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feat(remote-config): add an agentless fetcher constructor - #2456

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BridgeAR/2026-09-03-wasm-remote-agentless
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feat(remote-config): add an agentless fetcher constructor#2456
BridgeAR wants to merge 1 commit into
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BridgeAR/2026-09-03-wasm-remote-agentless

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@BridgeAR

@BridgeAR BridgeAR commented Sep 3, 2026

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What does this PR do?

Adds an explicit agentless constructor for the single-target remote-config fetcher.

Motivation

Consumers with an agentless-only contract should not express it through an optional mode flag or retain generic transport dispatch.

Additional Notes

The libdatadog-nodejs consumer pins commit 3bb89cfd2ce3c6f4ee3e4009c74a77e4cf89adf8.

How to test the change?

Run the remote-config tests, all-feature Clippy, and the no-default-features agentless check.

@BridgeAR
feat(remote-config): add an agentless fetcher constructor
3bb89cf 
Consumers that require agentless remote config should not have to express that invariant through an optional mode flag. The generic constructor also keeps the agent path reachable in builds that never use it.

Add a constructor that accepts validated agentless configuration directly while sharing the common fetcher state. Request-level tests pin endpoint selection for both the dedicated and generic constructors.
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📚 Documentation Check Results

⚠️ 682 documentation warning(s) found

📦 libdd-remote-config - 682 warning(s)

Updated: 2026-09-03 11:34:59 UTC | Commit: 797e8fa | missing-docs job results

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🔒 Cargo Deny Results

⚠️ 2 issue(s) found, showing only errors (advisories, bans, sources)

📦 libdd-remote-config - 2 error(s)

Show output 
error[unsound]: Rand is unsound with a custom logger using `rand::rng()`
    ┌─ /home/runner/work/libdatadog/libdatadog/Cargo.lock:102:1
    │
102 │ rand 0.8.5 registry+https://github.com/rust-lang/crates.io-index
    │ ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ unsound advisory detected
    │
    ├ ID: RUSTSEC-2026-0097
    ├ Advisory: https://rustsec.org/advisories/RUSTSEC-2026-0097
    ├ It has been reported (by [@lopopolo](https://github.com/lopopolo)) that the `rand` library is [unsound](https://rust-lang.github.io/unsafe-code-guidelines/glossary.html#soundness-of-code--of-a-library) (i.e. that safe code using the public API can cause Undefined Behaviour) when all the following conditions are met:
      
      - The `log` and `thread_rng` features are enabled
      - A [custom logger](https://docs.rs/log/latest/log/#implementing-a-logger) is defined
      - The custom logger accesses `rand::rng()` (previously `rand::thread_rng()`) and calls any `TryRng` (previously `RngCore`) methods on `ThreadRng`
      - The `ThreadRng` (attempts to) reseed while called from the custom logger (this happens every 64 kB of generated data)
      - Trace-level logging is enabled or warn-level logging is enabled and the random source (the `getrandom` crate) is unable to provide a new seed
      
      `TryRng` (previously `RngCore`) methods for `ThreadRng` use `unsafe` code to cast `*mut BlockRng<ReseedingCore>` to `&mut BlockRng<ReseedingCore>`. When all the above conditions are met this results in an aliased mutable reference, violating the Stacked Borrows rules. Miri is able to detect this violation in sample code. Since construction of [aliased mutable references is Undefined Behaviour](https://doc.rust-lang.org/stable/nomicon/references.html), the behaviour of optimized builds is hard to predict.
    ├ Announcement: https://github.com/rust-random/rand/pull/1763
    ├ Solution: Upgrade to >=0.10.1 OR <0.10.0, >=0.9.3 OR <0.9.0, >=0.8.6 (try `cargo update -p rand`)
    ├ rand v0.8.5
      ├── (dev) libdd-common v5.2.0
      │   ├── libdd-capabilities-impl v4.0.0
      │   │   └── libdd-remote-config v4.0.0
      │   │       └── (dev) libdd-remote-config v4.0.0 (*)
      │   └── libdd-remote-config v4.0.0 (*)
      └── proptest v1.5.0
          └── (dev) libdd-common v5.2.0 (*)

error[vulnerability]: Denial of Service via Stack Exhaustion
    ┌─ /home/runner/work/libdatadog/libdatadog/Cargo.lock:146:1
    │
146 │ time 0.3.41 registry+https://github.com/rust-lang/crates.io-index
    │ ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ security vulnerability detected
    │
    ├ ID: RUSTSEC-2026-0009
    ├ Advisory: https://rustsec.org/advisories/RUSTSEC-2026-0009
    ├ ## Impact
      
      When user-provided input is provided to any type that parses with the RFC 2822 format, a denial of
      service attack via stack exhaustion is possible. The attack relies on formally deprecated and
      rarely-used features that are part of the RFC 2822 format used in a malicious manner. Ordinary,
      non-malicious input will never encounter this scenario.
      
      ## Patches
      
      A limit to the depth of recursion was added in v0.3.47. From this version, an error will be returned
      rather than exhausting the stack.
      
      ## Workarounds
      
      Limiting the length of user input is the simplest way to avoid stack exhaustion, as the amount of
      the stack consumed would be at most a factor of the length of the input.
    ├ Announcement: https://github.com/time-rs/time/blob/main/CHANGELOG.md#0347-2026-02-05
    ├ Solution: Upgrade to >=0.3.47 (try `cargo update -p time`)
    ├ time v0.3.41
      └── libdd-remote-config v4.0.0
          └── (dev) libdd-remote-config v4.0.0 (*)

advisories FAILED, bans ok, sources ok

Updated: 2026-09-03 11:37:08 UTC | Commit: 797e8fa | dependency-check job results

@datadog-official

datadog-official Bot commented Sep 3, 2026 •
edited by datadog-prod-us1-5 Bot
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Tests

✅ All CI checks and tests passed.

🎉 All green!

🧪 All tests passed
❄️ No new flaky tests detected

🎯 Code Coverage (details)
• Patch Coverage: 95.48%
• Overall Coverage: 77.17% (+0.09%)

This comment will be updated automatically if new data arrives.
🔗 Commit SHA: 3bb89cf | Docs | View more details | Give us feedback!

@pr-commenter

pr-commenter Bot commented Sep 3, 2026 •
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Benchmarks

Comparison

Benchmark execution time: 2026-09-03 11:41:04

Comparing candidate commit 3bb89cf in PR branch BridgeAR/2026-09-03-wasm-remote-agentless with baseline commit efbbf4c in branch main.

Found 0 performance improvements and 0 performance regressions! Performance is the same for 14 metrics, 0 unstable metrics.

Explanation

This is an A/B test comparing a candidate commit's performance against that of a baseline commit. Performance changes are noted in the tables below as:

  • 🟩 = significantly better candidate vs. baseline
  • 🟥 = significantly worse candidate vs. baseline

We compute a confidence interval (CI) over the relative difference of means between metrics from the candidate and baseline commits, considering the baseline as the reference.

If the CI is entirely outside the configured SIGNIFICANT_IMPACT_THRESHOLD (or the deprecated UNCONFIDENCE_THRESHOLD), the change is considered significant.

Feel free to reach out to #apm-benchmarking-platform on Slack if you have any questions.

More details about the CI and significant changes

You can imagine this CI as a range of values that is likely to contain the true difference of means between the candidate and baseline commits.

CIs of the difference of means are often centered around 0%, because often changes are not that big:

---------------------------------(------|---^--------)-------------------------------->
                              -0.6%    0%  0.3%     +1.2%
                                 |          |        |
         lower bound of the CI --'          |        |
sample mean (center of the CI) -------------'        |
         upper bound of the CI ----------------------'

As described above, a change is considered significant if the CI is entirely outside the configured SIGNIFICANT_IMPACT_THRESHOLD (or the deprecated UNCONFIDENCE_THRESHOLD).

For instance, for an execution time metric, this confidence interval indicates a significantly worse performance:

----------------------------------------|---------|---(---------^---------)---------->
                                       0%        1%  1.3%      2.2%      3.1%
                                                  |   |         |         |
       significant impact threshold --------------'   |         |         |
                      lower bound of CI --------------'         |         |
       sample mean (center of the CI) --------------------------'         |
                      upper bound of CI ----------------------------------'

Candidate

Candidate benchmark details

Group 1

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3bb89cf 1788405086 BridgeAR/2026-09-03-wasm-remote-agentless
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
flagevaluation_evp/payloads/scale/2500flags_500users_20fields execution_time 21.548ms 21.624ms ± 0.032ms 21.622ms ± 0.021ms 21.648ms 21.677ms 21.685ms 21.692ms 0.32% -0.115 -0.572 0.15% 0.002ms 1 200
flagevaluation_evp/payloads/scale/2500flags_500users_20fields throughput 115247.893op/s 115612.446op/s ± 171.432op/s 115621.890op/s ± 112.386op/s 115726.210op/s 115916.679op/s 115976.719op/s 116017.722op/s 0.34% 0.122 -0.569 0.15% 12.122op/s 1 200
flagevaluation_evp/payloads/stress/10flags_1000users_250fields execution_time 102.328ms 102.998ms ± 0.216ms 102.968ms ± 0.054ms 103.030ms 103.417ms 103.532ms 105.037ms 2.01% 4.871 40.405 0.21% 0.015ms 1 200
flagevaluation_evp/payloads/stress/10flags_1000users_250fields throughput 9520.445op/s 9708.958op/s ± 20.185op/s 9711.797op/s ± 5.131op/s 9716.103op/s 9729.203op/s 9735.295op/s 9772.526op/s 0.63% -4.755 39.015 0.21% 1.427op/s 1 200
flagevaluation_evp/payloads/typical/100flags_50users_10fields execution_time 595.280µs 596.998µs ± 0.865µs 596.965µs ± 0.632µs 597.636µs 598.375µs 599.103µs 599.351µs 0.40% 0.281 -0.505 0.14% 0.061µs 1 200
flagevaluation_evp/payloads/typical/100flags_50users_10fields throughput 166847.194op/s 167505.154op/s ± 242.688op/s 167513.943op/s ± 177.396op/s 167676.413op/s 167880.274op/s 167949.446op/s 167988.222op/s 0.28% -0.274 -0.511 0.14% 17.161op/s 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
flagevaluation_evp/payloads/scale/2500flags_500users_20fields execution_time [21.620ms; 21.628ms] or [-0.021%; +0.021%] None None None
flagevaluation_evp/payloads/scale/2500flags_500users_20fields throughput [115588.687op/s; 115636.204op/s] or [-0.021%; +0.021%] None None None
flagevaluation_evp/payloads/stress/10flags_1000users_250fields execution_time [102.968ms; 103.028ms] or [-0.029%; +0.029%] None None None
flagevaluation_evp/payloads/stress/10flags_1000users_250fields throughput [9706.160op/s; 9711.755op/s] or [-0.029%; +0.029%] None None None
flagevaluation_evp/payloads/typical/100flags_50users_10fields execution_time [596.878µs; 597.118µs] or [-0.020%; +0.020%] None None None
flagevaluation_evp/payloads/typical/100flags_50users_10fields throughput [167471.520op/s; 167538.788op/s] or [-0.020%; +0.020%] None None None

Group 2

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3bb89cf 1788405086 BridgeAR/2026-09-03-wasm-remote-agentless
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 157.023ns 160.045ns ± 2.384ns 159.581ns ± 1.752ns 161.537ns 164.511ns 166.728ns 171.905ns 7.72% 1.212 2.508 1.49% 0.169ns 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 [159.714ns; 160.375ns] or [-0.206%; +0.206%] None None None

Group 3

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3bb89cf 1788405086 BridgeAR/2026-09-03-wasm-remote-agentless
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 259.311µs 265.079µs ± 12.300µs 262.118µs ± 1.022µs 263.808µs 278.122µs 310.068µs 393.717µs 50.21% 7.191 63.900 4.63% 0.870µs 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 [263.375µs; 266.784µs] or [-0.643%; +0.643%] None None None

Group 4

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz 3bb89cf 1788405086 BridgeAR/2026-09-03-wasm-remote-agentless
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
flagevaluation_evp/coalescer/scale/2500flags_500users_20fields execution_time 5.405ms 5.427ms ± 0.019ms 5.426ms ± 0.005ms 5.431ms 5.439ms 5.446ms 5.668ms 4.46% 10.982 140.248 0.34% 0.001ms 1 200
flagevaluation_evp/coalescer/scale/2500flags_500users_20fields throughput 441065.218op/s 460629.258op/s ± 1517.978op/s 460739.256op/s ± 407.483op/s 461130.078op/s 461686.393op/s 462216.750op/s 462566.826op/s 0.40% -10.759 136.449 0.33% 107.337op/s 1 200
flagevaluation_evp/coalescer/stress/10flags_1000users_250fields execution_time 7.948ms 7.978ms ± 0.009ms 7.977ms ± 0.005ms 7.983ms 7.992ms 8.008ms 8.020ms 0.54% 0.759 3.493 0.12% 0.001ms 1 200
flagevaluation_evp/coalescer/stress/10flags_1000users_250fields throughput 124691.067op/s 125347.128op/s ± 144.706op/s 125365.967op/s ± 72.624op/s 125424.579op/s 125568.642op/s 125696.486op/s 125812.186op/s 0.36% -0.742 3.450 0.12% 10.232op/s 1 200
flagevaluation_evp/coalescer/typical/100flags_50users_10fields execution_time 181.384µs 187.269µs ± 38.926µs 184.364µs ± 0.374µs 184.958µs 185.715µs 186.568µs 734.917µs 298.62% 14.028 194.868 20.73% 2.752µs 1 200
flagevaluation_evp/coalescer/typical/100flags_50users_10fields throughput 136069.787op/s 539935.013op/s ± 28779.901op/s 542405.939op/s ± 1099.956op/s 543294.291op/s 544047.644op/s 549687.973op/s 551316.924op/s 1.64% -13.920 192.845 5.32% 2035.046op/s 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
flagevaluation_evp/coalescer/scale/2500flags_500users_20fields execution_time [5.425ms; 5.430ms] or [-0.047%; +0.047%] None None None
flagevaluation_evp/coalescer/scale/2500flags_500users_20fields throughput [460418.880op/s; 460839.635op/s] or [-0.046%; +0.046%] None None None
flagevaluation_evp/coalescer/stress/10flags_1000users_250fields execution_time [7.977ms; 7.979ms] or [-0.016%; +0.016%] None None None
flagevaluation_evp/coalescer/stress/10flags_1000users_250fields throughput [125327.073op/s; 125367.183op/s] or [-0.016%; +0.016%] None None None
flagevaluation_evp/coalescer/typical/100flags_50users_10fields execution_time [181.874µs; 192.664µs] or [-2.881%; +2.881%] None None None
flagevaluation_evp/coalescer/typical/100flags_50users_10fields throughput [535946.395op/s; 543923.630op/s] or [-0.739%; +0.739%] None None None

Baseline

Baseline benchmark details

Group 1

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz efbbf4c 1788373668 main
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
flagevaluation_evp/payloads/scale/2500flags_500users_20fields execution_time 21.691ms 21.846ms ± 0.076ms 21.846ms ± 0.056ms 21.902ms 21.960ms 22.002ms 22.024ms 0.82% -0.030 -0.678 0.34% 0.005ms 1 200
flagevaluation_evp/payloads/scale/2500flags_500users_20fields throughput 113513.014op/s 114439.579op/s ± 395.692op/s 114438.669op/s ± 290.821op/s 114714.653op/s 115110.905op/s 115202.481op/s 115253.366op/s 0.71% 0.044 -0.680 0.34% 27.980op/s 1 200
flagevaluation_evp/payloads/stress/10flags_1000users_250fields execution_time 103.275ms 103.496ms ± 0.263ms 103.498ms ± 0.093ms 103.566ms 103.622ms 103.683ms 106.895ms 3.28% 10.893 138.815 0.25% 0.019ms 1 200
flagevaluation_evp/payloads/stress/10flags_1000users_250fields throughput 9354.952op/s 9662.225op/s ± 23.861op/s 9662.059op/s ± 8.638op/s 9672.561op/s 9678.827op/s 9680.192op/s 9682.856op/s 0.22% -10.724 135.937 0.25% 1.687op/s 1 200
flagevaluation_evp/payloads/typical/100flags_50users_10fields execution_time 594.187µs 595.242µs ± 0.494µs 595.219µs ± 0.331µs 595.579µs 596.018µs 596.514µs 596.699µs 0.25% 0.282 0.051 0.08% 0.035µs 1 200
flagevaluation_evp/payloads/typical/100flags_50users_10fields throughput 167588.567op/s 167999.029op/s ± 139.408op/s 168005.514op/s ± 93.354op/s 168096.214op/s 168220.168op/s 168276.881op/s 168297.303op/s 0.17% -0.277 0.046 0.08% 9.858op/s 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
flagevaluation_evp/payloads/scale/2500flags_500users_20fields execution_time [21.835ms; 21.856ms] or [-0.048%; +0.048%] None None None
flagevaluation_evp/payloads/scale/2500flags_500users_20fields throughput [114384.740op/s; 114494.419op/s] or [-0.048%; +0.048%] None None None
flagevaluation_evp/payloads/stress/10flags_1000users_250fields execution_time [103.460ms; 103.533ms] or [-0.035%; +0.035%] None None None
flagevaluation_evp/payloads/stress/10flags_1000users_250fields throughput [9658.918op/s; 9665.532op/s] or [-0.034%; +0.034%] None None None
flagevaluation_evp/payloads/typical/100flags_50users_10fields execution_time [595.173µs; 595.310µs] or [-0.012%; +0.012%] None None None
flagevaluation_evp/payloads/typical/100flags_50users_10fields throughput [167979.709op/s; 168018.350op/s] or [-0.012%; +0.012%] None None None

Group 2

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz efbbf4c 1788373668 main
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 157.054ns 159.794ns ± 2.221ns 159.333ns ± 1.217ns 160.462ns 164.328ns 166.556ns 169.651ns 6.48% 1.493 2.746 1.39% 0.157ns 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 [159.486ns; 160.102ns] or [-0.193%; +0.193%] None None None

Group 3

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz efbbf4c 1788373668 main
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 259.859µs 265.256µs ± 11.949µs 262.406µs ± 1.088µs 263.900µs 276.633µs 313.851µs 388.969µs 48.23% 7.112 62.068 4.49% 0.845µs 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 [263.600µs; 266.912µs] or [-0.624%; +0.624%] None None None

Group 4

cpu_model git_commit_sha git_commit_date git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz efbbf4c 1788373668 main
scenario metric min mean ± sd median ± mad p75 p95 p99 max peak_to_median_ratio skewness kurtosis cv sem runs sample_size
flagevaluation_evp/coalescer/scale/2500flags_500users_20fields execution_time 5.368ms 5.390ms ± 0.017ms 5.389ms ± 0.005ms 5.394ms 5.400ms 5.403ms 5.613ms 4.15% 10.904 139.230 0.32% 0.001ms 1 200
flagevaluation_evp/coalescer/scale/2500flags_500users_20fields throughput 445414.637op/s 463801.305op/s ± 1428.730op/s 463897.577op/s ± 439.100op/s 464294.025op/s 464873.802op/s 465275.792op/s 465760.263op/s 0.40% -10.690 135.611 0.31% 101.026op/s 1 200
flagevaluation_evp/coalescer/stress/10flags_1000users_250fields execution_time 7.945ms 7.958ms ± 0.007ms 7.957ms ± 0.004ms 7.961ms 7.969ms 7.981ms 7.996ms 0.49% 1.790 6.771 0.09% 0.000ms 1 200
flagevaluation_evp/coalescer/stress/10flags_1000users_250fields throughput 125065.868op/s 125664.050op/s ± 106.941op/s 125675.348op/s ± 59.636op/s 125731.694op/s 125800.264op/s 125832.409op/s 125872.876op/s 0.16% -1.776 6.687 0.08% 7.562op/s 1 200
flagevaluation_evp/coalescer/typical/100flags_50users_10fields execution_time 179.211µs 182.379µs ± 0.752µs 182.200µs ± 0.398µs 182.826µs 183.702µs 184.620µs 184.677µs 1.36% 0.494 1.649 0.41% 0.053µs 1 200
flagevaluation_evp/coalescer/typical/100flags_50users_10fields throughput 541486.365op/s 548316.506op/s ± 2255.123op/s 548847.631op/s ± 1200.728op/s 549999.004op/s 550604.327op/s 551214.616op/s 558000.424op/s 1.67% -0.451 1.721 0.41% 159.461op/s 1 200
scenario metric 95% CI mean Shapiro-Wilk pvalue Ljung-Box pvalue (lag=1) Dip test pvalue
flagevaluation_evp/coalescer/scale/2500flags_500users_20fields execution_time [5.388ms; 5.393ms] or [-0.044%; +0.044%] None None None
flagevaluation_evp/coalescer/scale/2500flags_500users_20fields throughput [463603.297op/s; 463999.313op/s] or [-0.043%; +0.043%] None None None
flagevaluation_evp/coalescer/stress/10flags_1000users_250fields execution_time [7.957ms; 7.959ms] or [-0.012%; +0.012%] None None None
flagevaluation_evp/coalescer/stress/10flags_1000users_250fields throughput [125649.229op/s; 125678.871op/s] or [-0.012%; +0.012%] None None None
flagevaluation_evp/coalescer/typical/100flags_50users_10fields execution_time [182.275µs; 182.484µs] or [-0.057%; +0.057%] None None None
flagevaluation_evp/coalescer/typical/100flags_50users_10fields throughput [548003.968op/s; 548629.044op/s] or [-0.057%; +0.057%] None None None

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dd-octo-sts Bot commented Sep 3, 2026

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Artifact Size Benchmark Report

aarch64-alpine-linux-musl
Artifact Baseline Commit Change
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.so 8.45 MB 8.45 MB 0% (0 B) 👌
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.a 91.30 MB 91.30 MB 0% (0 B) 👌
aarch64-unknown-linux-gnu
Artifact Baseline Commit Change
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.so 11.38 MB 11.38 MB 0% (0 B) 👌
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.a 102.61 MB 102.61 MB 0% (0 B) 👌
libdatadog-x64-windows
Artifact Baseline Commit Change
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.dll 27.33 MB 27.33 MB 0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.lib 96.08 KB 96.08 KB 0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.pdb 185.41 MB 185.41 MB +0% (+8.00 KB) 👌
/libdatadog-x64-windows/debug/static/datadog_profiling_ffi.lib 805.24 MB 805.24 MB 0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.dll 9.01 MB 9.01 MB 0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.lib 96.08 KB 96.08 KB 0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.pdb 26.21 MB 26.21 MB 0% (0 B) 👌
/libdatadog-x64-windows/release/static/datadog_profiling_ffi.lib 52.22 MB 52.22 MB 0% (0 B) 👌
libdatadog-x86-windows
Artifact Baseline Commit Change
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.dll 23.82 MB 23.82 MB 0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.lib 97.58 KB 97.58 KB 0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.pdb 190.43 MB 190.43 MB 0% (0 B) 👌
/libdatadog-x86-windows/debug/static/datadog_profiling_ffi.lib 788.61 MB 788.61 MB 0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.dll 6.96 MB 6.96 MB 0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.lib 97.58 KB 97.58 KB 0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.pdb 28.19 MB 28.19 MB 0% (0 B) 👌
/libdatadog-x86-windows/release/static/datadog_profiling_ffi.lib 49.70 MB 49.70 MB 0% (0 B) 👌
x86_64-alpine-linux-musl
Artifact Baseline Commit Change
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.a 81.45 MB 81.45 MB 0% (0 B) 👌
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.so 9.41 MB 9.41 MB 0% (0 B) 👌
x86_64-unknown-linux-gnu
Artifact Baseline Commit Change
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.a 97.22 MB 97.22 MB 0% (0 B) 👌
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.so 11.46 MB 11.46 MB 0% (0 B) 👌

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