feat(library-config)!: make libdd-library-config no_std compatible by pawelchcki · Pull Request #1770 · DataDog/libdatadog

pawelchcki · 2026-03-20T12:32:36Z

What does this PR do?

Make libdd-library-config and libdd-library-config-ffi usable in no_std environments.

Motivation

Enable library config parsing in contexts without a full std runtime (e.g. injected into processes).

Key changes

Replace serde_yaml with yaml_serde (no_std-compatible), HashMap with BTreeMap
Add no_std_entry feature for standalone staticlib builds (allocator, panic handler)
Add ddog_library_configurator_get_from_bytes FFI function (works in both std and no_std)
Propagate std feature to workspace consumers of libdd-common-ffi

Uses a fork of yaml_serde pending upstream no_std support: yaml/yaml-serde#7

How to test

cargo check -p libdd-library-config --no-default-features
cargo check -p libdd-library-config-ffi --no-default-features
cargo check -p libdd-library-config-ffi --all-features
cargo check --workspace

…fig-ffi no_std compatible Add no_std support to both crates with std enabled by default. Core types and the matching engine compile under no_std+alloc, while file I/O, YAML parsing, and FFI bindings are gated behind the std feature flag.

github-actions · 2026-03-20T12:33:26Z

📚 Documentation Check Results

⚠️ 325 documentation warning(s) found

📦 `libdd-common` - 175 warning(s)

📦 `libdd-library-config` - 150 warning(s)

Updated: 2026-04-08 11:36:13 UTC | Commit: c238708 | missing-docs job results

github-actions · 2026-03-20T12:34:55Z

Clippy Allow Annotation Report

Comparing clippy allow annotations between branches:

Base Branch: origin/main
PR Branch: origin/pawel/no-std-library-config

Summary by Rule

Rule	Base Branch	PR Branch	Change
expect_used	2	2	No change (0%)
panic	1	1	No change (0%)
unwrap_used	1	1	No change (0%)
Total	4	4	No change (0%)

Annotation Counts by File

File	Base Branch	PR Branch	Change
`libdd-common-ffi/src/cstr.rs`	1	1	No change (0%)
`libdd-common-ffi/src/slice.rs`	2	2	No change (0%)
`libdd-common/src/cstr.rs`	1	1	No change (0%)

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`	21	21	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	196	196	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.

github-actions · 2026-03-20T12:36:56Z

🔒 Cargo Deny Results

✅ No issues found!

📦 `libdd-common` - ✅ No issues

📦 `libdd-library-config` - ✅ No issues

Updated: 2026-04-08 11:39:22 UTC | Commit: c238708 | dependency-check job results

Add dlmalloc (non-Linux) and rustix-dlmalloc (Linux) as global allocators, a panic handler, and no-std-dev/no-std-release profiles with panic="abort" to support building the FFI crate as staticlib/cdylib without std.

… builds Define minimal #[repr(C)] FFI types (Slice, CharSlice, CStr, AsBytes) locally for no_std, matching libdd-common-ffi layout. This enables ddog_library_configurator_new, with_local_path, with_fleet_path, with_process_info, and drop to compile and link without std.

Add CString and Vec types to the local ffi_types module for no_std, with proper Drop impls using alloc::ffi::CString. Un-gate the LibraryConfig struct while keeping rs_vec_to_ffi and logged_result_to_ffi_with_messages behind std.

datadog-prod-us1-3 · 2026-03-20T12:58:35Z

✅ Tests

🎉 All green!

❄️ No new flaky tests detected
🧪 All tests passed

_{This comment will be updated automatically if new data arrives.

🔗 Commit SHA: bc5fdf6 | Docs | Datadog PR Page | Was this helpful? React with 👍/👎 or give us feedback!}

Replace the custom ffi_types::CString and Vec wrappers with a re-export of alloc::ffi::CString. In no_std mode LibraryConfig fields are alloc::ffi::CString (no C header generation happens without std anyway).

dd-octo-sts · 2026-03-20T13:12:15Z

Artifact Size Benchmark Report

aarch64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.so	7.63 MB	7.63 MB	0% (0 B) 👌
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.a	82.89 MB	82.93 MB	+.05% (+43.74 KB) 🔍

aarch64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.so	10.08 MB	10.08 MB	+.05% (+5.93 KB) 🔍
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.a	98.86 MB	98.96 MB	+.10% (+102.84 KB) 🔍

libdatadog-x64-windows

Artifact	Baseline	Commit	Change
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.dll	24.98 MB	25.02 MB	+.14% (+38.00 KB) 🔍
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.lib	77.85 KB	78.50 KB	+.83% (+664 B) 🔍
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.pdb	182.40 MB	183.30 MB	+.49% (+928.00 KB) 🔍
/libdatadog-x64-windows/debug/static/datadog_profiling_ffi.lib	904.68 MB	906.71 MB	+.22% (+2.03 MB) 🔍
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.dll	7.85 MB	7.86 MB	+.15% (+12.50 KB) 🔍
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.lib	77.85 KB	78.50 KB	+.83% (+664 B) 🔍
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.pdb	23.51 MB	23.51 MB	+.03% (+8.00 KB) 🔍
/libdatadog-x64-windows/release/static/datadog_profiling_ffi.lib	45.85 MB	45.89 MB	+.09% (+44.05 KB) 🔍

libdatadog-x86-windows

Artifact	Baseline	Commit	Change
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.dll	21.48 MB	21.51 MB	+.14% (+31.00 KB) 🔍
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.lib	79.06 KB	79.72 KB	+.83% (+674 B) 🔍
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.pdb	186.41 MB	187.31 MB	+.48% (+928.00 KB) 🔍
/libdatadog-x86-windows/debug/static/datadog_profiling_ffi.lib	889.47 MB	891.47 MB	+.22% (+1.99 MB) 🔍
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.dll	6.09 MB	6.10 MB	+.09% (+6.00 KB) 🔍
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.lib	79.06 KB	79.72 KB	+.83% (+674 B) 🔍
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.pdb	25.16 MB	25.17 MB	+.06% (+16.00 KB) 🔍
/libdatadog-x86-windows/release/static/datadog_profiling_ffi.lib	43.33 MB	43.37 MB	+.09% (+40.83 KB) 🔍

x86_64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.a	74.07 MB	74.12 MB	+.05% (+45.37 KB) 🔍
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.so	8.49 MB	8.49 MB	+.04% (+4.00 KB) 🔍

x86_64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.a	91.32 MB	91.43 MB	+.12% (+116.61 KB) 🔍
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.so	10.13 MB	10.15 MB	+.16% (+16.93 KB) 🔍

codecov-commenter · 2026-03-20T13:13:47Z

Codecov Report

❌ Patch coverage is 40.15152% with 79 lines in your changes missing coverage. Please review.
✅ Project coverage is 71.49%. Comparing base (d2685bc) to head (6263db2).

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #1770      +/-   ##
==========================================
- Coverage   71.51%   71.49%   -0.03%     
==========================================
  Files         426      426              
  Lines       67369    67427      +58     
==========================================
+ Hits        48179    48204      +25     
- Misses      19190    19223      +33

Components	Coverage Δ
libdd-crashtracker	`65.99% <ø> (-0.02%)`	⬇️
libdd-crashtracker-ffi	`34.09% <ø> (ø)`
libdd-alloc	`98.77% <ø> (ø)`
libdd-data-pipeline	`86.67% <ø> (+0.01%)`	⬆️
libdd-data-pipeline-ffi	`74.97% <ø> (+0.11%)`	⬆️
libdd-common	`79.09% <47.82%> (-0.08%)`	⬇️
libdd-common-ffi	`73.64% <47.82%> (-0.23%)`	⬇️
libdd-telemetry	`62.80% <ø> (ø)`
libdd-telemetry-ffi	`16.75% <ø> (ø)`
libdd-dogstatsd-client	`82.64% <ø> (ø)`
datadog-ipc	`73.10% <ø> (ø)`
libdd-profiling	`82.13% <ø> (ø)`
libdd-profiling-ffi	`64.94% <ø> (ø)`
datadog-sidecar	`30.56% <ø> (+0.31%)`	⬆️
datdog-sidecar-ffi	`8.92% <ø> (+1.49%)`	⬆️
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	`88.73% <ø> (ø)`
datadog-tracer-flare	`86.88% <ø> (ø)`
libdd-log	`74.69% <ø> (ø)`

🚀 New features to boost your workflow:

❄️ Test Analytics: Detect flaky tests, report on failures, and find test suite problems.
📦 JS Bundle Analysis: Save yourself from yourself by tracking and limiting bundle sizes in JS merges.

pr-commenter · 2026-03-20T13:15:23Z

Benchmarks

Comparison

Benchmark execution time: 2026-03-20 20:49:20

Comparing candidate commit 3243266 in PR branch pawel/no-std-library-config with baseline commit 5d5a596 in branch main.

Found 14 performance improvements and 0 performance regressions! Performance is the same for 45 metrics, 2 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/ 3782-8224-6310-005

🟩 execution_time [-3.491µs; -3.213µs] or [-4.360%; -4.013%]
🟩 throughput [+523892.248op/s; +570070.617op/s] or [+4.194%; +4.564%]

scenario:credit_card/is_card_number/ 378282246310005

🟩 execution_time [-15.872µs; -15.714µs] or [-18.814%; -18.627%]
🟩 throughput [+2718514.960op/s; +2740916.111op/s] or [+22.932%; +23.121%]

scenario:credit_card/is_card_number/378282246310005

🟩 execution_time [-5.647µs; -5.530µs] or [-8.018%; -7.853%]
🟩 throughput [+1211504.087op/s; +1235522.463op/s] or [+8.532%; +8.701%]

scenario:credit_card/is_card_number/37828224631000521389798

🟩 execution_time [-7.458µs; -7.420µs] or [-14.038%; -13.967%]
🟩 throughput [+3056203.836op/s; +3073912.169op/s] or [+16.236%; +16.330%]

scenario:credit_card/is_card_number_no_luhn/ 378282246310005

🟩 execution_time [-4.763µs; -4.710µs] or [-8.086%; -7.997%]
🟩 throughput [+1476664.639op/s; +1492285.631op/s] or [+8.698%; +8.790%]

scenario:credit_card/is_card_number_no_luhn/378282246310005

🟩 execution_time [-5.135µs; -5.075µs] or [-9.228%; -9.120%]
🟩 throughput [+1804975.558op/s; +1825414.378op/s] or [+10.043%; +10.157%]

scenario:credit_card/is_card_number_no_luhn/37828224631000521389798

🟩 execution_time [-7.428µs; -7.387µs] or [-13.979%; -13.903%]
🟩 throughput [+3039350.567op/s; +3058359.021op/s] or [+16.150%; +16.251%]

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	`3243266`	1774038746	pawel/no-std-library-config

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	49.114ms	49.583ms ± 1.225ms	49.458ms ± 0.076ms	49.507ms	49.631ms	57.430ms	62.017ms	25.39%	8.308	71.149	2.46%	0.087ms	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	[49.413ms; 49.753ms] or [-0.342%; +0.342%]	None	None	None

Group 2

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3243266`	1774038746	pawel/no-std-library-config

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	12.948ms	12.981ms ± 0.016ms	12.980ms ± 0.011ms	12.991ms	13.006ms	13.019ms	13.040ms	0.46%	0.411	0.176	0.12%	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	[12.979ms; 12.983ms] or [-0.017%; +0.017%]	None	None	None

Group 3

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3243266`	1774038746	pawel/no-std-library-config

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	186.083µs	186.470µs ± 0.200µs	186.460µs ± 0.157µs	186.621µs	186.796µs	186.897µs	187.261µs	0.43%	0.387	0.161	0.11%	0.014µs	1	200
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo...	throughput	5340139.519op/s	5362797.113op/s ± 5748.120op/s	5363076.958op/s ± 4528.355op/s	5367452.800op/s	5371467.422op/s	5373211.201op/s	5373955.421op/s	0.20%	-0.381	0.144	0.11%	406.453op/s	1	200
normalization/normalize_name/normalize_name/bad-name	execution_time	17.882µs	17.956µs ± 0.035µs	17.954µs ± 0.021µs	17.974µs	18.017µs	18.054µs	18.073µs	0.66%	0.614	0.642	0.19%	0.002µs	1	200
normalization/normalize_name/normalize_name/bad-name	throughput	55332649.192op/s	55693007.668op/s ± 107863.069op/s	55697659.997op/s ± 65174.739op/s	55768691.153op/s	55851433.879op/s	55906006.909op/s	55921000.074op/s	0.40%	-0.601	0.617	0.19%	7627.071op/s	1	200
normalization/normalize_name/normalize_name/good	execution_time	10.338µs	10.537µs ± 0.123µs	10.534µs ± 0.043µs	10.574µs	10.631µs	10.721µs	11.998µs	13.90%	8.298	96.366	1.17%	0.009µs	1	200
normalization/normalize_name/normalize_name/good	throughput	83344224.908op/s	94915170.699op/s ± 1019481.724op/s	94928993.899op/s ± 383407.414op/s	95362493.090op/s	95958810.295op/s	96372104.864op/s	96731501.200op/s	1.90%	-7.297	81.238	1.07%	72088.244op/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	[186.442µs; 186.498µs] or [-0.015%; +0.015%]	None	None	None
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo...	throughput	[5362000.478op/s; 5363593.747op/s] or [-0.015%; +0.015%]	None	None	None
normalization/normalize_name/normalize_name/bad-name	execution_time	[17.951µs; 17.960µs] or [-0.027%; +0.027%]	None	None	None
normalization/normalize_name/normalize_name/bad-name	throughput	[55678058.884op/s; 55707956.452op/s] or [-0.027%; +0.027%]	None	None	None
normalization/normalize_name/normalize_name/good	execution_time	[10.520µs; 10.554µs] or [-0.162%; +0.162%]	None	None	None
normalization/normalize_name/normalize_name/good	throughput	[94773880.337op/s; 95056461.061op/s] or [-0.149%; +0.149%]	None	None	None

Group 4

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3243266`	1774038746	pawel/no-std-library-config

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	159.525µs	160.684µs ± 0.386µs	160.639µs ± 0.202µs	160.854µs	161.367µs	161.749µs	162.426µs	1.11%	1.014	2.668	0.24%	0.027µs	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	[160.630µs; 160.737µs] or [-0.033%; +0.033%]	None	None	None

Group 5

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3243266`	1774038746	pawel/no-std-library-config

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	3.891µs	3.913µs ± 0.003µs	3.912µs ± 0.001µs	3.914µs	3.918µs	3.920µs	3.921µs	0.21%	-1.311	12.437	0.08%	0.000µs	1	200
credit_card/is_card_number/	throughput	255062089.714op/s	255570178.439op/s ± 195452.472op/s	255602181.072op/s ± 97781.372op/s	255684390.472op/s	255795574.180op/s	255840982.755op/s	256984511.382op/s	0.54%	1.340	12.664	0.08%	13820.577op/s	1	200
credit_card/is_card_number/ 3782-8224-6310-005	execution_time	74.611µs	76.708µs ± 0.874µs	76.693µs ± 0.628µs	77.317µs	78.079µs	79.230µs	79.438µs	3.58%	0.255	0.050	1.14%	0.062µs	1	200
credit_card/is_card_number/ 3782-8224-6310-005	throughput	12588500.280op/s	13038085.647op/s ± 148261.337op/s	13039046.402op/s ± 105886.017op/s	13144877.877op/s	13274049.067op/s	13331540.374op/s	13402819.278op/s	2.79%	-0.189	-0.040	1.13%	10483.660op/s	1	200
credit_card/is_card_number/ 378282246310005	execution_time	68.370µs	68.568µs ± 0.074µs	68.561µs ± 0.044µs	68.613µs	68.679µs	68.713µs	69.055µs	0.72%	1.295	8.178	0.11%	0.005µs	1	200
credit_card/is_card_number/ 378282246310005	throughput	14481164.667op/s	14584149.457op/s ± 15761.225op/s	14585454.655op/s ± 9300.720op/s	14593816.241op/s	14606389.714op/s	14618270.167op/s	14626342.042op/s	0.28%	-1.267	7.986	0.11%	1114.487op/s	1	200
credit_card/is_card_number/37828224631	execution_time	3.894µs	3.914µs ± 0.003µs	3.914µs ± 0.002µs	3.915µs	3.917µs	3.919µs	3.920µs	0.17%	-1.998	15.114	0.07%	0.000µs	1	200
credit_card/is_card_number/37828224631	throughput	255072891.869op/s	255519590.296op/s ± 172317.122op/s	255501951.170op/s ± 107391.353op/s	255630771.555op/s	255750170.106op/s	255820726.352op/s	256828410.286op/s	0.52%	2.025	15.348	0.07%	12184.661op/s	1	200
credit_card/is_card_number/378282246310005	execution_time	64.612µs	64.838µs ± 0.156µs	64.806µs ± 0.089µs	64.907µs	65.122µs	65.381µs	65.555µs	1.16%	1.430	3.012	0.24%	0.011µs	1	200
credit_card/is_card_number/378282246310005	throughput	15254338.038op/s	15423109.014op/s ± 36911.446op/s	15430714.550op/s ± 21231.847op/s	15449721.970op/s	15468930.653op/s	15473065.402op/s	15477095.446op/s	0.30%	-1.409	2.916	0.24%	2610.033op/s	1	200
credit_card/is_card_number/37828224631000521389798	execution_time	45.400µs	45.686µs ± 0.131µs	45.695µs ± 0.095µs	45.776µs	45.896µs	45.935µs	45.963µs	0.59%	-0.153	-0.711	0.29%	0.009µs	1	200
credit_card/is_card_number/37828224631000521389798	throughput	21756643.302op/s	21888547.819op/s ± 62631.822op/s	21884462.109op/s ± 45304.908op/s	21933555.603op/s	21999054.708op/s	22017762.846op/s	22026405.134op/s	0.65%	0.164	-0.708	0.29%	4428.739op/s	1	200
credit_card/is_card_number/x371413321323331	execution_time	6.430µs	6.436µs ± 0.003µs	6.436µs ± 0.002µs	6.438µs	6.442µs	6.447µs	6.449µs	0.20%	0.999	1.586	0.05%	0.000µs	1	200
credit_card/is_card_number/x371413321323331	throughput	155069423.004op/s	155378556.187op/s ± 83694.159op/s	155385090.803op/s ± 51513.289op/s	155440616.634op/s	155491588.433op/s	155516760.118op/s	155522536.206op/s	0.09%	-0.994	1.573	0.05%	5918.071op/s	1	200
credit_card/is_card_number_no_luhn/	execution_time	3.898µs	3.913µs ± 0.002µs	3.913µs ± 0.001µs	3.914µs	3.917µs	3.918µs	3.919µs	0.16%	-0.892	7.006	0.06%	0.000µs	1	200
credit_card/is_card_number_no_luhn/	throughput	255168943.812op/s	255566246.776op/s ± 155944.121op/s	255573426.283op/s ± 89853.071op/s	255663183.419op/s	255777375.235op/s	255850615.125op/s	256557169.473op/s	0.38%	0.907	7.104	0.06%	11026.915op/s	1	200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	execution_time	61.457µs	62.681µs ± 0.505µs	62.714µs ± 0.358µs	63.009µs	63.470µs	63.597µs	63.845µs	1.80%	-0.200	-0.421	0.80%	0.036µs	1	200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	throughput	15662866.622op/s	15954835.016op/s ± 128844.795op/s	15945455.999op/s ± 91470.929op/s	16040868.187op/s	16188204.580op/s	16262951.172op/s	16271499.983op/s	2.04%	0.237	-0.397	0.81%	9110.703op/s	1	200
credit_card/is_card_number_no_luhn/ 378282246310005	execution_time	53.950µs	54.165µs ± 0.076µs	54.163µs ± 0.045µs	54.210µs	54.295µs	54.340µs	54.369µs	0.38%	0.011	0.245	0.14%	0.005µs	1	200
credit_card/is_card_number_no_luhn/ 378282246310005	throughput	18392775.636op/s	18462268.490op/s ± 25982.182op/s	18462793.778op/s ± 15292.387op/s	18476289.379op/s	18507208.285op/s	18524449.569op/s	18535675.615op/s	0.39%	-0.001	0.244	0.14%	1837.218op/s	1	200
credit_card/is_card_number_no_luhn/37828224631	execution_time	3.897µs	3.913µs ± 0.002µs	3.912µs ± 0.001µs	3.914µs	3.917µs	3.919µs	3.921µs	0.22%	-0.530	8.566	0.06%	0.000µs	1	200
credit_card/is_card_number_no_luhn/37828224631	throughput	255036318.728op/s	255577507.017op/s ± 157555.171op/s	255597367.349op/s ± 83988.573op/s	255669490.968op/s	255759536.405op/s	255870573.921op/s	256591057.300op/s	0.39%	0.549	8.668	0.06%	11140.833op/s	1	200
credit_card/is_card_number_no_luhn/378282246310005	execution_time	50.313µs	50.538µs ± 0.106µs	50.525µs ± 0.059µs	50.585µs	50.721µs	50.872µs	50.990µs	0.92%	1.022	1.928	0.21%	0.007µs	1	200
credit_card/is_card_number_no_luhn/378282246310005	throughput	19611700.221op/s	19787263.316op/s ± 41307.198op/s	19792110.865op/s ± 23113.761op/s	19814976.655op/s	19840734.128op/s	19861670.598op/s	19875536.978op/s	0.42%	-1.004	1.869	0.21%	2920.860op/s	1	200
credit_card/is_card_number_no_luhn/37828224631000521389798	execution_time	45.396µs	45.728µs ± 0.140µs	45.738µs ± 0.101µs	45.835µs	45.936µs	45.969µs	45.988µs	0.55%	-0.279	-0.735	0.30%	0.010µs	1	200
credit_card/is_card_number_no_luhn/37828224631000521389798	throughput	21744567.656op/s	21868880.636op/s ± 66803.566op/s	21863575.284op/s ± 48344.984op/s	21911825.814op/s	21989595.426op/s	22005589.151op/s	22028365.897op/s	0.75%	0.290	-0.727	0.30%	4723.725op/s	1	200
credit_card/is_card_number_no_luhn/x371413321323331	execution_time	6.430µs	6.438µs ± 0.004µs	6.437µs ± 0.003µs	6.440µs	6.445µs	6.448µs	6.454µs	0.26%	0.641	0.886	0.06%	0.000µs	1	200
credit_card/is_card_number_no_luhn/x371413321323331	throughput	154949005.425op/s	155333051.866op/s ± 97351.367op/s	155344526.474op/s ± 63541.584op/s	155402793.370op/s	155478687.787op/s	155505433.774op/s	155529307.066op/s	0.12%	-0.637	0.874	0.06%	6883.781op/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	[3.912µs; 3.913µs] or [-0.011%; +0.011%]	None	None	None
credit_card/is_card_number/	throughput	[255543090.606op/s; 255597266.272op/s] or [-0.011%; +0.011%]	None	None	None
credit_card/is_card_number/ 3782-8224-6310-005	execution_time	[76.587µs; 76.829µs] or [-0.158%; +0.158%]	None	None	None
credit_card/is_card_number/ 3782-8224-6310-005	throughput	[13017538.052op/s; 13058633.243op/s] or [-0.158%; +0.158%]	None	None	None
credit_card/is_card_number/ 378282246310005	execution_time	[68.557µs; 68.578µs] or [-0.015%; +0.015%]	None	None	None
credit_card/is_card_number/ 378282246310005	throughput	[14581965.103op/s; 14586333.811op/s] or [-0.015%; +0.015%]	None	None	None
credit_card/is_card_number/37828224631	execution_time	[3.913µs; 3.914µs] or [-0.009%; +0.009%]	None	None	None
credit_card/is_card_number/37828224631	throughput	[255495708.800op/s; 255543471.791op/s] or [-0.009%; +0.009%]	None	None	None
credit_card/is_card_number/378282246310005	execution_time	[64.817µs; 64.860µs] or [-0.033%; +0.033%]	None	None	None
credit_card/is_card_number/378282246310005	throughput	[15417993.443op/s; 15428224.585op/s] or [-0.033%; +0.033%]	None	None	None
credit_card/is_card_number/37828224631000521389798	execution_time	[45.668µs; 45.704µs] or [-0.040%; +0.040%]	None	None	None
credit_card/is_card_number/37828224631000521389798	throughput	[21879867.651op/s; 21897227.987op/s] or [-0.040%; +0.040%]	None	None	None
credit_card/is_card_number/x371413321323331	execution_time	[6.435µs; 6.436µs] or [-0.007%; +0.007%]	None	None	None
credit_card/is_card_number/x371413321323331	throughput	[155366956.982op/s; 155390155.393op/s] or [-0.007%; +0.007%]	None	None	None
credit_card/is_card_number_no_luhn/	execution_time	[3.913µs; 3.913µs] or [-0.008%; +0.008%]	None	None	None
credit_card/is_card_number_no_luhn/	throughput	[255544634.421op/s; 255587859.132op/s] or [-0.008%; +0.008%]	None	None	None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	execution_time	[62.611µs; 62.751µs] or [-0.112%; +0.112%]	None	None	None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	throughput	[15936978.367op/s; 15972691.666op/s] or [-0.112%; +0.112%]	None	None	None
credit_card/is_card_number_no_luhn/ 378282246310005	execution_time	[54.154µs; 54.175µs] or [-0.020%; +0.020%]	None	None	None
credit_card/is_card_number_no_luhn/ 378282246310005	throughput	[18458667.609op/s; 18465869.370op/s] or [-0.020%; +0.020%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631	execution_time	[3.912µs; 3.913µs] or [-0.009%; +0.009%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631	throughput	[255555671.386op/s; 255599342.648op/s] or [-0.009%; +0.009%]	None	None	None
credit_card/is_card_number_no_luhn/378282246310005	execution_time	[50.523µs; 50.552µs] or [-0.029%; +0.029%]	None	None	None
credit_card/is_card_number_no_luhn/378282246310005	throughput	[19781538.536op/s; 19792988.097op/s] or [-0.029%; +0.029%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631000521389798	execution_time	[45.708µs; 45.747µs] or [-0.042%; +0.042%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631000521389798	throughput	[21859622.304op/s; 21878138.968op/s] or [-0.042%; +0.042%]	None	None	None
credit_card/is_card_number_no_luhn/x371413321323331	execution_time	[6.437µs; 6.438µs] or [-0.009%; +0.009%]	None	None	None
credit_card/is_card_number_no_luhn/x371413321323331	throughput	[155319559.903op/s; 155346543.829op/s] 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 8259CL CPU @ 2.50GHz	`3243266`	1774038746	pawel/no-std-library-config

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	189.970ns	192.206ns ± 1.751ns	192.055ns ± 1.247ns	193.198ns	195.589ns	196.831ns	200.229ns	4.26%	1.045	1.610	0.91%	0.124ns	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	[191.964ns; 192.449ns] or [-0.126%; +0.126%]	None	None	None

Group 7

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3243266`	1774038746	pawel/no-std-library-config

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	5.017µs	5.075µs ± 0.028µs	5.070µs ± 0.020µs	5.092µs	5.136µs	5.138µs	5.144µs	1.46%	0.818	0.080	0.56%	0.002µs	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	[5.071µs; 5.079µs] or [-0.077%; +0.077%]	None	None	None

Group 8

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3243266`	1774038746	pawel/no-std-library-config

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	144.066µs	146.725µs ± 1.713µs	146.419µs ± 0.592µs	147.120µs	148.560µs	152.883µs	161.733µs	10.46%	4.936	34.787	1.16%	0.121µs	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	[146.488µs; 146.963µs] or [-0.162%; +0.162%]	None	None	None

Group 9

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3243266`	1774038746	pawel/no-std-library-config

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	34.319µs	34.772µs ± 0.755µs	34.433µs ± 0.055µs	34.523µs	36.364µs	36.394µs	38.026µs	10.43%	1.824	1.907	2.17%	0.053µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
redis/obfuscate_redis_string	execution_time	[34.668µs; 34.877µs] or [-0.301%; +0.301%]	None	None	None

Group 10

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3243266`	1774038746	pawel/no-std-library-config

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	4.219ms	4.224ms ± 0.003ms	4.224ms ± 0.002ms	4.226ms	4.228ms	4.232ms	4.254ms	0.72%	3.861	32.638	0.08%	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	[4.224ms; 4.225ms] or [-0.011%; +0.011%]	None	None	None

Group 11

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3243266`	1774038746	pawel/no-std-library-config

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	3.402ms	3.435ms ± 0.032ms	3.424ms ± 0.007ms	3.433ms	3.520ms	3.543ms	3.556ms	3.86%	2.182	3.872	0.93%	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	[3.430ms; 3.439ms] or [-0.129%; +0.129%]	None	None	None

Group 12

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3243266`	1774038746	pawel/no-std-library-config

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	13.930ms	13.973ms ± 0.025ms	13.970ms ± 0.012ms	13.983ms	14.016ms	14.067ms	14.104ms	0.96%	1.815	6.138	0.18%	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	[13.970ms; 13.977ms] or [-0.025%; +0.025%]	None	None	None

Group 13

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3243266`	1774038746	pawel/no-std-library-config

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	86.368µs	86.727µs ± 0.133µs	86.719µs ± 0.053µs	86.770µs	86.849µs	87.037µs	88.082µs	1.57%	5.415	53.044	0.15%	0.009µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
sql/obfuscate_sql_string	execution_time	[86.709µs; 86.745µs] or [-0.021%; +0.021%]	None	None	None

Group 14

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3243266`	1774038746	pawel/no-std-library-config

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	495.453µs	497.119µs ± 1.855µs	496.327µs ± 0.402µs	497.004µs	500.559µs	503.511µs	506.162µs	1.98%	1.724	2.866	0.37%	0.131µs	1	200
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000...	throughput	1975652.931op/s	2011619.765op/s ± 7459.876op/s	2014800.839op/s ± 1632.194op/s	2016158.107op/s	2017615.917op/s	2018271.327op/s	2018356.504op/s	0.18%	-1.703	2.728	0.37%	527.493op/s	1	200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	execution_time	377.107µs	377.948µs ± 0.420µs	377.940µs ± 0.294µs	378.210µs	378.697µs	379.002µs	379.275µs	0.35%	0.425	-0.165	0.11%	0.030µs	1	200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	throughput	2636611.134op/s	2645871.277op/s ± 2936.437op/s	2645926.134op/s ± 2063.075op/s	2648127.091op/s	2650181.783op/s	2650969.736op/s	2651765.742op/s	0.22%	-0.420	-0.174	0.11%	207.637op/s	1	200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	execution_time	168.540µs	168.878µs ± 0.133µs	168.866µs ± 0.077µs	168.961µs	169.118µs	169.229µs	169.283µs	0.25%	0.357	0.312	0.08%	0.009µs	1	200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	throughput	5907277.450op/s	5921433.873op/s ± 4669.255op/s	5921857.646op/s ± 2683.541op/s	5924190.817op/s	5928745.128op/s	5931178.265op/s	5933307.144op/s	0.19%	-0.352	0.308	0.08%	330.166op/s	1	200
normalization/normalize_service/normalize_service/[empty string]	execution_time	36.827µs	37.034µs ± 0.123µs	37.067µs ± 0.103µs	37.138µs	37.199µs	37.235µs	37.247µs	0.48%	-0.190	-1.455	0.33%	0.009µs	1	200
normalization/normalize_service/normalize_service/[empty string]	throughput	26847786.874op/s	27002749.368op/s ± 89872.594op/s	26977882.674op/s ± 75057.453op/s	27099282.655op/s	27134688.371op/s	27141319.393op/s	27153928.466op/s	0.65%	0.195	-1.456	0.33%	6354.952op/s	1	200
normalization/normalize_service/normalize_service/test_ASCII	execution_time	46.217µs	46.316µs ± 0.065µs	46.304µs ± 0.036µs	46.352µs	46.422µs	46.452µs	46.820µs	1.11%	2.710	16.959	0.14%	0.005µs	1	200
normalization/normalize_service/normalize_service/test_ASCII	throughput	21358573.247op/s	21590865.579op/s ± 29993.568op/s	21596511.169op/s ± 16688.328op/s	21611003.159op/s	21625825.688op/s	21630327.091op/s	21637186.203op/s	0.19%	-2.662	16.462	0.14%	2120.866op/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	[496.862µs; 497.376µs] or [-0.052%; +0.052%]	None	None	None
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000...	throughput	[2010585.898op/s; 2012653.632op/s] or [-0.051%; +0.051%]	None	None	None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	execution_time	[377.890µs; 378.006µs] or [-0.015%; +0.015%]	None	None	None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	throughput	[2645464.316op/s; 2646278.239op/s] or [-0.015%; +0.015%]	None	None	None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	execution_time	[168.860µs; 168.897µs] or [-0.011%; +0.011%]	None	None	None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	throughput	[5920786.760op/s; 5922080.987op/s] or [-0.011%; +0.011%]	None	None	None
normalization/normalize_service/normalize_service/[empty string]	execution_time	[37.017µs; 37.051µs] or [-0.046%; +0.046%]	None	None	None
normalization/normalize_service/normalize_service/[empty string]	throughput	[26990293.890op/s; 27015204.845op/s] or [-0.046%; +0.046%]	None	None	None
normalization/normalize_service/normalize_service/test_ASCII	execution_time	[46.307µs; 46.325µs] or [-0.019%; +0.019%]	None	None	None
normalization/normalize_service/normalize_service/test_ASCII	throughput	[21586708.759op/s; 21595022.399op/s] or [-0.019%; +0.019%]	None	None	None

Group 15

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3243266`	1774038746	pawel/no-std-library-config

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	2.307µs	2.353µs ± 0.013µs	2.352µs ± 0.004µs	2.359µs	2.374µs	2.378µs	2.380µs	1.17%	-0.982	2.559	0.56%	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	[2.351µs; 2.355µs] or [-0.077%; +0.077%]	None	None	None

Group 16

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3243266`	1774038746	pawel/no-std-library-config

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	4.232ms	4.236ms ± 0.008ms	4.235ms ± 0.001ms	4.236ms	4.240ms	4.246ms	4.345ms	2.60%	11.941	154.706	0.19%	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	[4.235ms; 4.237ms] or [-0.027%; +0.027%]	None	None	None

Group 17

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3243266`	1774038746	pawel/no-std-library-config

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	728.096µs	729.441µs ± 0.612µs	729.423µs ± 0.354µs	729.797µs	730.541µs	730.960µs	732.439µs	0.41%	0.754	2.186	0.08%	0.043µs	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	[729.356µs; 729.526µs] or [-0.012%; +0.012%]	None	None	None

Group 18

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3243266`	1774038746	pawel/no-std-library-config

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	235.877ns	249.118ns ± 14.979ns	242.679ns ± 4.069ns	251.441ns	283.017ns	290.129ns	292.849ns	20.67%	1.504	0.953	6.00%	1.059ns	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	[247.042ns; 251.194ns] or [-0.833%; +0.833%]	None	None	None

Group 19

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3243266`	1774038746	pawel/no-std-library-config

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	1.207µs	3.205µs ± 1.418µs	2.982µs ± 0.030µs	3.014µs	3.684µs	13.945µs	14.734µs	394.17%	7.332	55.007	44.14%	0.100µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
write only interface	execution_time	[3.009µs; 3.402µs] or [-6.132%; +6.132%]	None	None	None

Group 20

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`3243266`	1774038746	pawel/no-std-library-config

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	18.194µs	26.725µs ± 10.111µs	18.670µs ± 0.400µs	35.281µs	45.520µs	46.194µs	70.428µs	277.22%	0.925	0.612	37.74%	0.715µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
two way interface	execution_time	[25.323µs; 28.126µs] or [-5.244%; +5.244%]	None	None	None

Baseline

Omitted due to size.

cbindgen doesn't evaluate cfg(not(feature = "std")) and picks up the ffi_types module types, causing redefinitions with common.h. Exclude Slice_CChar, CharSlice, CStr, Error, and Vec_U8 from the generated header since they are already provided by common.h. Also simplify ffi_types::CString to a re-export of alloc::ffi::CString.

- Fix import ordering for rustfmt (cfg(not(...)) before cfg(feature)) - Remove ddog_CStr from cbindgen exclude list (not in common.h) - Regenerate LICENSE-3rdparty.yml for new deps

… builds Make the minimum subset of libdd-common-ffi work in no_std+alloc so that libdd-library-config-ffi can use the real FFI types instead of duplicating them in a local ffi_types module (~55 lines removed). - Add std feature to libdd-common-ffi (default on), gating std-only modules - Replace std:: imports with core::/alloc:: equivalents in slice.rs and cstr.rs - Replace std::ffi::CStr with core::ffi::CStr in libdd-common cstr macros - Make libdd-common-ffi a non-optional dependency of libdd-library-config-ffi - Delete the duplicated ffi_types module from libdd-library-config-ffi - Remove cbindgen exclude list (no longer needed without ffi_types)

…wn dep BTreeMap from alloc::collections works in both std and no_std without needing the hashbrown crate. The config maps are small, so O(log n) vs O(1) is negligible, and deterministic iteration order is a bonus.

… YAML parsing yaml-peg supports no_std+alloc, enabling parse_stable_config_slice to work without std. Moved trim_bytes into parse_stable_config_slice so all callers (including get_config_from_bytes) benefit from whitespace trimming. Removed serde_yaml dependency.

…paths in cstr.rs

…staticlib/cdylib compat The staticlib/cdylib crate types require an unwinding runtime that doesn't exist in no_std. Gate #![no_std] on the new no_std_entry feature so that --no-default-features compiles with implicit std, while true no_std builds use --features no_std_entry with -Zbuild-std panic=abort.

…eature to consumers Make vec.rs no_std-compatible (core/alloc imports, gate anyhow impl). Move vec module out of #[cfg(feature = "std")] gate since it only needs alloc. Add features = ["std"] to all workspace crates that depend on libdd-common-ffi with default-features = false, since they all need the std-gated types (Handle, Result, Error, etc).

paullegranddc · 2026-03-23T15:14:35Z

libdd-library-config/src/lib.rs

+                Ok(s) => s,
+                Err(e) => return LoggedResult::Err(anyhow::Error::msg(e)),
+            };
+            match yaml_peg::serde::from_str::<StableConfig>(s) {


I don't feel good replacing serde_yaml with a basically unknown yaml parser crate

yes but, https://github.com/dtolnay/serde-yaml was deprecated 2 years ago and stopped receiving any updates. same https://github.com/sebastienrousseau/serde_yml

https://github.com/jayvdb/advisory-db/blob/main/crates/serde_yaml/RUSTSEC-0000-0000.md#recommended-alternatives

yaml_peg is one of recommended alternatives, although with caveat. Generally looks like the state of yaml parsing in Rust is not_great:tm:

I used to rely on https://github.com/Ethiraric/yaml-rust2 and/or https://github.com/saphyr-rs/saphyr. They are not super active, but still slightly more than yaml-peg? Alas, they don't have a no_std feature it seems...

@yannham yesterday I found https://github.com/yaml/yaml-serde - which is resurected serde-yaml now under new auspices.

Luckily converting it into no_std was super simple yaml/yaml-serde#7

bantonsson

I'm not super confident about the changes either. Besides, is there a need for no_std right now, or is it just a nice to have?

Cargo.toml

libdd-library-config/src/lib.rs

pawelchcki · 2026-03-23T19:16:09Z

If you're good with the idea of these changes, I'll be happy to add more testing to cover more of the yaml edgecases.
@bantonsson @paullegranddc
I can also make serde_yaml the default if std is enabled - this is not large problem.

Making this a no_std will also help with pushing these changes to other 3 repositories (httpd and maybe even cpp)

The difference in artifact size is hundreds of kB vs MB of size - I can also add tests in libdatadog which will show you that.

pawelchcki · 2026-03-24T15:35:58Z

I converted back to draft, as it looks like the consesus leans towards slight ok-go on this issue. Because of it I need to add more tests and push this change through some automated code reviews.

- Replace yaml_peg with yaml_serde (serde on libyaml-rs) for YAML parsing - Fix panic on comment-only YAML by using unwrap_or_default - Add yaml wrapper module to isolate YAML dependency - Add tests for comment-only and empty YAML inputs - Remove unused no-std-dev/no-std-release profiles

…comments - Add ddog_library_configurator_get_from_bytes FFI function available in both std and no_std builds, completing the no_std FFI surface - Add LibraryConfigBytesResult type and drop function for the new API - Refactor vec_to_ffi to use alloc::ffi types, making it no_std-compatible - Change get_config_from_bytes to take &ProcessInfo (only borrows internally) - Add SAFETY comments on unsafe blocks (abort, CStr::from_bytes_with_nul_unchecked) - Document rust_eh_personality linkage constraint and panic handler behavior - Add comment explaining no_std_entry feature gating on #![no_std] - Fix safety doc reference (std::str::from_raw_parts -> core::slice::from_raw_parts) - Document ConfigMap duplicate key behavior - Fix typo: varriable -> variable

…config # Conflicts: # Cargo.lock # LICENSE-3rdparty.yml # libdd-common-ffi/Cargo.toml # libdd-library-config/Cargo.toml

… TODO

Avoid full lockfile regeneration that pulled newer transitive deps incompatible with MSRV 1.84.1.

pawelchcki · 2026-04-08T10:37:36Z

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libdd-library-config-ffi/src/lib.rs

…c safety Ensures ddog_library_configurator_get_from_bytes returns LibraryConfigBytesResult::Err on panic (e.g. invalid FFI slice input) instead of aborting the process in std+catch_panic+unwind builds.

…le return types Accept an error constructor parameter instead of hardcoding LibraryConfigLoggedResult::Err, so both get and get_from_bytes share the same panic-catching logic.

pawelchcki · 2026-04-08T11:44:50Z

@paullegranddc @bantonsson not sure if you'd strongly prefer to wait until yaml/yaml-serde#7 is merged ? If you'r ok with branch version the this PR is now ready to review.

If not, I can mark it again as draft

pawelchcki · 2026-04-10T13:36:50Z

…avoid duplication

…port Introduce a no_std-compatible ConfigRead trait so 3rd-party libraries can provide custom file readers (in-memory, sandboxed, etc.) instead of relying on std::fs. get_config_from_file now delegates to the new get_config_from_reader + StdConfigRead.

- Fix TOCTOU in StdConfigRead::read() by reading from already-opened file handle instead of re-opening via fs::read() - Propagate debug logs through get_config_from_bytes (returns LoggedResult instead of anyhow::Result), add logs to LibraryConfigBytesResult FFI type - Use thiserror for ConfigReadError to get core::error::Error impl (works in no_std via default-features = false) - Fix ConfigMap deserializer expecting message (stale HashMap reference) - Add no_std CI build step for library-config crates

…e yaml wrapper - Move MAX_CONFIG_FILE_SIZE, ConfigReadError, ConfigRead trait, and StdConfigRead into dedicated config_read.rs module - Remove yaml::from_bytes wrapper — yaml_serde::from_slice already handles empty, comment-only, and whitespace-only documents - Remove unused trim_bytes utility

pawelchcki added 3 commits March 20, 2026 13:42

feat(library-config-ffi): add global allocator for no_std builds

f2492fd

Add dlmalloc (non-Linux) and rustix-dlmalloc (Linux) as global allocators, a panic handler, and no-std-dev/no-std-release profiles with panic="abort" to support building the FFI crate as staticlib/cdylib without std.

refactor(library-config-ffi): use alloc::ffi::CString directly in no_std

8cc7d0c

Replace the custom ffi_types::CString and Vec wrappers with a re-export of alloc::ffi::CString. In no_std mode LibraryConfig fields are alloc::ffi::CString (no C header generation happens without std anyway).

pawelchcki added 3 commits March 20, 2026 16:17

fix: address CI failures (rustfmt, cbindgen excludes, LICENSE-3rdparty)

3eb69ce

- Fix import ordering for rustfmt (cfg(not(...)) before cfg(feature)) - Remove ddog_CStr from cbindgen exclude list (not in common.h) - Regenerate LICENSE-3rdparty.yml for new deps

github-actions bot added the common label Mar 20, 2026

pawelchcki added 7 commits March 20, 2026 18:36

chore: update Cargo.lock for yaml-peg dependency

641fc8e

refactor(common-ffi): use imports instead of fully qualified alloc:: …

3370b92

…paths in cstr.rs

refactor(common-ffi): consolidate std re-exports into a single cfg block

1ca7bf2

refactor(common-ffi): consolidate cfg-gated imports in slice.rs

a7fbecd

pawelchcki force-pushed the pawel/no-std-library-config branch from ee51658 to e77ef42 Compare March 20, 2026 20:07

pawelchcki added 2 commits March 20, 2026 21:10

chore: regenerate LICENSE-3rdparty.yml

dc6bf5c

github-actions bot added telemetry sidecar data-pipeline crashtracker labels Mar 20, 2026

paullegranddc reviewed Mar 23, 2026

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bantonsson requested changes Mar 23, 2026

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Cargo.toml Outdated Show resolved Hide resolved

libdd-library-config/src/lib.rs Outdated Show resolved Hide resolved

pawelchcki marked this pull request as draft March 24, 2026 15:34

pawelchcki mentioned this pull request Apr 7, 2026

Add no_std support yaml/yaml-serde#7

Open

pawelchcki added 7 commits April 7, 2026 23:46

Merge remote-tracking branch 'origin/main' into pawel/no-std-library-…

5f89b6c

…config # Conflicts: # Cargo.lock # LICENSE-3rdparty.yml # libdd-common-ffi/Cargo.toml # libdd-library-config/Cargo.toml

style(library-config): fix rustfmt blank line between doc comment and…

7e50e99

… TODO

fix: use main's Cargo.lock with minimal dep additions

da96080

Avoid full lockfile regeneration that pulled newer transitive deps incompatible with MSRV 1.84.1.

chore: regenerate LICENSE-3rdparty.csv

b6c41a1

Merge branch 'main' into pawel/no-std-library-config

464fcec

pawelchcki marked this pull request as ready for review April 8, 2026 10:36

pawelchcki requested a review from a team as a code owner April 8, 2026 10:36

pawelchcki requested review from mabdinur and removed request for a team April 8, 2026 10:36

chatgpt-codex-connector bot reviewed Apr 8, 2026

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libdd-library-config-ffi/src/lib.rs Outdated Show resolved Hide resolved

pawelchcki added 2 commits April 8, 2026 13:05

fix(library-config-ffi): wrap get_from_bytes in catch_unwind for pani…

b757c8c

…c safety Ensures ddog_library_configurator_get_from_bytes returns LibraryConfigBytesResult::Err on panic (e.g. invalid FFI slice input) instead of aborting the process in std+catch_panic+unwind builds.

refactor(library-config-ffi): generalize catch_panic macro for multip…

6263db2

…le return types Accept an error constructor parameter instead of hardcoding LibraryConfigLoggedResult::Err, so both get and get_from_bytes share the same panic-catching logic.

pawelchcki requested review from bantonsson and paullegranddc April 8, 2026 11:42

pawelchcki requested a review from yannham April 9, 2026 16:51

pawelchcki added 4 commits April 10, 2026 21:59

fix(library-config-ffi): move panic prefix into catch_panic macro to …

a045a89

…avoid duplication

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What does this PR do?

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📚 Documentation Check Results

📦 libdd-common - 175 warning(s)

📦 libdd-library-config - 150 warning(s)

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Clippy Allow Annotation Report

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🔒 Cargo Deny Results

📦 libdd-common - ✅ No issues

📦 libdd-library-config - ✅ No issues

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Artifact Size Benchmark Report

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Codecov Report

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Benchmarks

Comparison

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More details about the CI and significant changes

scenario:credit_card/is_card_number/ 3782-8224-6310-005

scenario:credit_card/is_card_number/ 378282246310005

scenario:credit_card/is_card_number/378282246310005

scenario:credit_card/is_card_number/37828224631000521389798

scenario:credit_card/is_card_number_no_luhn/ 378282246310005

scenario:credit_card/is_card_number_no_luhn/378282246310005

scenario:credit_card/is_card_number_no_luhn/37828224631000521389798

Candidate

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Baseline

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pawelchcki commented Mar 20, 2026 •

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📦 `libdd-common` - 175 warning(s)

📦 `libdd-library-config` - 150 warning(s)

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📦 `libdd-common` - ✅ No issues

📦 `libdd-library-config` - ✅ No issues

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