fix(libdd-crashtracker-ffi)!: add missing fields for endpoint configuration

[hoolioh]

What does this PR do?

Previous PR (#1705) missed some fields for Endpoint configuration on the FFI layer. This PR solves that issue.

[github-actions]

Clippy Allow Annotation Report

Comparing clippy allow annotations between branches:

• Base Branch: origin/main
• PR Branch: origin/julio/add-endpoint-configuration-in-ffi

Summary by Rule

Rule	Base Branch	PR Branch	Change

Annotation Counts by File

File	Base Branch	PR Branch	Change

Annotation Stats by Crate

Crate	Base Branch	PR Branch	Change
clippy-annotation-reporter	5	5	No change (0%)
datadog-ffe-ffi	1	1	No change (0%)
datadog-ipc	28	28	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	59	59	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	9	9	No change (0%)
libdd-trace-utils	15	15	No change (0%)
Total	208	208	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.

[codecov-commenter]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 71.54%. Comparing base (4dd532f) to head (28312a2).
⚠️ Report is 4 commits behind head on main.

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #1758      +/-   ##
==========================================
+ Coverage   71.51%   71.54%   +0.03%     
==========================================
  Files         430      430              
  Lines       64075    64259     +184     
==========================================
+ Hits        45821    45977     +156     
- Misses      18254    18282      +28     

Components	Coverage Δ
libdd-crashtracker	65.00% <100.00%> (+1.07%)	⬆️
libdd-crashtracker-ffi	34.80% <100.00%> (+16.60%)	⬆️
libdd-alloc	98.77% <ø> (ø)
libdd-data-pipeline	87.92% <ø> (ø)
libdd-data-pipeline-ffi	74.85% <ø> (ø)
libdd-common	79.87% <ø> (+0.14%)	⬆️
libdd-common-ffi	73.87% <ø> (+0.46%)	⬆️
libdd-telemetry	62.48% <ø> (ø)
libdd-telemetry-ffi	16.75% <ø> (ø)
libdd-dogstatsd-client	82.64% <ø> (ø)
datadog-ipc	80.35% <ø> (-0.12%)	⬇️
libdd-profiling	81.48% <ø> (-0.12%)	⬇️
libdd-profiling-ffi	63.65% <ø> (ø)
datadog-sidecar	33.10% <ø> (ø)
datdog-sidecar-ffi	10.79% <ø> (ø)
spawn-worker	54.69% <ø> (ø)
libdd-tinybytes	93.16% <ø> (ø)
libdd-trace-normalization	81.71% <ø> (ø)
libdd-trace-obfuscation	91.80% <ø> (ø)
libdd-trace-protobuf	68.25% <ø> (ø)
libdd-trace-utils	88.95% <ø> (ø)
datadog-tracer-flare	90.46% <ø> (ø)
libdd-log	74.69% <ø> (ø)

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[pr-commenter]

Benchmarks

Comparison

Benchmark execution time: 2026-03-18 17:26:56

Comparing candidate commit 28312a2 in PR branch julio/add-endpoint-configuration-in-ffi with baseline commit 6e12752 in branch main.

Found 0 performance improvements and 0 performance regressions! Performance is the same for 59 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 ----------------------------------'

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	28312a2	1773853788	julio/add-endpoint-configuration-in-ffi

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	4.181ms	4.188ms ± 0.008ms	4.187ms ± 0.002ms	4.189ms	4.193ms	4.197ms	4.291ms	2.48%	11.038	138.690	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	[4.187ms; 4.189ms] or [-0.026%; +0.026%]	None	None	None

Group 2

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	28312a2	1773853788	julio/add-endpoint-configuration-in-ffi

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	144.411µs	146.433µs ± 1.583µs	146.141µs ± 0.473µs	146.717µs	147.934µs	152.639µs	161.108µs	10.24%	5.349	40.571	1.08%	0.112µs	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	[146.213µs; 146.652µs] or [-0.150%; +0.150%]	None	None	None

Group 3

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	28312a2	1773853788	julio/add-endpoint-configuration-in-ffi

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	2.449µs	2.477µs ± 0.022µs	2.469µs ± 0.008µs	2.481µs	2.524µs	2.530µs	2.588µs	4.81%	1.673	3.007	0.88%	0.002µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
tags/replace_trace_tags	execution_time	[2.474µs; 2.480µs] or [-0.122%; +0.122%]	None	None	None

Group 4

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	28312a2	1773853788	julio/add-endpoint-configuration-in-ffi

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
profile_add_sample2_frames_x1000	execution_time	746.908µs	747.639µs ± 0.472µs	747.562µs ± 0.276µs	747.903µs	748.483µs	749.040µs	749.229µs	0.22%	1.018	0.885	0.06%	0.033µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
profile_add_sample2_frames_x1000	execution_time	[747.573µs; 747.704µs] or [-0.009%; +0.009%]	None	None	None

Group 5

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	28312a2	1773853788	julio/add-endpoint-configuration-in-ffi

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
benching serializing traces from their internal representation to msgpack	execution_time	14.116ms	14.175ms ± 0.028ms	14.172ms ± 0.014ms	14.186ms	14.224ms	14.269ms	14.340ms	1.19%	1.855	7.140	0.19%	0.002ms	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
benching serializing traces from their internal representation to msgpack	execution_time	[14.171ms; 14.178ms] or [-0.027%; +0.027%]	None	None	None

Group 6

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	28312a2	1773853788	julio/add-endpoint-configuration-in-ffi

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	495.234µs	496.411µs ± 0.958µs	496.209µs ± 0.317µs	496.572µs	497.146µs	500.310µs	504.352µs	1.64%	4.446	27.181	0.19%	0.068µs	1	200
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000...	throughput	1982741.993op/s	2014467.227op/s ± 3855.403op/s	2015280.980op/s ± 1288.951op/s	2016325.855op/s	2017388.556op/s	2017733.648op/s	2019249.052op/s	0.20%	-4.392	26.549	0.19%	272.618op/s	1	200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	execution_time	369.940µs	370.491µs ± 0.307µs	370.463µs ± 0.182µs	370.665µs	371.003µs	371.241µs	372.110µs	0.44%	1.175	3.862	0.08%	0.022µs	1	200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	throughput	2687374.562op/s	2699125.840op/s ± 2236.737op/s	2699323.948op/s ± 1326.592op/s	2700561.849op/s	2702304.486op/s	2703102.292op/s	2703139.461op/s	0.14%	-1.164	3.805	0.08%	158.161op/s	1	200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	execution_time	168.699µs	169.114µs ± 0.161µs	169.087µs ± 0.096µs	169.205µs	169.394µs	169.576µs	169.715µs	0.37%	0.746	0.898	0.09%	0.011µs	1	200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	throughput	5892227.864op/s	5913167.915op/s ± 5610.903op/s	5914123.760op/s ± 3366.435op/s	5917007.095op/s	5921015.064op/s	5923857.521op/s	5927715.780op/s	0.23%	-0.739	0.884	0.09%	396.751op/s	1	200
normalization/normalize_service/normalize_service/[empty string]	execution_time	36.857µs	37.044µs ± 0.118µs	37.036µs ± 0.109µs	37.151µs	37.223µs	37.266µs	37.292µs	0.69%	0.157	-1.435	0.32%	0.008µs	1	200
normalization/normalize_service/normalize_service/[empty string]	throughput	26815308.040op/s	26995095.542op/s ± 85941.661op/s	27000815.286op/s ± 79722.241op/s	27078075.055op/s	27105543.397op/s	27123902.642op/s	27131672.117op/s	0.48%	-0.152	-1.439	0.32%	6076.993op/s	1	200
normalization/normalize_service/normalize_service/test_ASCII	execution_time	46.159µs	46.276µs ± 0.053µs	46.272µs ± 0.031µs	46.306µs	46.376µs	46.429µs	46.450µs	0.38%	0.679	0.853	0.11%	0.004µs	1	200
normalization/normalize_service/normalize_service/test_ASCII	throughput	21528754.433op/s	21609300.735op/s ± 24541.561op/s	21611575.160op/s ± 14691.905op/s	21624930.047op/s	21645847.618op/s	21655003.445op/s	21664331.868op/s	0.24%	-0.671	0.838	0.11%	1735.350op/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	[496.278µs; 496.544µs] or [-0.027%; +0.027%]	None	None	None
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000...	throughput	[2013932.905op/s; 2015001.549op/s] or [-0.027%; +0.027%]	None	None	None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	execution_time	[370.448µs; 370.533µs] or [-0.011%; +0.011%]	None	None	None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	throughput	[2698815.850op/s; 2699435.830op/s] or [-0.011%; +0.011%]	None	None	None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	execution_time	[169.092µs; 169.136µs] or [-0.013%; +0.013%]	None	None	None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	throughput	[5912390.297op/s; 5913945.532op/s] or [-0.013%; +0.013%]	None	None	None
normalization/normalize_service/normalize_service/[empty string]	execution_time	[37.028µs; 37.060µs] or [-0.044%; +0.044%]	None	None	None
normalization/normalize_service/normalize_service/[empty string]	throughput	[26983184.854op/s; 27007006.229op/s] or [-0.044%; +0.044%]	None	None	None
normalization/normalize_service/normalize_service/test_ASCII	execution_time	[46.269µs; 46.284µs] or [-0.016%; +0.016%]	None	None	None
normalization/normalize_service/normalize_service/test_ASCII	throughput	[21605899.511op/s; 21612701.960op/s] or [-0.016%; +0.016%]	None	None	None

Group 7

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	28312a2	1773853788	julio/add-endpoint-configuration-in-ffi

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	1.162µs	3.140µs ± 1.418µs	2.969µs ± 0.029µs	2.995µs	3.349µs	13.642µs	15.050µs	406.83%	7.539	57.356	45.06%	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	[2.943µs; 3.336µs] or [-6.261%; +6.261%]	None	None	None

Group 8

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	28312a2	1773853788	julio/add-endpoint-configuration-in-ffi

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	3.404ms	3.443ms ± 0.031ms	3.433ms ± 0.010ms	3.447ms	3.521ms	3.547ms	3.562ms	3.77%	1.903	3.281	0.89%	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	[3.438ms; 3.447ms] or [-0.124%; +0.124%]	None	None	None

Group 9

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	28312a2	1773853788	julio/add-endpoint-configuration-in-ffi

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
ip_address/quantize_peer_ip_address_benchmark	execution_time	4.984µs	5.070µs ± 0.065µs	5.053µs ± 0.036µs	5.091µs	5.185µs	5.188µs	5.190µs	2.71%	0.826	-0.846	1.28%	0.005µs	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	[5.061µs; 5.079µs] or [-0.178%; +0.178%]	None	None	None

Group 10

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	28312a2	1773853788	julio/add-endpoint-configuration-in-ffi

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	12.976ms	13.006ms ± 0.016ms	13.005ms ± 0.009ms	13.015ms	13.032ms	13.052ms	13.113ms	0.83%	1.853	8.874	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	[13.004ms; 13.009ms] or [-0.017%; +0.017%]	None	None	None

Group 11

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	28312a2	1773853788	julio/add-endpoint-configuration-in-ffi

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	17.993µs	25.840µs ± 9.721µs	18.294µs ± 0.159µs	34.187µs	44.082µs	47.567µs	69.398µs	279.35%	1.005	0.723	37.52%	0.687µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
two way interface	execution_time	[24.493µs; 27.187µs] or [-5.214%; +5.214%]	None	None	None

Group 12

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	28312a2	1773853788	julio/add-endpoint-configuration-in-ffi

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	236.747ns	248.876ns ± 15.339ns	241.347ns ± 2.586ns	252.224ns	289.383ns	296.191ns	300.530ns	24.52%	1.882	2.611	6.15%	1.085ns	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	[246.750ns; 251.002ns] or [-0.854%; +0.854%]	None	None	None

Group 13

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	28312a2	1773853788	julio/add-endpoint-configuration-in-ffi

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo...	execution_time	185.806µs	186.276µs ± 0.199µs	186.264µs ± 0.130µs	186.410µs	186.629µs	186.748µs	186.824µs	0.30%	0.305	-0.112	0.11%	0.014µs	1	200
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo...	throughput	5352626.340op/s	5368382.813op/s ± 5740.147op/s	5368738.013op/s ± 3757.861op/s	5372174.874op/s	5377884.663op/s	5378956.558op/s	5381964.043op/s	0.25%	-0.300	-0.116	0.11%	405.890op/s	1	200
normalization/normalize_name/normalize_name/bad-name	execution_time	17.822µs	17.913µs ± 0.117µs	17.897µs ± 0.026µs	17.934µs	17.979µs	18.063µs	19.452µs	8.69%	11.408	147.017	0.65%	0.008µs	1	200
normalization/normalize_name/normalize_name/bad-name	throughput	51409350.626op/s	55828996.098op/s ± 340501.167op/s	55874709.182op/s ± 80423.762op/s	55941682.442op/s	56026828.325op/s	56092587.621op/s	56111774.655op/s	0.42%	-11.035	140.435	0.61%	24077.068op/s	1	200
normalization/normalize_name/normalize_name/good	execution_time	10.187µs	10.269µs ± 0.031µs	10.269µs ± 0.019µs	10.287µs	10.323µs	10.342µs	10.377µs	1.05%	0.142	0.513	0.30%	0.002µs	1	200
normalization/normalize_name/normalize_name/good	throughput	96369871.983op/s	97383232.437op/s ± 291317.598op/s	97383867.938op/s ± 177148.247op/s	97562919.244op/s	97866243.328op/s	98057170.834op/s	98162635.255op/s	0.80%	-0.119	0.493	0.30%	20599.265op/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	[186.248µs; 186.304µs] 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	[5367587.284op/s; 5369178.342op/s] or [-0.015%; +0.015%]	None	None	None
normalization/normalize_name/normalize_name/bad-name	execution_time	[17.896µs; 17.929µs] or [-0.091%; +0.091%]	None	None	None
normalization/normalize_name/normalize_name/bad-name	throughput	[55781805.911op/s; 55876186.285op/s] or [-0.085%; +0.085%]	None	None	None
normalization/normalize_name/normalize_name/good	execution_time	[10.265µs; 10.273µs] or [-0.041%; +0.041%]	None	None	None
normalization/normalize_name/normalize_name/good	throughput	[97342858.619op/s; 97423606.254op/s] or [-0.041%; +0.041%]	None	None	None

Group 14

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	28312a2	1773853788	julio/add-endpoint-configuration-in-ffi

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
redis/obfuscate_redis_string	execution_time	33.973µs	34.610µs ± 0.797µs	34.137µs ± 0.066µs	35.433µs	36.020µs	36.208µs	37.641µs	10.27%	1.129	-0.115	2.30%	0.056µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
redis/obfuscate_redis_string	execution_time	[34.500µs; 34.721µs] or [-0.319%; +0.319%]	None	None	None

Group 15

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	28312a2	1773853788	julio/add-endpoint-configuration-in-ffi

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
credit_card/is_card_number/	execution_time	3.892µs	3.912µs ± 0.003µs	3.912µs ± 0.001µs	3.913µs	3.917µs	3.920µs	3.940µs	0.71%	1.938	28.029	0.09%	0.000µs	1	200
credit_card/is_card_number/	throughput	253814113.137op/s	255601761.440op/s ± 218509.914op/s	255626789.690op/s ± 96955.030op/s	255708823.356op/s	255801117.297op/s	255876456.438op/s	256944151.942op/s	0.52%	-1.871	27.738	0.09%	15450.984op/s	1	200
credit_card/is_card_number/ 3782-8224-6310-005	execution_time	80.225µs	80.818µs ± 0.291µs	80.781µs ± 0.218µs	81.028µs	81.295µs	81.579µs	81.883µs	1.36%	0.527	0.124	0.36%	0.021µs	1	200
credit_card/is_card_number/ 3782-8224-6310-005	throughput	12212598.891op/s	12373683.107op/s ± 44480.502op/s	12379118.330op/s ± 33530.164op/s	12406077.770op/s	12438659.296op/s	12446910.271op/s	12464922.301op/s	0.69%	-0.507	0.081	0.36%	3145.246op/s	1	200
credit_card/is_card_number/ 378282246310005	execution_time	73.077µs	73.632µs ± 0.308µs	73.614µs ± 0.204µs	73.820µs	74.168µs	74.360µs	74.910µs	1.76%	0.615	0.635	0.42%	0.022µs	1	200
credit_card/is_card_number/ 378282246310005	throughput	13349285.730op/s	13581343.394op/s ± 56593.753op/s	13584375.252op/s ± 37676.125op/s	13621919.371op/s	13661663.019op/s	13681370.347op/s	13684242.936op/s	0.74%	-0.587	0.553	0.42%	4001.783op/s	1	200
credit_card/is_card_number/37828224631	execution_time	3.894µs	3.912µs ± 0.003µs	3.912µs ± 0.001µs	3.914µs	3.917µs	3.918µs	3.919µs	0.17%	-1.409	10.951	0.07%	0.000µs	1	200
credit_card/is_card_number/37828224631	throughput	255184508.583op/s	255603102.727op/s ± 171852.517op/s	255616333.892op/s ± 83515.219op/s	255691441.674op/s	255833751.462op/s	255903975.094op/s	256813288.701op/s	0.47%	1.432	11.123	0.07%	12151.808op/s	1	200
credit_card/is_card_number/378282246310005	execution_time	70.127µs	70.665µs ± 0.254µs	70.643µs ± 0.184µs	70.838µs	71.115µs	71.323µs	71.434µs	1.12%	0.421	-0.092	0.36%	0.018µs	1	200
credit_card/is_card_number/378282246310005	throughput	13998861.557op/s	14151542.469op/s ± 50879.147op/s	14155593.903op/s ± 37015.182op/s	14190426.844op/s	14225872.883op/s	14249402.498op/s	14259855.744op/s	0.74%	-0.403	-0.117	0.36%	3597.699op/s	1	200
credit_card/is_card_number/37828224631000521389798	execution_time	53.062µs	53.135µs ± 0.039µs	53.130µs ± 0.023µs	53.154µs	53.212µs	53.257µs	53.267µs	0.26%	0.946	1.003	0.07%	0.003µs	1	200
credit_card/is_card_number/37828224631000521389798	throughput	18773192.715op/s	18819940.143op/s ± 13784.721op/s	18821742.957op/s ± 8210.671op/s	18829560.028op/s	18838346.707op/s	18842149.627op/s	18845718.676op/s	0.13%	-0.941	0.991	0.07%	974.727op/s	1	200
credit_card/is_card_number/x371413321323331	execution_time	6.428µs	6.442µs ± 0.011µs	6.441µs ± 0.004µs	6.445µs	6.455µs	6.460µs	6.540µs	1.55%	5.459	41.913	0.18%	0.001µs	1	200
credit_card/is_card_number/x371413321323331	throughput	152895919.649op/s	155227903.331op/s ± 272263.107op/s	155260807.899op/s ± 101401.634op/s	155362256.457op/s	155472391.517op/s	155540770.726op/s	155574623.694op/s	0.20%	-5.384	41.090	0.17%	19251.909op/s	1	200
credit_card/is_card_number_no_luhn/	execution_time	3.898µs	3.913µs ± 0.003µs	3.913µs ± 0.002µs	3.915µs	3.918µs	3.919µs	3.920µs	0.17%	-0.607	3.878	0.07%	0.000µs	1	200
credit_card/is_card_number_no_luhn/	throughput	255122902.837op/s	255544808.617op/s ± 175299.529op/s	255553487.352op/s ± 116873.946op/s	255655144.324op/s	255803213.781op/s	255838398.746op/s	256533573.769op/s	0.38%	0.618	3.939	0.07%	12395.549op/s	1	200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	execution_time	64.841µs	65.144µs ± 0.125µs	65.132µs ± 0.078µs	65.208µs	65.372µs	65.510µs	65.632µs	0.77%	0.892	1.519	0.19%	0.009µs	1	200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	throughput	15236369.015op/s	15350707.380op/s ± 29518.822op/s	15353520.293op/s ± 18414.398op/s	15372236.977op/s	15390565.200op/s	15400081.087op/s	15422427.294op/s	0.45%	-0.876	1.472	0.19%	2087.296op/s	1	200
credit_card/is_card_number_no_luhn/ 378282246310005	execution_time	58.187µs	58.378µs ± 0.106µs	58.366µs ± 0.071µs	58.439µs	58.585µs	58.671µs	58.690µs	0.56%	0.636	0.095	0.18%	0.007µs	1	200
credit_card/is_card_number_no_luhn/ 378282246310005	throughput	17038561.335op/s	17129938.603op/s ± 30935.206op/s	17133285.556op/s ± 20718.684op/s	17153467.789op/s	17172159.293op/s	17180755.064op/s	17185923.010op/s	0.31%	-0.627	0.078	0.18%	2187.449op/s	1	200
credit_card/is_card_number_no_luhn/37828224631	execution_time	3.897µs	3.913µs ± 0.003µs	3.913µs ± 0.002µs	3.914µs	3.918µs	3.921µs	3.922µs	0.23%	-0.238	4.994	0.07%	0.000µs	1	200
credit_card/is_card_number_no_luhn/37828224631	throughput	255000621.040op/s	255571219.850op/s ± 186958.004op/s	255590658.162op/s ± 106149.933op/s	255682048.369op/s	255810638.335op/s	255841846.445op/s	256636658.117op/s	0.41%	0.254	5.060	0.07%	13219.927op/s	1	200
credit_card/is_card_number_no_luhn/378282246310005	execution_time	55.165µs	55.529µs ± 0.177µs	55.497µs ± 0.104µs	55.623µs	55.875µs	56.066µs	56.100µs	1.09%	0.810	0.769	0.32%	0.012µs	1	200
credit_card/is_card_number_no_luhn/378282246310005	throughput	17825329.498op/s	18008785.516op/s ± 57130.382op/s	18018907.734op/s ± 33857.171op/s	18048377.131op/s	18090223.805op/s	18117265.338op/s	18127455.845op/s	0.60%	-0.790	0.728	0.32%	4039.728op/s	1	200
credit_card/is_card_number_no_luhn/37828224631000521389798	execution_time	53.057µs	53.148µs ± 0.038µs	53.150µs ± 0.026µs	53.174µs	53.204µs	53.239µs	53.263µs	0.21%	-0.002	-0.177	0.07%	0.003µs	1	200
credit_card/is_card_number_no_luhn/37828224631000521389798	throughput	18774651.042op/s	18815217.994op/s ± 13614.532op/s	18814634.242op/s ± 9110.080op/s	18824752.758op/s	18837649.360op/s	18845322.822op/s	18847560.433op/s	0.18%	0.005	-0.179	0.07%	962.693op/s	1	200
credit_card/is_card_number_no_luhn/x371413321323331	execution_time	6.429µs	6.437µs ± 0.005µs	6.437µs ± 0.003µs	6.440µs	6.445µs	6.455µs	6.460µs	0.35%	1.160	2.577	0.08%	0.000µs	1	200
credit_card/is_card_number_no_luhn/x371413321323331	throughput	154807227.645op/s	155343212.300op/s ± 121573.736op/s	155349938.482op/s ± 77712.063op/s	155436442.078op/s	155500730.263op/s	155537739.712op/s	155539285.430op/s	0.12%	-1.152	2.546	0.08%	8596.561op/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 [-0.012%; +0.012%]	None	None	None
credit_card/is_card_number/	throughput	[255571478.067op/s; 255632044.812op/s] or [-0.012%; +0.012%]	None	None	None
credit_card/is_card_number/ 3782-8224-6310-005	execution_time	[80.777µs; 80.858µs] or [-0.050%; +0.050%]	None	None	None
credit_card/is_card_number/ 3782-8224-6310-005	throughput	[12367518.537op/s; 12379847.676op/s] or [-0.050%; +0.050%]	None	None	None
credit_card/is_card_number/ 378282246310005	execution_time	[73.589µs; 73.674µs] or [-0.058%; +0.058%]	None	None	None
credit_card/is_card_number/ 378282246310005	throughput	[13573500.044op/s; 13589186.744op/s] or [-0.058%; +0.058%]	None	None	None
credit_card/is_card_number/37828224631	execution_time	[3.912µs; 3.913µs] or [-0.009%; +0.009%]	None	None	None
credit_card/is_card_number/37828224631	throughput	[255579285.621op/s; 255626919.833op/s] or [-0.009%; +0.009%]	None	None	None
credit_card/is_card_number/378282246310005	execution_time	[70.629µs; 70.700µs] or [-0.050%; +0.050%]	None	None	None
credit_card/is_card_number/378282246310005	throughput	[14144491.108op/s; 14158593.829op/s] or [-0.050%; +0.050%]	None	None	None
credit_card/is_card_number/37828224631000521389798	execution_time	[53.130µs; 53.141µs] or [-0.010%; +0.010%]	None	None	None
credit_card/is_card_number/37828224631000521389798	throughput	[18818029.713op/s; 18821850.573op/s] or [-0.010%; +0.010%]	None	None	None
credit_card/is_card_number/x371413321323331	execution_time	[6.441µs; 6.444µs] or [-0.025%; +0.025%]	None	None	None
credit_card/is_card_number/x371413321323331	throughput	[155190170.283op/s; 155265636.379op/s] or [-0.024%; +0.024%]	None	None	None
credit_card/is_card_number_no_luhn/	execution_time	[3.913µs; 3.914µs] or [-0.010%; +0.010%]	None	None	None
credit_card/is_card_number_no_luhn/	throughput	[255520513.789op/s; 255569103.446op/s] or [-0.010%; +0.010%]	None	None	None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	execution_time	[65.126µs; 65.161µs] or [-0.027%; +0.027%]	None	None	None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	throughput	[15346616.355op/s; 15354798.405op/s] or [-0.027%; +0.027%]	None	None	None
credit_card/is_card_number_no_luhn/ 378282246310005	execution_time	[58.363µs; 58.392µs] or [-0.025%; +0.025%]	None	None	None
credit_card/is_card_number_no_luhn/ 378282246310005	throughput	[17125651.281op/s; 17134225.925op/s] or [-0.025%; +0.025%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631	execution_time	[3.912µs; 3.913µs] or [-0.010%; +0.010%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631	throughput	[255545309.269op/s; 255597130.431op/s] or [-0.010%; +0.010%]	None	None	None
credit_card/is_card_number_no_luhn/378282246310005	execution_time	[55.505µs; 55.553µs] or [-0.044%; +0.044%]	None	None	None
credit_card/is_card_number_no_luhn/378282246310005	throughput	[18000867.795op/s; 18016703.238op/s] or [-0.044%; +0.044%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631000521389798	execution_time	[53.143µs; 53.154µs] or [-0.010%; +0.010%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631000521389798	throughput	[18813331.151op/s; 18817104.837op/s] or [-0.010%; +0.010%]	None	None	None
credit_card/is_card_number_no_luhn/x371413321323331	execution_time	[6.437µs; 6.438µs] or [-0.011%; +0.011%]	None	None	None
credit_card/is_card_number_no_luhn/x371413321323331	throughput	[155326363.349op/s; 155360061.250op/s] or [-0.011%; +0.011%]	None	None	None

Group 16

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	28312a2	1773853788	julio/add-endpoint-configuration-in-ffi

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	50.684ms	50.923ms ± 0.866ms	50.779ms ± 0.040ms	50.835ms	51.116ms	54.575ms	61.124ms	20.37%	9.311	98.702	1.70%	0.061ms	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
benching deserializing traces from msgpack to their internal representation	execution_time	[50.803ms; 51.043ms] or [-0.236%; +0.236%]	None	None	None

Group 17

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	28312a2	1773853788	julio/add-endpoint-configuration-in-ffi

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	159.353µs	160.479µs ± 0.634µs	160.444µs ± 0.156µs	160.594µs	160.826µs	160.963µs	168.737µs	5.17%	11.060	142.327	0.39%	0.045µs	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	[160.391µs; 160.567µs] or [-0.055%; +0.055%]	None	None	None

Group 18

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	28312a2	1773853788	julio/add-endpoint-configuration-in-ffi

scenario	metric	min	mean ± sd	median ± mad	p75	p95	p99	max	peak_to_median_ratio	skewness	kurtosis	cv	sem	runs	sample_size
single_flag_killswitch/rules-based	execution_time	190.405ns	192.912ns ± 2.132ns	192.555ns ± 1.224ns	193.720ns	196.749ns	199.338ns	203.109ns	5.48%	1.545	3.854	1.10%	0.151ns	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
single_flag_killswitch/rules-based	execution_time	[192.617ns; 193.208ns] or [-0.153%; +0.153%]	None	None	None

Group 19

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	28312a2	1773853788	julio/add-endpoint-configuration-in-ffi

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	4.177ms	4.181ms ± 0.002ms	4.181ms ± 0.002ms	4.183ms	4.186ms	4.188ms	4.192ms	0.25%	0.798	1.435	0.06%	0.000ms	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
profile_add_sample_frames_x1000	execution_time	[4.181ms; 4.182ms] or [-0.008%; +0.008%]	None	None	None

Group 20

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	28312a2	1773853788	julio/add-endpoint-configuration-in-ffi

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	86.754µs	86.997µs ± 0.277µs	86.983µs ± 0.054µs	87.036µs	87.107µs	87.153µs	90.705µs	4.28%	12.086	159.693	0.32%	0.020µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
sql/obfuscate_sql_string	execution_time	[86.959µs; 87.036µs] or [-0.044%; +0.044%]	None	None	None

Baseline

Omitted due to size.

[hoolioh]

@danielsn, in the Rust side the timeout value was used to set the endpoint value. Should I add a dedicated value for the endpoint configuration? Is the timeout value inside the crashtracker config also used for another purpose?

[danielsn]

Yes it is https://github.com/DataDog/libdatadog/blob/main/libdd-crashtracker/src/collector/crash_handler.rs#L279

[hoolioh]

Then I guess we should use a new one for configuring just the Endpoint timeout, right?

[danielsn]

Lets do that then LGTM to ship

[dd-octo-sts]

Artifact Size Benchmark Report

aarch64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.a	100.36 MB	100.37 MB	+0% (+9.48 KB) 👌
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.so	8.70 MB	8.70 MB	0% (0 B) 👌

aarch64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.a	117.03 MB	117.04 MB	+0% (+11.04 KB) 👌
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.so	11.28 MB	11.28 MB	0% (0 B) 👌

libdatadog-x64-windows

Artifact	Baseline	Commit	Change
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.dll	27.18 MB	27.18 MB	0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.lib	76.61 KB	76.61 KB	0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.pdb	186.12 MB	186.10 MB	-0% (-16.00 KB) 👌
/libdatadog-x64-windows/debug/static/datadog_profiling_ffi.lib	917.07 MB	917.07 MB	0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.dll	9.94 MB	9.94 MB	0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.lib	76.61 KB	76.61 KB	0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.pdb	24.78 MB	24.78 MB	0% (0 B) 👌
/libdatadog-x64-windows/release/static/datadog_profiling_ffi.lib	51.46 MB	51.46 MB	0% (0 B) 👌

libdatadog-x86-windows

Artifact	Baseline	Commit	Change
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.dll	22.98 MB	22.98 MB	0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.lib	77.80 KB	77.80 KB	0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.pdb	190.31 MB	190.30 MB	-0% (-8.00 KB) 👌
/libdatadog-x86-windows/debug/static/datadog_profiling_ffi.lib	900.75 MB	900.75 MB	0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.dll	7.54 MB	7.54 MB	0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.lib	77.80 KB	77.80 KB	0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.pdb	26.52 MB	26.52 MB	0% (0 B) 👌
/libdatadog-x86-windows/release/static/datadog_profiling_ffi.lib	47.09 MB	47.09 MB	0% (0 B) 👌

x86_64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.a	87.57 MB	87.58 MB	+0% (+8.15 KB) 👌
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.so	10.22 MB	10.22 MB	0% (0 B) 👌

x86_64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.a	109.90 MB	109.91 MB	+0% (+9.35 KB) 👌
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.so	11.97 MB	11.97 MB	0% (0 B) 👌

[gyuheon0h]

pending @danielsn

[danielsn]

Meta question: We did the original changes to avoid requiring downstream to take ddcommon. Could we instead have just re-exported Endpoint?

[danielsn]

Is this guaranteed to fail for the right reason?

[hoolioh]

Another source of error could be turning CharSlice fields to String but since there is none present in the struct the only source of error is when calling build() and passing through the ensure! statement.

[danielsn]

Should we really accept a empty endpoint?

[hoolioh]

When passing an empty edpoint the builder will set the internal field to None which, if I recall correctly, was allowed by the previous implementation. However I don't have a deep knowledge about the crate so I'll blindly follow your guidance here.

[danielsn]

I'd say None shouldn't ever make sense because what would be the point of having a report that doesn't go anywhere even to a file. But I'm ok doing that as a followup PR if this is blocking other things

[danielsn]

Yes it is https://github.com/DataDog/libdatadog/blob/main/libdd-crashtracker/src/collector/crash_handler.rs#L279

[gyuheon0h]

Follow up request. Can crashtracker init fail if config has an unset url. We should be clear on the behavior; it doesn't make sense to start a crashtracker when there is nowhere for the report to go.

Can be follow up