob)
- Add .github/dependabot.yml for git submodule auto-updates
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@leoromanovsky @codecov-commenter