feat(remote-config): add an agentless fetcher constructor by BridgeAR · Pull Request #2456 · DataDog/libdatadog

BridgeAR · 2026-09-03T11:33:10Z

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.

github-actions · 2026-09-03T11:34:59Z

📚 Documentation Check Results

⚠️ 682 documentation warning(s) found

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

Updated: 2026-09-09 21:47:02 UTC | Commit: 9dd16e5 | missing-docs job results

github-actions · 2026-09-03T11:37:09Z

🔒 Cargo Deny Results

✅ No issues found!

📦 `libdd-remote-config` - ✅ No issues

Updated: 2026-09-09 21:48:56 UTC | Commit: 9dd16e5 | dependency-check job results

datadog-official · 2026-09-03T11:43:09Z

✅ All CI checks and tests passed.

🎉 All green!

🧪 All tests passed
❄️ No new flaky tests detected

🎯 Code Coverage (details)
• Patch Coverage: 95.45%
• Overall Coverage: 77.71% (+0.08%)

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

🔗 Commit SHA: f4e3e5e | Docs | View more details | Give us feedback!}

pr-commenter · 2026-09-03T11:43:27Z

Benchmarks

Comparison

Benchmark execution time: 2026-09-09 21:56:20

Comparing candidate commit f4e3e5e in PR branch BridgeAR/2026-09-03-wasm-remote-agentless with baseline commit a2a1dfb in branch main.

📊 Benchmarking dashboard

Found 1 performance improvements and 0 performance regressions! Performance is the same for 12 metrics, 1 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:sdk_test_data/rules-based

🟩 execution_time [-24.868µs; -20.167µs] or [-8.712%; -7.065%]

Unstable benchmarks

These benchmarks have a confidence interval too wide to call a change; treat them as noise rather than signal.

scenario:flagevaluation_evp/coalescer/typical/100flags_50users_10fields

unstable execution_time [-11063.136ns; +10240.120ns] or [-6.009%; +5.562%]

Candidate

Candidate benchmark details

Group 1

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz	`f4e3e5e`	1788989402	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	5.319ms	5.335ms ± 0.008ms	5.335ms ± 0.005ms	5.340ms	5.348ms	5.357ms	5.364ms	0.54%	0.561	0.841	0.14%	0.001ms	1	200
flagevaluation_evp/coalescer/scale/2500flags_500users_20fields	throughput	466102.726op/s	468581.504op/s ± 665.453op/s	468628.958op/s ± 406.619op/s	469010.742op/s	469547.832op/s	469961.886op/s	469991.689op/s	0.29%	-0.550	0.818	0.14%	47.055op/s	1	200
flagevaluation_evp/coalescer/stress/10flags_1000users_250fields	execution_time	7.930ms	7.978ms ± 0.013ms	7.978ms ± 0.004ms	7.982ms	7.992ms	8.021ms	8.057ms	0.98%	0.721	10.720	0.16%	0.001ms	1	200
flagevaluation_evp/coalescer/stress/10flags_1000users_250fields	throughput	124121.915op/s	125338.397op/s ± 199.956op/s	125337.793op/s ± 63.706op/s	125403.462op/s	125530.455op/s	126012.646op/s	126095.677op/s	0.60%	-0.663	10.552	0.16%	14.139op/s	1	200
flagevaluation_evp/coalescer/typical/100flags_50users_10fields	execution_time	171.024µs	183.692µs ± 57.335µs	179.723µs ± 0.248µs	179.995µs	180.590µs	181.257µs	990.289µs	451.01%	14.026	194.819	31.13%	4.054µs	1	200
flagevaluation_evp/coalescer/typical/100flags_50users_10fields	throughput	100980.623op/s	554420.553op/s ± 32471.801op/s	556411.497op/s ± 765.797op/s	557097.907op/s	558079.943op/s	583251.590op/s	584714.539op/s	5.09%	-13.703	189.046	5.84%	2296.103op/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	[5.334ms; 5.336ms] or [-0.020%; +0.020%]	None	None	None
flagevaluation_evp/coalescer/scale/2500flags_500users_20fields	throughput	[468489.278op/s; 468673.729op/s] or [-0.020%; +0.020%]	None	None	None
flagevaluation_evp/coalescer/stress/10flags_1000users_250fields	execution_time	[7.977ms; 7.980ms] or [-0.022%; +0.022%]	None	None	None
flagevaluation_evp/coalescer/stress/10flags_1000users_250fields	throughput	[125310.685op/s; 125366.109op/s] or [-0.022%; +0.022%]	None	None	None
flagevaluation_evp/coalescer/typical/100flags_50users_10fields	execution_time	[175.746µs; 191.638µs] or [-4.326%; +4.326%]	None	None	None
flagevaluation_evp/coalescer/typical/100flags_50users_10fields	throughput	[549920.273op/s; 558920.832op/s] or [-0.812%; +0.812%]	None	None	None

Group 2

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz	`f4e3e5e`	1788989402	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	256.983µs	262.914µs ± 12.024µs	259.972µs ± 1.326µs	261.914µs	276.312µs	312.494µs	381.544µs	46.76%	6.640	53.998	4.56%	0.850µs	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	[261.248µs; 264.580µs] or [-0.634%; +0.634%]	None	None	None

Group 3

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz	`f4e3e5e`	1788989402	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	21.737ms	21.867ms ± 0.076ms	21.854ms ± 0.045ms	21.905ms	22.006ms	22.082ms	22.133ms	1.28%	1.016	1.137	0.35%	0.005ms	1	200
flagevaluation_evp/payloads/scale/2500flags_500users_20fields	throughput	112951.569op/s	114329.832op/s ± 396.247op/s	114396.037op/s ± 233.137op/s	114609.809op/s	114836.887op/s	114942.186op/s	115011.086op/s	0.54%	-0.995	1.074	0.35%	28.019op/s	1	200
flagevaluation_evp/payloads/stress/10flags_1000users_250fields	execution_time	102.899ms	103.593ms ± 0.460ms	103.479ms ± 0.216ms	103.824ms	104.337ms	104.726ms	107.474ms	3.86%	3.471	24.115	0.44%	0.033ms	1	200
flagevaluation_evp/payloads/stress/10flags_1000users_250fields	throughput	9304.563op/s	9653.355op/s ± 42.255op/s	9663.815op/s ± 20.105op/s	9677.523op/s	9694.308op/s	9708.783op/s	9718.289op/s	0.56%	-3.291	22.073	0.44%	2.988op/s	1	200
flagevaluation_evp/payloads/typical/100flags_50users_10fields	execution_time	591.867µs	593.877µs ± 0.612µs	593.893µs ± 0.407µs	594.280µs	594.896µs	595.328µs	595.486µs	0.27%	0.012	0.144	0.10%	0.043µs	1	200
flagevaluation_evp/payloads/typical/100flags_50users_10fields	throughput	167929.964op/s	168385.106op/s ± 173.558op/s	168380.389op/s ± 115.442op/s	168498.118op/s	168650.407op/s	168744.142op/s	168956.808op/s	0.34%	-0.006	0.146	0.10%	12.272op/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	[21.856ms; 21.877ms] or [-0.048%; +0.048%]	None	None	None
flagevaluation_evp/payloads/scale/2500flags_500users_20fields	throughput	[114274.916op/s; 114384.748op/s] or [-0.048%; +0.048%]	None	None	None
flagevaluation_evp/payloads/stress/10flags_1000users_250fields	execution_time	[103.529ms; 103.657ms] or [-0.062%; +0.062%]	None	None	None
flagevaluation_evp/payloads/stress/10flags_1000users_250fields	throughput	[9647.499op/s; 9659.211op/s] or [-0.061%; +0.061%]	None	None	None
flagevaluation_evp/payloads/typical/100flags_50users_10fields	execution_time	[593.793µs; 593.962µs] or [-0.014%; +0.014%]	None	None	None
flagevaluation_evp/payloads/typical/100flags_50users_10fields	throughput	[168361.052op/s; 168409.159op/s] or [-0.014%; +0.014%]	None	None	None

Group 4

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz	`f4e3e5e`	1788989402	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	163.540ns	166.388ns ± 2.468ns	165.925ns ± 1.434ns	167.405ns	170.539ns	173.646ns	180.111ns	8.55%	2.249	8.390	1.48%	0.175ns	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	[166.046ns; 166.731ns] or [-0.206%; +0.206%]	None	None	None

Baseline

Baseline benchmark details

Group 1

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz	`a2a1dfb`	1788978547	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	5.352ms	5.387ms ± 0.027ms	5.386ms ± 0.009ms	5.395ms	5.406ms	5.413ms	5.730ms	6.39%	9.806	120.713	0.51%	0.002ms	1	200
flagevaluation_evp/coalescer/scale/2500flags_500users_20fields	throughput	436317.117op/s	464054.777op/s ± 2248.287op/s	464187.580op/s ± 776.427op/s	464924.357op/s	466069.478op/s	466543.473op/s	467147.109op/s	0.64%	-9.403	114.149	0.48%	158.978op/s	1	200
flagevaluation_evp/coalescer/stress/10flags_1000users_250fields	execution_time	7.920ms	7.951ms ± 0.011ms	7.950ms ± 0.005ms	7.957ms	7.968ms	7.980ms	7.999ms	0.62%	0.492	3.130	0.13%	0.001ms	1	200
flagevaluation_evp/coalescer/stress/10flags_1000users_250fields	throughput	125013.178op/s	125769.131op/s ± 167.095op/s	125786.506op/s ± 78.514op/s	125847.916op/s	126026.940op/s	126191.395op/s	126270.077op/s	0.38%	-0.472	3.086	0.13%	11.815op/s	1	200
flagevaluation_evp/coalescer/typical/100flags_50users_10fields	execution_time	178.093µs	184.104µs ± 51.183µs	180.346µs ± 0.312µs	180.778µs	181.680µs	182.243µs	904.264µs	401.41%	14.033	194.944	27.73%	3.619µs	1	200
flagevaluation_evp/coalescer/typical/100flags_50users_10fields	throughput	110587.235op/s	551851.973op/s ± 31418.857op/s	554490.001op/s ± 961.866op/s	555315.603op/s	556043.576op/s	557922.619op/s	561505.959op/s	1.27%	-13.955	193.499	5.68%	2221.649op/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	[5.384ms; 5.391ms] or [-0.070%; +0.070%]	None	None	None
flagevaluation_evp/coalescer/scale/2500flags_500users_20fields	throughput	[463743.186op/s; 464366.368op/s] or [-0.067%; +0.067%]	None	None	None
flagevaluation_evp/coalescer/stress/10flags_1000users_250fields	execution_time	[7.950ms; 7.953ms] or [-0.018%; +0.018%]	None	None	None
flagevaluation_evp/coalescer/stress/10flags_1000users_250fields	throughput	[125745.973op/s; 125792.289op/s] or [-0.018%; +0.018%]	None	None	None
flagevaluation_evp/coalescer/typical/100flags_50users_10fields	execution_time	[177.010µs; 191.197µs] or [-3.853%; +3.853%]	None	None	None
flagevaluation_evp/coalescer/typical/100flags_50users_10fields	throughput	[547497.621op/s; 556206.324op/s] or [-0.789%; +0.789%]	None	None	None

Group 2

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz	`a2a1dfb`	1788978547	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	279.162µs	285.431µs ± 11.960µs	282.516µs ± 1.558µs	284.518µs	299.745µs	335.360µs	404.960µs	43.34%	6.613	54.665	4.18%	0.846µs	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	[283.774µs; 287.089µs] or [-0.581%; +0.581%]	None	None	None

Group 3

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz	`a2a1dfb`	1788978547	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	21.979ms	22.069ms ± 0.034ms	22.071ms ± 0.021ms	22.093ms	22.123ms	22.140ms	22.165ms	0.42%	-0.282	0.267	0.16%	0.002ms	1	200
flagevaluation_evp/payloads/scale/2500flags_500users_20fields	throughput	112790.010op/s	113280.583op/s ± 176.224op/s	113268.729op/s ± 108.623op/s	113376.943op/s	113615.208op/s	113715.337op/s	113742.832op/s	0.42%	0.292	0.271	0.16%	12.461op/s	1	200
flagevaluation_evp/payloads/stress/10flags_1000users_250fields	execution_time	103.660ms	104.202ms ± 0.502ms	104.084ms ± 0.180ms	104.313ms	104.680ms	105.382ms	109.810ms	5.50%	7.452	77.253	0.48%	0.036ms	1	200
flagevaluation_evp/payloads/stress/10flags_1000users_250fields	throughput	9106.628op/s	9596.949op/s ± 44.676op/s	9607.593op/s ± 16.598op/s	9615.879op/s	9630.750op/s	9635.539op/s	9646.963op/s	0.41%	-7.118	72.041	0.46%	3.159op/s	1	200
flagevaluation_evp/payloads/typical/100flags_50users_10fields	execution_time	605.493µs	607.561µs ± 0.745µs	607.550µs ± 0.542µs	608.096µs	608.745µs	609.259µs	609.658µs	0.35%	-0.005	-0.183	0.12%	0.053µs	1	200
flagevaluation_evp/payloads/typical/100flags_50users_10fields	throughput	164026.303op/s	164592.788op/s ± 201.912op/s	164595.427op/s ± 146.790op/s	164739.785op/s	164890.495op/s	165065.769op/s	165154.596op/s	0.34%	0.012	-0.182	0.12%	14.277op/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	[22.064ms; 22.074ms] or [-0.022%; +0.022%]	None	None	None
flagevaluation_evp/payloads/scale/2500flags_500users_20fields	throughput	[113256.160op/s; 113305.006op/s] or [-0.022%; +0.022%]	None	None	None
flagevaluation_evp/payloads/stress/10flags_1000users_250fields	execution_time	[104.133ms; 104.272ms] or [-0.067%; +0.067%]	None	None	None
flagevaluation_evp/payloads/stress/10flags_1000users_250fields	throughput	[9590.757op/s; 9603.140op/s] or [-0.065%; +0.065%]	None	None	None
flagevaluation_evp/payloads/typical/100flags_50users_10fields	execution_time	[607.458µs; 607.664µs] or [-0.017%; +0.017%]	None	None	None
flagevaluation_evp/payloads/typical/100flags_50users_10fields	throughput	[164564.805op/s; 164620.771op/s] or [-0.017%; +0.017%]	None	None	None

Group 4

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz	`a2a1dfb`	1788978547	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	158.880ns	162.245ns ± 2.771ns	161.840ns ± 1.409ns	163.260ns	166.421ns	172.725ns	178.749ns	10.45%	2.497	9.897	1.70%	0.196ns	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	[161.861ns; 162.629ns] or [-0.237%; +0.237%]	None	None	None

dd-octo-sts · 2026-09-03T12:04:29Z

Artifact Size Benchmark Report

aarch64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.a	95.57 MB	95.57 MB	0% (0 B) 👌
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.so	8.96 MB	8.96 MB	0% (0 B) 👌

aarch64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.so	12.10 MB	12.10 MB	0% (0 B) 👌
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.a	106.92 MB	106.92 MB	0% (0 B) 👌

libdatadog-x64-windows

Artifact	Baseline	Commit	Change
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.dll	28.91 MB	28.91 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	191.08 MB	191.09 MB	+0% (+16.00 KB) 👌
/libdatadog-x64-windows/debug/static/datadog_profiling_ffi.lib	810.01 MB	810.01 MB	0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.dll	9.65 MB	9.65 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	27.37 MB	27.37 MB	0% (0 B) 👌
/libdatadog-x64-windows/release/static/datadog_profiling_ffi.lib	55.31 MB	55.31 MB	0% (0 B) 👌

libdatadog-x86-windows

Artifact	Baseline	Commit	Change
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.dll	25.26 MB	25.26 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	196.30 MB	196.30 MB	-0% (-8.00 KB) 👌
/libdatadog-x86-windows/debug/static/datadog_profiling_ffi.lib	795.90 MB	795.90 MB	0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.dll	7.46 MB	7.46 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	29.44 MB	29.44 MB	0% (0 B) 👌
/libdatadog-x86-windows/release/static/datadog_profiling_ffi.lib	52.22 MB	52.22 MB	0% (0 B) 👌

x86_64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.a	85.61 MB	85.61 MB	0% (0 B) 👌
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.so	9.99 MB	9.99 MB	0% (0 B) 👌

x86_64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.a	101.52 MB	101.52 MB	0% (0 B) 👌
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.so	12.20 MB	12.20 MB	0% (0 B) 👌

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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The explicit agentless constructor uses one supplied configuration for its state and endpoint. The prior constructor still selects agent mode or agentless mode from the optional setting.

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BridgeAR force-pushed the BridgeAR/2026-09-03-wasm-remote-agentless branch from 3bb89cf to f4e3e5e Compare September 9, 2026 21:45

BridgeAR marked this pull request as ready for review September 9, 2026 21:46

BridgeAR requested review from a team as code owners September 9, 2026 21:46

datadog-official Bot reviewed Sep 9, 2026

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

feat(remote-config): add an agentless fetcher constructor#2456
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scenario:flagevaluation_evp/coalescer/typical/100flags_50users_10fields

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BridgeAR commented Sep 3, 2026

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

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🔒 Cargo Deny Results

📦 libdd-remote-config - ✅ No issues

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scenario:sdk_test_data/rules-based

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

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📦 `libdd-remote-config` - ✅ No issues

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