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feat(crashtracking): emit ucontext registers as structured data#1787

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feat(crashtracking): emit ucontext registers as structured data#1787
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gyuheon0h/PROF-14095-emit-ucontxt-structured

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@gyuheon0h gyuheon0h commented Mar 25, 2026 •
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What does this PR do?

This PR extracts out register data from ucontext and emits ucontext as structured data. The reason we do this is because ucontext register and pointer values are needed as structured data for downstream diagnosis workflows.

Motivation

RFC: Crashtracker Crash Pre-Diagnosis

Additional Notes

Schema

{
  "$schema": "http://json-schema.org/draft-07/schema#",
  "type": "object",
  "title": "UContext Schema",
  "description": "JSON schema for crashtracker ucontext data",
  "required": ["arch", "os", "registers", "raw"],
  "properties": {
    "arch": {
      "type": "string",
      "enum": ["x86_64", "aarch64"],
      "description": "Target architecture"
    },
    "os": {
      "type": "string", 
      "enum": ["linux", "macos"],
      "description": "Operating system"
    },
    "registers": {
      "type": "object",
      "description": "CPU register values as key-value pairs with hex string values",
      "additionalProperties": {
        "type": "string",
        "pattern": "^0x[0-9a-f]+$"
      }
    },
    "raw": {
      "type": "string",
      "description": "Debug representation of the complete ucontext structure"
    }
  },
  "additionalProperties": false
}

How to test the change?

Unit test

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gyuheon0h commented Mar 25, 2026

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@gyuheon0h gyuheon0h changed the title emit ucontext registers as structured data feat(crashtracking): emit ucontext registers as structured data Mar 25, 2026
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github-actions bot commented Mar 25, 2026 •
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📚 Documentation Check Results

⚠️ 1049 documentation warning(s) found

📦 libdd-crashtracker - 1049 warning(s)

Updated: 2026-03-27 21:58:29 UTC | Commit: 68b84bf | missing-docs job results

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github-actions bot commented Mar 25, 2026

Clippy Allow Annotation Report

Comparing clippy allow annotations between branches:

  • Base Branch: origin/main
  • PR Branch: origin/gyuheon0h/PROF-14095-emit-ucontxt-structured

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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🔒 Cargo Deny Results

⚠️ 1 issue(s) found, showing only errors (advisories, bans, sources)

📦 libdd-crashtracker - 1 error(s)

Show output 
error[unmaintained]: paste - no longer maintained
    ┌─ /home/runner/work/libdatadog/libdatadog/Cargo.lock:131:1
    │
131 │ paste 1.0.15 registry+https://github.com/rust-lang/crates.io-index
    │ ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ unmaintained advisory detected
    │
    ├ ID: RUSTSEC-2024-0436
    ├ Advisory: https://rustsec.org/advisories/RUSTSEC-2024-0436
    ├ The creator of the crate `paste` has stated in the [`README.md`](https://github.com/dtolnay/paste/blob/master/README.md) 
      that this project is not longer maintained as well as archived the repository
      
      ## Possible Alternative(s)
      
      - [`pastey`]: a fork of paste and is aimed to be a drop-in replacement with additional features for paste crate
      - [`with_builtin_macros`]: crate providing a [superset of `paste`'s functionality including general `macro_rules!` eager expansions](https://docs.rs/with_builtin_macros/0.1.0/with_builtin_macros/macro.with_eager_expansions.html)  and `concat!`/`concat_idents!` macros
      
      [`pastey`]: https://crates.io/crates/pastey
      [`with_builtin_macros`]: https://crates.io/crates/with_builtin_macros
    ├ Announcement: https://github.com/dtolnay/paste
    ├ Solution: No safe upgrade is available!
    ├ paste v1.0.15
      └── libdd-libunwind-sys v0.1.0
          └── libdd-crashtracker v1.0.0

advisories FAILED, bans ok, sources ok

Updated: 2026-03-27 22:01:11 UTC | Commit: 68b84bf | dependency-check job results

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datadog-official bot commented Mar 25, 2026 •
edited by datadog-datadog-prod-us1-2 bot
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✅ Tests

🎉 All green!

❄️ No new flaky tests detected
🧪 All tests passed

🎯 Code Coverage (details)
• Patch Coverage: 93.06%
• Overall Coverage: 71.48% (+0.21%)

This comment will be updated automatically if new data arrives.
🔗 Commit SHA: 3fef267 | Docs | Datadog PR Page | Was this helpful? React with 👍/👎 or give us feedback!

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Benchmarks

Comparison

Benchmark execution time: 2026-03-27 22:14:26

Comparing candidate commit 3fef267 in PR branch gyuheon0h/PROF-14095-emit-ucontxt-structured with baseline commit d75fe5e in branch main.

Found 0 performance improvements and 4 performance regressions! Performance is the same for 58 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:credit_card/is_card_number/x371413321323331

  • 🟥 execution_time [+941.418ns; +959.178ns] or [+16.069%; +16.372%]
  • 🟥 throughput [-24101230.388op/s; -23585496.681op/s] or [-14.118%; -13.816%]

scenario:credit_card/is_card_number_no_luhn/x371413321323331

  • 🟥 execution_time [+972.777ns; +989.997ns] or [+16.686%; +16.981%]
  • 🟥 throughput [-24985196.853op/s; -24480772.268op/s] or [-14.565%; -14.271%]

Candidate

Candidate benchmark details

Group 1

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3fef267 1774634347 gyuheon0h/PROF-14095-emit-ucontxt-structured
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 4.999µs 5.080µs ± 0.050µs 5.066µs ± 0.028µs 5.122µs 5.169µs 5.175µs 5.178µs 2.20% 0.452 -1.008 0.98% 0.004µs 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 [5.073µs; 5.087µs] or [-0.137%; +0.137%] None None None

Group 2

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3fef267 1774634347 gyuheon0h/PROF-14095-emit-ucontxt-structured
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 2.335µs 2.400µs ± 0.017µs 2.400µs ± 0.003µs 2.405µs 2.427µs 2.434µs 2.437µs 1.53% -1.748 5.202 0.69% 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 [2.398µs; 2.402µs] or [-0.096%; +0.096%] None None None

Group 3

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3fef267 1774634347 gyuheon0h/PROF-14095-emit-ucontxt-structured
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 14.784ms 14.832ms ± 0.021ms 14.831ms ± 0.014ms 14.845ms 14.869ms 14.883ms 14.906ms 0.51% 0.492 0.461 0.14% 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 [14.829ms; 14.835ms] or [-0.019%; +0.019%] None None None

Group 4

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3fef267 1774634347 gyuheon0h/PROF-14095-emit-ucontxt-structured
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 190.812ns 192.962ns ± 2.022ns 192.615ns ± 1.382ns 194.141ns 197.099ns 198.846ns 201.320ns 4.52% 1.233 1.398 1.05% 0.143ns 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 [192.682ns; 193.243ns] or [-0.145%; +0.145%] None None None

Group 5

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3fef267 1774634347 gyuheon0h/PROF-14095-emit-ucontxt-structured
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 289.079µs 289.700µs ± 0.496µs 289.636µs ± 0.198µs 289.843µs 290.172µs 291.212µs 293.901µs 1.47% 5.231 38.872 0.17% 0.035µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
sql/obfuscate_sql_string execution_time [289.632µs; 289.769µs] or [-0.024%; +0.024%] None None None

Group 6

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3fef267 1774634347 gyuheon0h/PROF-14095-emit-ucontxt-structured
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 185.618µs 186.089µs ± 0.309µs 186.052µs ± 0.161µs 186.219µs 186.564µs 186.853µs 188.260µs 1.19% 2.930 16.572 0.17% 0.022µs 1 200
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... throughput 5311797.888op/s 5373775.976op/s ± 8867.434op/s 5374838.917op/s ± 4634.476op/s 5379181.170op/s 5384576.990op/s 5386895.581op/s 5387408.549op/s 0.23% -2.881 16.151 0.16% 627.022op/s 1 200
normalization/normalize_name/normalize_name/bad-name execution_time 17.762µs 17.853µs ± 0.032µs 17.856µs ± 0.021µs 17.875µs 17.897µs 17.914µs 17.932µs 0.43% -0.364 -0.100 0.18% 0.002µs 1 200
normalization/normalize_name/normalize_name/bad-name throughput 55764790.674op/s 56013867.174op/s ± 99714.535op/s 56003636.942op/s ± 66207.859op/s 56076501.543op/s 56172784.962op/s 56265650.065op/s 56301298.052op/s 0.53% 0.373 -0.089 0.18% 7050.882op/s 1 200
normalization/normalize_name/normalize_name/good execution_time 10.550µs 10.603µs ± 0.025µs 10.597µs ± 0.015µs 10.621µs 10.644µs 10.676µs 10.712µs 1.09% 0.927 1.723 0.24% 0.002µs 1 200
normalization/normalize_name/normalize_name/good throughput 93352583.444op/s 94316080.529op/s ± 226012.149op/s 94367995.564op/s ± 133949.304op/s 94465613.080op/s 94626596.228op/s 94734446.408op/s 94788650.253op/s 0.45% -0.906 1.653 0.24% 15981.472op/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 [186.047µs; 186.132µs] or [-0.023%; +0.023%] None None None
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo... throughput [5372547.035op/s; 5375004.917op/s] or [-0.023%; +0.023%] None None None
normalization/normalize_name/normalize_name/bad-name execution_time [17.848µs; 17.857µs] or [-0.025%; +0.025%] None None None
normalization/normalize_name/normalize_name/bad-name throughput [56000047.699op/s; 56027686.650op/s] or [-0.025%; +0.025%] None None None
normalization/normalize_name/normalize_name/good execution_time [10.599µs; 10.606µs] or [-0.033%; +0.033%] None None None
normalization/normalize_name/normalize_name/good throughput [94284757.419op/s; 94347403.640op/s] or [-0.033%; +0.033%] None None None

Group 7

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3fef267 1774634347 gyuheon0h/PROF-14095-emit-ucontxt-structured
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 242.164ns 253.746ns ± 12.965ns 248.518ns ± 4.164ns 255.686ns 284.006ns 290.497ns 301.940ns 21.50% 1.668 1.849 5.10% 0.917ns 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 [251.950ns; 255.543ns] or [-0.708%; +0.708%] None None None

Group 8

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3fef267 1774634347 gyuheon0h/PROF-14095-emit-ucontxt-structured
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 3.366ms 3.393ms ± 0.021ms 3.391ms ± 0.007ms 3.398ms 3.418ms 3.461ms 3.600ms 6.18% 5.769 50.701 0.61% 0.001ms 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 [3.390ms; 3.396ms] or [-0.084%; +0.084%] None None None

Group 9

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3fef267 1774634347 gyuheon0h/PROF-14095-emit-ucontxt-structured
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 4.293ms 4.297ms ± 0.002ms 4.297ms ± 0.001ms 4.299ms 4.301ms 4.304ms 4.310ms 0.29% 1.271 3.487 0.05% 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 [4.297ms; 4.298ms] or [-0.007%; +0.007%] None None None

Group 10

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3fef267 1774634347 gyuheon0h/PROF-14095-emit-ucontxt-structured
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 3.892µs 3.911µs ± 0.003µs 3.911µs ± 0.001µs 3.913µs 3.916µs 3.917µs 3.918µs 0.17% -1.797 16.391 0.06% 0.000µs 1 200
credit_card/is_card_number/ throughput 255247318.880op/s 255670882.692op/s ± 164726.482op/s 255689849.115op/s ± 79323.658op/s 255762015.895op/s 255861675.155op/s 255895587.652op/s 256945440.243op/s 0.49% 1.826 16.647 0.06% 11647.921op/s 1 200
credit_card/is_card_number/ 3782-8224-6310-005 execution_time 79.020µs 79.625µs ± 0.323µs 79.554µs ± 0.200µs 79.837µs 80.200µs 80.571µs 80.831µs 1.61% 0.825 0.915 0.40% 0.023µs 1 200
credit_card/is_card_number/ 3782-8224-6310-005 throughput 12371477.774op/s 12559073.125op/s ± 50818.325op/s 12570145.907op/s ± 31678.232op/s 12596277.170op/s 12631598.517op/s 12649784.043op/s 12654960.493op/s 0.67% -0.798 0.840 0.40% 3593.398op/s 1 200
credit_card/is_card_number/ 378282246310005 execution_time 72.296µs 72.901µs ± 0.360µs 72.845µs ± 0.203µs 73.055µs 73.601µs 73.981µs 74.382µs 2.11% 1.085 1.547 0.49% 0.025µs 1 200
credit_card/is_card_number/ 378282246310005 throughput 13444027.690op/s 13717655.995op/s ± 67430.409op/s 13727701.723op/s ± 38303.209op/s 13764035.607op/s 13808752.500op/s 13824494.932op/s 13832094.609op/s 0.76% -1.051 1.433 0.49% 4768.050op/s 1 200
credit_card/is_card_number/37828224631 execution_time 3.891µs 3.913µs ± 0.003µs 3.913µs ± 0.002µs 3.915µs 3.918µs 3.920µs 3.927µs 0.36% -0.837 8.669 0.09% 0.000µs 1 200
credit_card/is_card_number/37828224631 throughput 254620130.564op/s 255542482.002op/s ± 224404.769op/s 255549481.369op/s ± 148335.700op/s 255699859.383op/s 255824526.430op/s 255890807.580op/s 257006647.497op/s 0.57% 0.863 8.813 0.09% 15867.813op/s 1 200
credit_card/is_card_number/378282246310005 execution_time 69.165µs 69.601µs ± 0.254µs 69.539µs ± 0.153µs 69.740µs 70.073µs 70.310µs 70.830µs 1.86% 1.215 2.267 0.36% 0.018µs 1 200
credit_card/is_card_number/378282246310005 throughput 14118372.356op/s 14367818.781op/s ± 52286.979op/s 14380316.942op/s ± 31606.763op/s 14407910.666op/s 14431012.824op/s 14443477.889op/s 14458075.196op/s 0.54% -1.185 2.123 0.36% 3697.248op/s 1 200
credit_card/is_card_number/37828224631000521389798 execution_time 52.232µs 52.311µs ± 0.035µs 52.310µs ± 0.026µs 52.337µs 52.365µs 52.385µs 52.412µs 0.20% 0.141 -0.551 0.07% 0.002µs 1 200
credit_card/is_card_number/37828224631000521389798 throughput 19079450.309op/s 19116358.304op/s ± 12647.153op/s 19116766.560op/s ± 9440.892op/s 19125280.875op/s 19135304.588op/s 19140205.140op/s 19145229.328op/s 0.15% -0.138 -0.553 0.07% 894.289op/s 1 200
credit_card/is_card_number/x371413321323331 execution_time 6.799µs 6.809µs ± 0.005µs 6.808µs ± 0.003µs 6.812µs 6.817µs 6.821µs 6.822µs 0.21% 0.552 -0.067 0.07% 0.000µs 1 200
credit_card/is_card_number/x371413321323331 throughput 146582237.886op/s 146868589.704op/s ± 98706.807op/s 146885600.795op/s ± 67420.504op/s 146941473.172op/s 147007933.418op/s 147034710.079op/s 147087408.087op/s 0.14% -0.548 -0.071 0.07% 6979.625op/s 1 200
credit_card/is_card_number_no_luhn/ execution_time 3.898µs 3.912µs ± 0.003µs 3.912µs ± 0.002µs 3.914µs 3.918µs 3.920µs 3.925µs 0.33% 0.301 2.422 0.08% 0.000µs 1 200
credit_card/is_card_number_no_luhn/ throughput 254802392.072op/s 255612392.685op/s ± 203187.425op/s 255647576.018op/s ± 137638.056op/s 255760150.612op/s 255858383.708op/s 255902737.804op/s 256557369.480op/s 0.36% -0.291 2.438 0.08% 14367.521op/s 1 200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 execution_time 64.092µs 64.487µs ± 0.172µs 64.464µs ± 0.120µs 64.607µs 64.810µs 64.997µs 65.145µs 1.06% 0.652 0.756 0.27% 0.012µs 1 200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 throughput 15350274.066op/s 15507058.713op/s ± 41307.931op/s 15512472.426op/s ± 28944.861op/s 15538230.485op/s 15562949.489op/s 15580908.257op/s 15602496.399op/s 0.58% -0.633 0.710 0.27% 2920.912op/s 1 200
credit_card/is_card_number_no_luhn/ 378282246310005 execution_time 57.747µs 58.109µs ± 0.185µs 58.088µs ± 0.124µs 58.199µs 58.484µs 58.562µs 58.712µs 1.07% 0.738 0.262 0.32% 0.013µs 1 200
credit_card/is_card_number_no_luhn/ 378282246310005 throughput 17032385.456op/s 17209153.568op/s ± 54572.992op/s 17215299.009op/s ± 36705.918op/s 17252866.909op/s 17281175.703op/s 17298257.550op/s 17317005.299op/s 0.59% -0.721 0.230 0.32% 3858.893op/s 1 200
credit_card/is_card_number_no_luhn/37828224631 execution_time 3.893µs 3.913µs ± 0.003µs 3.913µs ± 0.002µs 3.914µs 3.917µs 3.919µs 3.922µs 0.22% -1.331 10.420 0.07% 0.000µs 1 200
credit_card/is_card_number_no_luhn/37828224631 throughput 255000431.815op/s 255585054.402op/s ± 184600.123op/s 255571869.057op/s ± 110041.449op/s 255704724.145op/s 255816498.843op/s 255988054.157op/s 256861605.237op/s 0.50% 1.354 10.585 0.07% 13053.200op/s 1 200
credit_card/is_card_number_no_luhn/378282246310005 execution_time 54.591µs 54.827µs ± 0.200µs 54.748µs ± 0.094µs 54.940µs 55.246µs 55.388µs 55.712µs 1.76% 1.482 2.484 0.36% 0.014µs 1 200
credit_card/is_card_number_no_luhn/378282246310005 throughput 17949405.041op/s 18239458.969op/s ± 66118.572op/s 18265483.719op/s ± 31292.389op/s 18287626.137op/s 18304898.043op/s 18315836.003op/s 18318035.938op/s 0.29% -1.457 2.361 0.36% 4675.289op/s 1 200
credit_card/is_card_number_no_luhn/37828224631000521389798 execution_time 52.138µs 52.217µs ± 0.044µs 52.207µs ± 0.026µs 52.237µs 52.305µs 52.329µs 52.331µs 0.24% 0.784 -0.016 0.08% 0.003µs 1 200
credit_card/is_card_number_no_luhn/37828224631000521389798 throughput 19108972.499op/s 19150929.836op/s ± 15965.695op/s 19154470.781op/s ± 9678.845op/s 19162271.404op/s 19170958.490op/s 19175506.577op/s 19179843.902op/s 0.13% -0.780 -0.022 0.08% 1128.945op/s 1 200
credit_card/is_card_number_no_luhn/x371413321323331 execution_time 6.799µs 6.811µs ± 0.005µs 6.812µs ± 0.004µs 6.815µs 6.819µs 6.823µs 6.825µs 0.19% 0.058 -0.546 0.08% 0.000µs 1 200
credit_card/is_card_number_no_luhn/x371413321323331 throughput 146527699.561op/s 146813784.643op/s ± 110897.742op/s 146807431.413op/s ± 84800.719op/s 146896629.506op/s 146992635.825op/s 147026457.011op/s 147083619.785op/s 0.19% -0.055 -0.547 0.08% 7841.655op/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 [3.911µs; 3.912µs] or [-0.009%; +0.009%] None None None
credit_card/is_card_number/ throughput [255648053.186op/s; 255693712.198op/s] or [-0.009%; +0.009%] None None None
credit_card/is_card_number/ 3782-8224-6310-005 execution_time [79.580µs; 79.670µs] or [-0.056%; +0.056%] None None None
credit_card/is_card_number/ 3782-8224-6310-005 throughput [12552030.193op/s; 12566116.056op/s] or [-0.056%; +0.056%] None None None
credit_card/is_card_number/ 378282246310005 execution_time [72.851µs; 72.950µs] or [-0.068%; +0.068%] None None None
credit_card/is_card_number/ 378282246310005 throughput [13708310.788op/s; 13727001.201op/s] or [-0.068%; +0.068%] None None None
credit_card/is_card_number/37828224631 execution_time [3.913µs; 3.914µs] or [-0.012%; +0.012%] None None None
credit_card/is_card_number/37828224631 throughput [255511381.659op/s; 255573582.345op/s] or [-0.012%; +0.012%] None None None
credit_card/is_card_number/378282246310005 execution_time [69.566µs; 69.636µs] or [-0.051%; +0.051%] None None None
credit_card/is_card_number/378282246310005 throughput [14360572.309op/s; 14375065.254op/s] or [-0.050%; +0.050%] None None None
credit_card/is_card_number/37828224631000521389798 execution_time [52.306µs; 52.316µs] or [-0.009%; +0.009%] None None None
credit_card/is_card_number/37828224631000521389798 throughput [19114605.530op/s; 19118111.078op/s] or [-0.009%; +0.009%] None None None
credit_card/is_card_number/x371413321323331 execution_time [6.808µs; 6.809µs] or [-0.009%; +0.009%] None None None
credit_card/is_card_number/x371413321323331 throughput [146854909.890op/s; 146882269.519op/s] or [-0.009%; +0.009%] None None None
credit_card/is_card_number_no_luhn/ execution_time [3.912µs; 3.913µs] or [-0.011%; +0.011%] None None None
credit_card/is_card_number_no_luhn/ throughput [255584232.862op/s; 255640552.507op/s] or [-0.011%; +0.011%] None None None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 execution_time [64.463µs; 64.511µs] or [-0.037%; +0.037%] None None None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005 throughput [15501333.831op/s; 15512783.595op/s] or [-0.037%; +0.037%] None None None
credit_card/is_card_number_no_luhn/ 378282246310005 execution_time [58.084µs; 58.135µs] or [-0.044%; +0.044%] None None None
credit_card/is_card_number_no_luhn/ 378282246310005 throughput [17201590.276op/s; 17216716.860op/s] or [-0.044%; +0.044%] None None None
credit_card/is_card_number_no_luhn/37828224631 execution_time [3.912µs; 3.913µs] or [-0.010%; +0.010%] None None None
credit_card/is_card_number_no_luhn/37828224631 throughput [255559470.600op/s; 255610638.203op/s] or [-0.010%; +0.010%] None None None
credit_card/is_card_number_no_luhn/378282246310005 execution_time [54.799µs; 54.855µs] or [-0.051%; +0.051%] None None None
credit_card/is_card_number_no_luhn/378282246310005 throughput [18230295.571op/s; 18248622.367op/s] or [-0.050%; +0.050%] None None None
credit_card/is_card_number_no_luhn/37828224631000521389798 execution_time [52.211µs; 52.223µs] or [-0.012%; +0.012%] None None None
credit_card/is_card_number_no_luhn/37828224631000521389798 throughput [19148717.144op/s; 19153142.528op/s] or [-0.012%; +0.012%] None None None
credit_card/is_card_number_no_luhn/x371413321323331 execution_time [6.811µs; 6.812µs] or [-0.010%; +0.010%] None None None
credit_card/is_card_number_no_luhn/x371413321323331 throughput [146798415.282op/s; 146829154.003op/s] or [-0.010%; +0.010%] None None None

Group 11

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3fef267 1774634347 gyuheon0h/PROF-14095-emit-ucontxt-structured
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 144.671µs 146.263µs ± 1.622µs 145.954µs ± 0.422µs 146.444µs 147.921µs 153.179µs 161.028µs 10.33% 5.497 40.482 1.11% 0.115µs 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 [146.038µs; 146.488µs] or [-0.154%; +0.154%] None None None

Group 12

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3fef267 1774634347 gyuheon0h/PROF-14095-emit-ucontxt-structured
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 4.263ms 4.268ms ± 0.007ms 4.267ms ± 0.002ms 4.269ms 4.271ms 4.276ms 4.365ms 2.28% 11.496 147.244 0.17% 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 [4.267ms; 4.269ms] or [-0.024%; +0.024%] None None None

Group 13

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3fef267 1774634347 gyuheon0h/PROF-14095-emit-ucontxt-structured
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 13.810µs 13.962µs ± 0.094µs 13.935µs ± 0.035µs 13.983µs 14.158µs 14.267µs 14.343µs 2.93% 1.578 2.402 0.67% 0.007µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
two way interface execution_time [13.949µs; 13.975µs] or [-0.093%; +0.093%] None None None

Group 14

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3fef267 1774634347 gyuheon0h/PROF-14095-emit-ucontxt-structured
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 33.519µs 33.997µs ± 0.811µs 33.632µs ± 0.058µs 33.730µs 35.706µs 35.754µs 37.246µs 10.75% 1.788 1.586 2.38% 0.057µs 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
redis/obfuscate_redis_string execution_time [33.885µs; 34.110µs] or [-0.330%; +0.330%] None None None

Group 15

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3fef267 1774634347 gyuheon0h/PROF-14095-emit-ucontxt-structured
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 718.727µs 719.480µs ± 0.387µs 719.435µs ± 0.245µs 719.683µs 720.140µs 720.430µs 721.429µs 0.28% 1.078 3.068 0.05% 0.027µs 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 [719.426µs; 719.533µs] or [-0.007%; +0.007%] None None None

Group 16

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3fef267 1774634347 gyuheon0h/PROF-14095-emit-ucontxt-structured
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 926.912µs 931.131µs ± 2.091µs 930.973µs ± 1.141µs 932.248µs 934.002µs 934.838µs 950.071µs 2.05% 3.739 31.852 0.22% 0.148µs 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 [930.842µs; 931.421µs] or [-0.031%; +0.031%] None None None

Group 17

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3fef267 1774634347 gyuheon0h/PROF-14095-emit-ucontxt-structured
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 5.455µs 5.524µs ± 0.024µs 5.520µs ± 0.016µs 5.541µs 5.567µs 5.576µs 5.579µs 1.05% 0.135 -0.312 0.44% 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 [5.520µs; 5.527µs] or [-0.061%; +0.061%] None None None

Group 18

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3fef267 1774634347 gyuheon0h/PROF-14095-emit-ucontxt-structured
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 49.918ms 50.226ms ± 1.283ms 50.060ms ± 0.054ms 50.120ms 50.246ms 55.084ms 62.959ms 25.77% 8.886 80.399 2.55% 0.091ms 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 [50.049ms; 50.404ms] or [-0.354%; +0.354%] None None None

Group 19

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3fef267 1774634347 gyuheon0h/PROF-14095-emit-ucontxt-structured
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 159.943µs 160.813µs ± 0.299µs 160.792µs ± 0.155µs 160.959µs 161.311µs 161.883µs 162.397µs 1.00% 1.175 4.982 0.19% 0.021µs 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 [160.771µs; 160.854µs] or [-0.026%; +0.026%] None None None

Group 20

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3fef267 1774634347 gyuheon0h/PROF-14095-emit-ucontxt-structured
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 495.326µs 496.293µs ± 0.783µs 496.149µs ± 0.306µs 496.452µs 497.571µs 499.648µs 500.610µs 0.90% 2.859 10.326 0.16% 0.055µs 1 200
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000... throughput 1997563.638op/s 2014943.601op/s ± 3165.915op/s 2015522.096op/s ± 1242.956op/s 2016765.314op/s 2018040.113op/s 2018443.962op/s 2018871.514op/s 0.17% -2.839 10.199 0.16% 223.864op/s 1 200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて execution_time 370.680µs 371.652µs ± 0.342µs 371.643µs ± 0.239µs 371.898µs 372.256µs 372.413µs 372.499µs 0.23% 0.021 -0.301 0.09% 0.024µs 1 200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて throughput 2684572.532op/s 2690694.888op/s ± 2478.753op/s 2690757.605op/s ± 1730.873op/s 2692312.937op/s 2694821.537op/s 2695951.995op/s 2697745.002op/s 0.26% -0.017 -0.300 0.09% 175.274op/s 1 200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters execution_time 168.019µs 168.442µs ± 0.173µs 168.436µs ± 0.108µs 168.539µs 168.708µs 169.037µs 169.155µs 0.43% 0.806 2.124 0.10% 0.012µs 1 200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters throughput 5911731.253op/s 5936773.513op/s ± 6104.404op/s 5936971.044op/s ± 3804.653op/s 5940822.910op/s 5945633.144op/s 5947999.611op/s 5951712.785op/s 0.25% -0.795 2.091 0.10% 431.647op/s 1 200
normalization/normalize_service/normalize_service/[empty string] execution_time 36.848µs 37.027µs ± 0.100µs 37.023µs ± 0.084µs 37.111µs 37.180µs 37.247µs 37.265µs 0.65% 0.092 -1.063 0.27% 0.007µs 1 200
normalization/normalize_service/normalize_service/[empty string] throughput 26835081.711op/s 27007553.249op/s ± 73081.524op/s 27010520.899op/s ± 61411.405op/s 27067680.020op/s 27116181.515op/s 27133613.607op/s 27138810.465op/s 0.47% -0.084 -1.068 0.27% 5167.644op/s 1 200
normalization/normalize_service/normalize_service/test_ASCII execution_time 46.259µs 46.374µs ± 0.069µs 46.359µs ± 0.045µs 46.413µs 46.511µs 46.555µs 46.645µs 0.62% 0.829 0.610 0.15% 0.005µs 1 200
normalization/normalize_service/normalize_service/test_ASCII throughput 21438545.457op/s 21563937.846op/s ± 32130.096op/s 21570931.875op/s ± 20788.573op/s 21588774.269op/s 21606520.690op/s 21615313.014op/s 21617186.528op/s 0.21% -0.821 0.585 0.15% 2271.941op/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 [496.184µs; 496.402µs] or [-0.022%; +0.022%] None None None
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000... throughput [2014504.836op/s; 2015382.367op/s] or [-0.022%; +0.022%] None None None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて execution_time [371.604µs; 371.699µs] or [-0.013%; +0.013%] None None None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて throughput [2690351.357op/s; 2691038.419op/s] or [-0.013%; +0.013%] None None None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters execution_time [168.418µs; 168.466µs] or [-0.014%; +0.014%] None None None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters throughput [5935927.502op/s; 5937619.525op/s] or [-0.014%; +0.014%] None None None
normalization/normalize_service/normalize_service/[empty string] execution_time [37.013µs; 37.041µs] or [-0.038%; +0.038%] None None None
normalization/normalize_service/normalize_service/[empty string] throughput [26997424.853op/s; 27017681.646op/s] or [-0.038%; +0.038%] None None None
normalization/normalize_service/normalize_service/test_ASCII execution_time [46.364µs; 46.383µs] or [-0.021%; +0.021%] None None None
normalization/normalize_service/normalize_service/test_ASCII throughput [21559484.924op/s; 21568390.768op/s] or [-0.021%; +0.021%] None None None

Group 21

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3fef267 1774634347 gyuheon0h/PROF-14095-emit-ucontxt-structured
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 14.234ms 14.288ms ± 0.038ms 14.282ms ± 0.015ms 14.298ms 14.350ms 14.418ms 14.587ms 2.14% 3.487 20.236 0.27% 0.003ms 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 [14.283ms; 14.294ms] or [-0.037%; +0.037%] None None None

Baseline

Omitted due to size.

@gyuheon0h gyuheon0h force-pushed the gyuheon0h/PROF-14095-emit-ucontxt-structured branch 2 times, most recently from 222c096 to 267bfa5 Compare March 26, 2026 19:47
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codecov-commenter commented Mar 26, 2026 •
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Codecov Report

❌ Patch coverage is 93.05556% with 5 lines in your changes missing coverage. Please review.
✅ Project coverage is 71.47%. Comparing base (489884e) to head (3fef267).
⚠️ Report is 4 commits behind head on main.

Additional details and impacted files 
@@            Coverage Diff             @@
##             main    #1787      +/-   ##
==========================================
+ Coverage   71.17%   71.47%   +0.29%     
==========================================
  Files         414      414              
  Lines       65912    66082     +170     
==========================================
+ Hits        46915    47233     +318     
+ Misses      18997    18849     -148
Components Coverage Δ
libdd-crashtracker 65.84% <93.05%> (+0.52%) ⬆️
libdd-crashtracker-ffi 35.62% <ø> (+0.38%) ⬆️
libdd-alloc 98.77% <ø> (ø)
libdd-data-pipeline 87.31% <ø> (+0.04%) ⬆️
libdd-data-pipeline-ffi 74.40% <ø> (+0.22%) ⬆️
libdd-common 79.79% <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 81.62% <ø> (ø)
libdd-profiling-ffi 64.94% <ø> (ø)
datadog-sidecar 32.56% <ø> (+1.87%) ⬆️
datdog-sidecar-ffi 17.46% <ø> (+8.54%) ⬆️
spawn-worker 54.69% <ø> (ø)
libdd-tinybytes 93.16% <ø> (ø)
libdd-trace-normalization 81.71% <ø> (ø)
libdd-trace-obfuscation 87.24% <ø> (ø)
libdd-trace-protobuf 68.25% <ø> (ø)
libdd-trace-utils 88.84% <ø> (+0.20%) ⬆️
datadog-tracer-flare 86.88% <ø> (ø)
libdd-log 74.69% <ø> (ø)
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@gyuheon0h gyuheon0h force-pushed the gyuheon0h/PROF-14095-emit-ucontxt-structured branch from 267bfa5 to 51e6175 Compare March 26, 2026 20:02
@gyuheon0h gyuheon0h marked this pull request as ready for review March 26, 2026 20:05
@gyuheon0h gyuheon0h requested review from a team as code owners March 26, 2026 20:05
@gyuheon0h gyuheon0h force-pushed the gyuheon0h/PROF-14095-emit-ucontxt-structured branch from 51e6175 to aaec8b3 Compare March 26, 2026 20:24
@gyuheon0h gyuheon0h requested a review from gleocadie March 26, 2026 20:31
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Artifact Size Benchmark Report

aarch64-alpine-linux-musl
Artifact Baseline Commit Change
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.so 8.76 MB 8.76 MB 0% (0 B) 👌
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.a 101.90 MB 102.05 MB +.13% (+145.93 KB) 🔍
aarch64-unknown-linux-gnu
Artifact Baseline Commit Change
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.a 118.84 MB 119.03 MB +.15% (+186.59 KB) 🔍
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.so 11.36 MB 11.36 MB +.02% (+2.78 KB) 🔍
libdatadog-x64-windows
Artifact Baseline Commit Change
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.dll 27.39 MB 27.41 MB +.06% (+18.00 KB) 🔍
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.lib 80.69 KB 80.69 KB 0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.pdb 187.22 MB 187.32 MB +.05% (+104.00 KB) 🔍
/libdatadog-x64-windows/debug/static/datadog_profiling_ffi.lib 924.91 MB 925.63 MB +.07% (+739.85 KB) 🔍
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.dll 9.06 MB 9.07 MB +.03% (+3.50 KB) 🔍
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.lib 80.69 KB 80.69 KB 0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.pdb 26.98 MB 26.99 MB +.05% (+16.00 KB) 🔍
/libdatadog-x64-windows/release/static/datadog_profiling_ffi.lib 61.28 MB 61.30 MB +.04% (+25.43 KB) 🔍
libdatadog-x86-windows
Artifact Baseline Commit Change
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.dll 23.20 MB 23.22 MB +.06% (+16.50 KB) 🔍
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.lib 81.94 KB 81.94 KB 0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.pdb 191.48 MB 191.59 MB +.05% (+112.00 KB) 🔍
/libdatadog-x86-windows/debug/static/datadog_profiling_ffi.lib 908.20 MB 908.92 MB +.07% (+732.15 KB) 🔍
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.dll 6.90 MB 6.90 MB +.04% (+3.50 KB) 🔍
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.lib 81.94 KB 81.94 KB 0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.pdb 29.11 MB 29.12 MB +.05% (+16.00 KB) 🔍
/libdatadog-x86-windows/release/static/datadog_profiling_ffi.lib 57.68 MB 57.70 MB +.03% (+23.24 KB) 🔍
x86_64-alpine-linux-musl
Artifact Baseline Commit Change
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.a 88.72 MB 88.86 MB +.15% (+144.70 KB) 🔍
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.so 10.32 MB 10.34 MB +.15% (+16.00 KB) 🔍
x86_64-unknown-linux-gnu
Artifact Baseline Commit Change
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.a 111.54 MB 111.71 MB +.14% (+170.57 KB) 🔍
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.so 12.07 MB 12.09 MB +.17% (+22.09 KB) 🔍

@gyuheon0h gyuheon0h force-pushed the gyuheon0h/PROF-14095-emit-ucontxt-structured branch from aaec8b3 to 3fef267 Compare March 27, 2026 17:59
@gyuheon0h gyuheon0h requested a review from danielsn March 27, 2026 18:09
@gyuheon0h gyuheon0h force-pushed the gyuheon0h/PROF-14095-emit-ucontxt-structured branch from f63f13d to 3fef267 Compare March 27, 2026 21:56
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