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feat(library-config): support windows memory file#1262

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feat(library-config): support windows memory file#1262

dmehala wants to merge3 commits intomainfromdmehala/win-memfd

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dmehala commentedOct 8, 2025•
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What does this PR do?

Implement a memfd-like for Windows to store in-memory the tracer configuration. It relies on Windows API to create in-memory file that can be shared and accessed by other processes.

Main difference with the linux implementation is the anonymous file format:datadog-tracer-info-<PID>.

Motivation

@raphaelgavache and supporting service renaming on Windows.

How to test the change?

Boot a windows VM. Compile this code:

writer

// clang-cl .\writer.cc -Iinclude "C:\workspace\libdatadog\target\debug\datadog_library_config_ffi.lib" user32.lib ws2_32.lib crypt32.lib secur32.lib userenv.lib ntdll.lib ncrypt.lib advapi32.lib  -o writer.exe#include<datadog/library-config.h>#include<iostream>intmain(int argc,char *argv[]) {auto pid =GetCurrentProcessId();  std::cout <<"PID:" << pid << std::endl;structddog_TracerMetadata *builder =ddog_tracer_metadata_new();ddog_tracer_metadata_set(builder, DDOG_METADATA_KIND_RUNTIME_ID,"12");structddog_Result_TracerMemfdHandle result =ddog_tracer_metadata_store(builder);ddog_tracer_metadata_free(builder);if (result.tag == DDOG_RESULT_TRACER_MEMFD_HANDLE_ERR_TRACER_MEMFD_HANDLE) {    std::cout <<"writer.cc: err:" << (char *)result.err.message.ptr              << std::endl;return1;  }void *handle = result.ok.fd;if (handle ==nullptr) {    std::cout <<"handle is nullptr" << std::endl;return2;  }  std::cout <<"tag:" << result.tag <<" handle:" << handle << std::endl;system("pause");return0;}

reader

// clang .\reader.cc -o reader.exe#include<iostream>// clang-format off#include<windows.h>#include<psapi.h>// clang-format onstaticconstsize_t k_anon_file_size =256;voidtry_read_anon_file(int pid) {char fm[256];snprintf(fm,256,"datadog-tracer-info-%d", pid);  std::cout <<"Trying to read anonymous file:" << fm <<"..." << std::endl;  HANDLE h =OpenFileMapping(FILE_MAP_READ,FALSE, fm);if (h ==NULL) {/*std::cout << "Could not open the anonymous file" << std::endl;*/return;  }  std::cout <<"FOUND ONE!" << std::endl;void *addr =MapViewOfFile(h, FILE_MAP_READ,0,0, k_anon_file_size);if (addr ==NULL) {/*std::cout << "Could not map the file..." << std::endl;*/return;  }char *content = (char *)addr;  std::cout <<"[PID:" << pid <<"] content:" << content << std::endl;UnmapViewOfFile(addr);CloseHandle(h);return;}intmain(int argc,char *argv[]) {if (argc >=2) {int pid =std::atoi(argv[1]);try_read_anon_file(pid);return0;  }  DWORD processes[1024], sz_processes;if (!EnumProcesses(processes,sizeof(processes), &sz_processes)) {printf("EnumProcesses failed\n");return1;  }constsize_t cProcesses = sz_processes /sizeof(DWORD);for (size_t i =0; i < cProcesses; i++) {if (processes[i] !=0) {try_read_anon_file(processes[i]);    }  }return0;}

Expected result:

feat(library-config): support windows memory file

e319e5b

Implement a memfd-like for Windows to store in-memory the tracerconfiguration. It relies on Windows API to create in-memory file thatcan be shared and accessed by other processes.

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pr-commenterbot commentedOct 8, 2025•
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Benchmarks

Comparison

Benchmark execution time: 2025-10-09 09:11:49

Comparing candidate commit57a4e3d in PR branchdmehala/win-memfd with baseline commitf65f27b in branchmain.

Found 2 performance improvements and 0 performance regressions! Performance is the same for 51 metrics, 2 unstable metrics.

scenario:credit_card/is_card_number/378282246310005

🟩execution_time [-9.520µs; -9.240µs] or [-12.191%; -11.833%]
🟩throughput [+1722528.528op/s; +1774905.993op/s] or [+13.450%; +13.859%]

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	`57a4e3d`	1760000332	dmehala/win-memfd

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	243.678ns	254.091ns ± 12.849ns	247.954ns ± 2.450ns	256.289ns	285.712ns	295.484ns	298.440ns	20.36%	1.879	2.633	5.04%	0.909ns	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	[252.310ns; 255.872ns] or [-0.701%; +0.701%]	None	None	None

Group 2

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`57a4e3d`	1760000332	dmehala/win-memfd

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	34.844µs ± 0.861µs	34.439µs ± 0.056µs	34.564µs	36.649µs	36.719µs	38.419µs	11.56%	1.773	1.657	2.46%	0.061µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
redis/obfuscate_redis_string	execution_time	[34.725µs; 34.963µs] or [-0.342%; +0.342%]	None	None	None

Group 3

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`57a4e3d`	1760000332	dmehala/win-memfd

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	2.317µs	2.383µs ± 0.022µs	2.377µs ± 0.006µs	2.390µs	2.432µs	2.435µs	2.436µs	2.48%	0.290	1.665	0.91%	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	[2.380µs; 2.386µs] or [-0.126%; +0.126%]	None	None	None

Group 4

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`57a4e3d`	1760000332	dmehala/win-memfd

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	10.770ms	10.801ms ± 0.017ms	10.799ms ± 0.010ms	10.809ms	10.826ms	10.849ms	10.895ms	0.88%	1.670	6.477	0.15%	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	[10.799ms; 10.803ms] or [-0.021%; +0.021%]	None	None	None

Group 5

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`57a4e3d`	1760000332	dmehala/win-memfd

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/2597	execution_time	6.199ms	6.265ms ± 0.049ms	6.251ms ± 0.024ms	6.284ms	6.367ms	6.400ms	6.502ms	4.01%	1.513	2.699	0.78%	0.003ms	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
receiver_entry_point/report/2597	execution_time	[6.258ms; 6.272ms] or [-0.108%; +0.108%]	None	None	None

Group 6

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`57a4e3d`	1760000332	dmehala/win-memfd

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	5.012µs	5.061µs ± 0.028µs	5.067µs ± 0.026µs	5.089µs	5.097µs	5.105µs	5.164µs	1.91%	0.144	-0.750	0.55%	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	[5.057µs; 5.065µs] or [-0.077%; +0.077%]	None	None	None

Group 7

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`57a4e3d`	1760000332	dmehala/win-memfd

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	1.206µs	3.176µs ± 1.447µs	2.999µs ± 0.024µs	3.020µs	3.357µs	13.917µs	15.300µs	410.17%	7.497	56.830	45.43%	0.102µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
write only interface	execution_time	[2.975µs; 3.376µs] or [-6.313%; +6.313%]	None	None	None

Group 8

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`57a4e3d`	1760000332	dmehala/win-memfd

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	204.193µs	205.077µs ± 0.510µs	205.015µs ± 0.302µs	205.347µs	206.016µs	206.331µs	208.859µs	1.87%	2.447	13.966	0.25%	0.036µs	1	200
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo...	throughput	4787927.796op/s	4876249.090op/s ± 12054.522op/s	4877699.271op/s ± 7205.765op/s	4884234.888op/s	4890589.225op/s	4891933.028op/s	4897328.825op/s	0.40%	-2.374	13.271	0.25%	852.383op/s	1	200
normalization/normalize_name/normalize_name/bad-name	execution_time	18.521µs	18.625µs ± 0.084µs	18.618µs ± 0.062µs	18.677µs	18.788µs	18.858µs	18.888µs	1.45%	0.779	0.057	0.45%	0.006µs	1	200
normalization/normalize_name/normalize_name/bad-name	throughput	52944760.667op/s	53693652.875op/s ± 242133.872op/s	53710777.477op/s ± 179791.718op/s	53943405.888op/s	53977029.846op/s	53987035.197op/s	53992666.149op/s	0.52%	-0.759	0.008	0.45%	17121.450op/s	1	200
normalization/normalize_name/normalize_name/good	execution_time	10.865µs	10.919µs ± 0.027µs	10.919µs ± 0.019µs	10.937µs	10.967µs	10.990µs	10.995µs	0.70%	0.389	-0.116	0.25%	0.002µs	1	200
normalization/normalize_name/normalize_name/good	throughput	90950432.015op/s	91582973.571op/s ± 229823.111op/s	91583478.351op/s ± 155850.303op/s	91743729.839op/s	91936899.024op/s	92008855.366op/s	92036393.016op/s	0.49%	-0.376	-0.134	0.25%	16250.948op/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	[205.006µs; 205.148µs] or [-0.034%; +0.034%]	None	None	None
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo...	throughput	[4874578.449op/s; 4877919.731op/s] or [-0.034%; +0.034%]	None	None	None
normalization/normalize_name/normalize_name/bad-name	execution_time	[18.613µs; 18.636µs] or [-0.063%; +0.063%]	None	None	None
normalization/normalize_name/normalize_name/bad-name	throughput	[53660095.449op/s; 53727210.301op/s] or [-0.062%; +0.062%]	None	None	None
normalization/normalize_name/normalize_name/good	execution_time	[10.915µs; 10.923µs] or [-0.035%; +0.035%]	None	None	None
normalization/normalize_name/normalize_name/good	throughput	[91551122.299op/s; 91614824.844op/s] or [-0.035%; +0.035%]	None	None	None

Group 9

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`57a4e3d`	1760000332	dmehala/win-memfd

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	14.990ms	15.045ms ± 0.030ms	15.041ms ± 0.012ms	15.053ms	15.086ms	15.170ms	15.223ms	1.21%	2.502	10.015	0.20%	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	[15.041ms; 15.049ms] or [-0.027%; +0.027%]	None	None	None

Group 10

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`57a4e3d`	1760000332	dmehala/win-memfd

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	90.635µs	90.856µs ± 0.200µs	90.825µs ± 0.055µs	90.885µs	91.060µs	91.267µs	93.194µs	2.61%	8.335	92.208	0.22%	0.014µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
sql/obfuscate_sql_string	execution_time	[90.828µs; 90.883µs] or [-0.030%; +0.030%]	None	None	None

Group 11

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`57a4e3d`	1760000332	dmehala/win-memfd

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	159.239µs	159.952µs ± 0.296µs	159.913µs ± 0.162µs	160.098µs	160.386µs	161.003µs	161.967µs	1.28%	2.193	11.136	0.18%	0.021µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
benching string interning on wordpress profile	execution_time	[159.911µs; 159.993µs] or [-0.026%; +0.026%]	None	None	None

Group 12

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`57a4e3d`	1760000332	dmehala/win-memfd

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	60.015ms	60.458ms ± 2.090ms	60.181ms ± 0.077ms	60.297ms	60.432ms	71.845ms	79.790ms	32.58%	8.433	71.168	3.45%	0.148ms	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	[60.169ms; 60.748ms] or [-0.479%; +0.479%]	None	None	None

Group 13

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`57a4e3d`	1760000332	dmehala/win-memfd

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	3.894µs	3.914µs ± 0.003µs	3.914µs ± 0.001µs	3.916µs	3.918µs	3.920µs	3.920µs	0.17%	-1.736	13.909	0.07%	0.000µs	1	200
credit_card/is_card_number/	throughput	255084263.667op/s	255496193.162op/s ± 172820.815op/s	255509543.284op/s ± 96256.094op/s	255600431.800op/s	255701300.861op/s	255771951.830op/s	256787352.032op/s	0.50%	1.762	14.135	0.07%	12220.277op/s	1	200
credit_card/is_card_number/ 3782-8224-6310-005	execution_time	76.801µs	78.335µs ± 0.763µs	78.338µs ± 0.544µs	78.780µs	79.686µs	80.349µs	80.764µs	3.10%	0.476	-0.013	0.97%	0.054µs	1	200
credit_card/is_card_number/ 3782-8224-6310-005	throughput	12381774.608op/s	12766843.204op/s ± 123854.061op/s	12765193.185op/s ± 89034.450op/s	12860919.282op/s	12942775.838op/s	12999086.971op/s	13020733.993op/s	2.00%	-0.425	-0.092	0.97%	8757.805op/s	1	200
credit_card/is_card_number/ 378282246310005	execution_time	70.752µs	72.304µs ± 0.714µs	72.206µs ± 0.443µs	72.693µs	73.649µs	74.050µs	74.538µs	3.23%	0.514	0.017	0.99%	0.051µs	1	200
credit_card/is_card_number/ 378282246310005	throughput	13415896.757op/s	13831848.266op/s ± 136016.233op/s	13849190.250op/s ± 85494.556op/s	13929132.442op/s	14029822.439op/s	14103942.458op/s	14133972.365op/s	2.06%	-0.462	-0.038	0.98%	9617.800op/s	1	200
credit_card/is_card_number/37828224631	execution_time	3.895µs	3.914µs ± 0.003µs	3.914µs ± 0.001µs	3.916µs	3.919µs	3.922µs	3.923µs	0.23%	-1.052	10.715	0.07%	0.000µs	1	200
credit_card/is_card_number/37828224631	throughput	254891694.982op/s	255462830.809op/s ± 180625.508op/s	255478955.776op/s ± 95985.271op/s	255562480.236op/s	255684829.068op/s	255733007.437op/s	256711874.693op/s	0.48%	1.077	10.881	0.07%	12772.152op/s	1	200
credit_card/is_card_number/378282246310005	execution_time	67.332µs	68.708µs ± 0.704µs	68.612µs ± 0.473µs	69.164µs	69.852µs	70.751µs	71.293µs	3.91%	0.660	0.668	1.02%	0.050µs	1	200
credit_card/is_card_number/378282246310005	throughput	14026549.761op/s	14555862.450op/s ± 148255.717op/s	14574633.284op/s ± 99891.172op/s	14660053.092op/s	14768114.821op/s	14821498.917op/s	14851786.797op/s	1.90%	-0.593	0.490	1.02%	10483.262op/s	1	200
credit_card/is_card_number/37828224631000521389798	execution_time	52.761µs	52.915µs ± 0.053µs	52.913µs ± 0.031µs	52.946µs	52.998µs	53.046µs	53.083µs	0.32%	0.226	0.520	0.10%	0.004µs	1	200
credit_card/is_card_number/37828224631000521389798	throughput	18838456.646op/s	18898371.310op/s ± 18900.255op/s	18899052.213op/s ± 11024.021op/s	18909125.071op/s	18929135.351op/s	18941626.535op/s	18953304.273op/s	0.29%	-0.219	0.515	0.10%	1336.450op/s	1	200
credit_card/is_card_number/x371413321323331	execution_time	6.429µs	6.437µs ± 0.005µs	6.437µs ± 0.003µs	6.440µs	6.446µs	6.449µs	6.462µs	0.40%	1.122	2.757	0.08%	0.000µs	1	200
credit_card/is_card_number/x371413321323331	throughput	154743423.653op/s	155353531.060op/s ± 117683.953op/s	155362146.016op/s ± 82694.524op/s	155445642.727op/s	155504394.766op/s	155531065.878op/s	155541511.667op/s	0.12%	-1.114	2.714	0.08%	8321.512op/s	1	200
credit_card/is_card_number_no_luhn/	execution_time	3.894µs	3.915µs ± 0.003µs	3.914µs ± 0.002µs	3.917µs	3.920µs	3.922µs	3.923µs	0.22%	-0.933	8.001	0.08%	0.000µs	1	200
credit_card/is_card_number_no_luhn/	throughput	254909680.163op/s	255447431.150op/s ± 207984.981op/s	255466431.713op/s ± 129630.166op/s	255584777.471op/s	255686850.837op/s	255752138.105op/s	256814556.671op/s	0.53%	0.956	8.156	0.08%	14706.759op/s	1	200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	execution_time	64.933µs	65.129µs ± 0.134µs	65.077µs ± 0.057µs	65.191µs	65.367µs	65.508µs	65.922µs	1.30%	1.957	6.075	0.21%	0.009µs	1	200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	throughput	15169536.812op/s	15354310.979op/s ± 31500.870op/s	15366405.963op/s ± 13377.279op/s	15374208.996op/s	15384450.628op/s	15388501.903op/s	15400585.222op/s	0.22%	-1.931	5.883	0.20%	2227.448op/s	1	200
credit_card/is_card_number_no_luhn/ 378282246310005	execution_time	58.613µs	58.977µs ± 0.208µs	58.936µs ± 0.127µs	59.079µs	59.355µs	59.566µs	59.689µs	1.28%	0.924	0.814	0.35%	0.015µs	1	200
credit_card/is_card_number_no_luhn/ 378282246310005	throughput	16753436.327op/s	16956039.374op/s ± 59536.881op/s	16967590.206op/s ± 36543.407op/s	16998394.935op/s	17032640.588op/s	17051270.739op/s	17061044.417op/s	0.55%	-0.904	0.764	0.35%	4209.893op/s	1	200
credit_card/is_card_number_no_luhn/37828224631	execution_time	3.895µs	3.916µs ± 0.003µs	3.916µs ± 0.002µs	3.917µs	3.920µs	3.923µs	3.924µs	0.22%	-1.285	10.269	0.08%	0.000µs	1	200
credit_card/is_card_number_no_luhn/37828224631	throughput	254811219.792op/s	255382312.899op/s ± 193149.680op/s	255378363.289op/s ± 115645.377op/s	255499067.429op/s	255624459.716op/s	255765387.542op/s	256711240.647op/s	0.52%	1.309	10.437	0.08%	13657.745op/s	1	200
credit_card/is_card_number_no_luhn/378282246310005	execution_time	55.367µs	55.690µs ± 0.197µs	55.654µs ± 0.117µs	55.795µs	56.042µs	56.326µs	56.367µs	1.28%	0.987	0.997	0.35%	0.014µs	1	200
credit_card/is_card_number_no_luhn/378282246310005	throughput	17740799.818op/s	17956849.676op/s ± 63334.274op/s	17968025.911op/s ± 37912.448op/s	18001121.920op/s	18039800.763op/s	18052501.379op/s	18061256.558op/s	0.52%	-0.966	0.936	0.35%	4478.409op/s	1	200
credit_card/is_card_number_no_luhn/37828224631000521389798	execution_time	52.789µs	52.928µs ± 0.046µs	52.927µs ± 0.033µs	52.963µs	53.001µs	53.024µs	53.051µs	0.23%	-0.284	0.264	0.09%	0.003µs	1	200
credit_card/is_card_number_no_luhn/37828224631000521389798	throughput	18849729.656op/s	18893555.216op/s ± 16531.606op/s	18893771.668op/s ± 11833.844op/s	18904086.118op/s	18924513.112op/s	18935655.090op/s	18943258.826op/s	0.26%	0.290	0.270	0.09%	1168.961op/s	1	200
credit_card/is_card_number_no_luhn/x371413321323331	execution_time	6.428µs	6.436µs ± 0.003µs	6.435µs ± 0.002µs	6.438µs	6.442µs	6.443µs	6.444µs	0.13%	0.268	-0.665	0.05%	0.000µs	1	200
credit_card/is_card_number_no_luhn/x371413321323331	throughput	155184387.631op/s	155381394.056op/s ± 81404.298op/s	155393609.112op/s ± 59217.438op/s	155442039.072op/s	155501463.032op/s	155539675.286op/s	155566142.557op/s	0.11%	-0.266	-0.666	0.05%	5756.153op/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	[3.914µs; 3.914µs] or [-0.009%; +0.009%]	None	None	None
credit_card/is_card_number/	throughput	[255472241.859op/s; 255520144.465op/s] or [-0.009%; +0.009%]	None	None	None
credit_card/is_card_number/ 3782-8224-6310-005	execution_time	[78.229µs; 78.441µs] or [-0.135%; +0.135%]	None	None	None
credit_card/is_card_number/ 3782-8224-6310-005	throughput	[12749678.223op/s; 12784008.186op/s] or [-0.134%; +0.134%]	None	None	None
credit_card/is_card_number/ 378282246310005	execution_time	[72.205µs; 72.403µs] or [-0.137%; +0.137%]	None	None	None
credit_card/is_card_number/ 378282246310005	throughput	[13812997.725op/s; 13850698.808op/s] or [-0.136%; +0.136%]	None	None	None
credit_card/is_card_number/37828224631	execution_time	[3.914µs; 3.915µs] or [-0.010%; +0.010%]	None	None	None
credit_card/is_card_number/37828224631	throughput	[255437797.851op/s; 255487863.767op/s] or [-0.010%; +0.010%]	None	None	None
credit_card/is_card_number/378282246310005	execution_time	[68.610µs; 68.806µs] or [-0.142%; +0.142%]	None	None	None
credit_card/is_card_number/378282246310005	throughput	[14535315.634op/s; 14576409.267op/s] or [-0.141%; +0.141%]	None	None	None
credit_card/is_card_number/37828224631000521389798	execution_time	[52.907µs; 52.922µs] or [-0.014%; +0.014%]	None	None	None
credit_card/is_card_number/37828224631000521389798	throughput	[18895751.917op/s; 18900990.704op/s] or [-0.014%; +0.014%]	None	None	None
credit_card/is_card_number/x371413321323331	execution_time	[6.436µs; 6.438µs] or [-0.011%; +0.011%]	None	None	None
credit_card/is_card_number/x371413321323331	throughput	[155337221.196op/s; 155369840.924op/s] or [-0.010%; +0.010%]	None	None	None
credit_card/is_card_number_no_luhn/	execution_time	[3.914µs; 3.915µs] or [-0.011%; +0.011%]	None	None	None
credit_card/is_card_number_no_luhn/	throughput	[255418606.432op/s; 255476255.868op/s] or [-0.011%; +0.011%]	None	None	None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	execution_time	[65.110µs; 65.147µs] or [-0.029%; +0.029%]	None	None	None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	throughput	[15349945.261op/s; 15358676.696op/s] or [-0.028%; +0.028%]	None	None	None
credit_card/is_card_number_no_luhn/ 378282246310005	execution_time	[58.948µs; 59.006µs] or [-0.049%; +0.049%]	None	None	None
credit_card/is_card_number_no_luhn/ 378282246310005	throughput	[16947788.135op/s; 16964290.613op/s] or [-0.049%; +0.049%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631	execution_time	[3.915µs; 3.916µs] or [-0.010%; +0.010%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631	throughput	[255355544.211op/s; 255409081.587op/s] or [-0.010%; +0.010%]	None	None	None
credit_card/is_card_number_no_luhn/378282246310005	execution_time	[55.662µs; 55.717µs] or [-0.049%; +0.049%]	None	None	None
credit_card/is_card_number_no_luhn/378282246310005	throughput	[17948072.155op/s; 17965627.197op/s] or [-0.049%; +0.049%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631000521389798	execution_time	[52.922µs; 52.935µs] or [-0.012%; +0.012%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631000521389798	throughput	[18891264.095op/s; 18895846.338op/s] or [-0.012%; +0.012%]	None	None	None
credit_card/is_card_number_no_luhn/x371413321323331	execution_time	[6.435µs; 6.436µs] or [-0.007%; +0.007%]	None	None	None
credit_card/is_card_number_no_luhn/x371413321323331	throughput	[155370112.203op/s; 155392675.909op/s] or [-0.007%; +0.007%]	None	None	None

Group 14

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`57a4e3d`	1760000332	dmehala/win-memfd

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	534.293µs	536.214µs ± 1.613µs	535.642µs ± 0.505µs	536.584µs	539.758µs	542.076µs	543.089µs	1.39%	1.833	3.376	0.30%	0.114µs	1	200
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000...	throughput	1841319.225op/s	1864942.381op/s ± 5581.088op/s	1866917.141op/s ± 1758.931op/s	1868310.025op/s	1870249.906op/s	1871188.823op/s	1871632.438op/s	0.25%	-1.815	3.289	0.30%	394.643op/s	1	200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	execution_time	383.170µs	384.020µs ± 0.341µs	384.000µs ± 0.214µs	384.216µs	384.616µs	384.892µs	385.006µs	0.26%	0.297	0.076	0.09%	0.024µs	1	200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	throughput	2597365.186op/s	2604030.495op/s ± 2310.183op/s	2604167.129op/s ± 1448.625op/s	2605563.826op/s	2607644.066op/s	2608837.685op/s	2609807.038op/s	0.22%	-0.292	0.072	0.09%	163.355op/s	1	200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	execution_time	190.184µs	190.731µs ± 0.287µs	190.708µs ± 0.191µs	190.911µs	191.158µs	191.293µs	192.500µs	0.94%	1.282	6.026	0.15%	0.020µs	1	200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	throughput	5194806.579op/s	5243009.752op/s ± 7873.261op/s	5243615.696op/s ± 5259.026op/s	5248688.938op/s	5254671.459op/s	5257595.749op/s	5258077.216op/s	0.28%	-1.254	5.828	0.15%	556.724op/s	1	200
normalization/normalize_service/normalize_service/[empty string]	execution_time	36.876µs	37.077µs ± 0.093µs	37.097µs ± 0.061µs	37.149µs	37.198µs	37.220µs	37.255µs	0.42%	-0.504	-0.687	0.25%	0.007µs	1	200
normalization/normalize_service/normalize_service/[empty string]	throughput	26842216.870op/s	26970868.760op/s ± 67517.638op/s	26956111.884op/s ± 44589.234op/s	27016028.462op/s	27097418.737op/s	27115784.405op/s	27117545.307op/s	0.60%	0.512	-0.679	0.25%	4774.218op/s	1	200
normalization/normalize_service/normalize_service/test_ASCII	execution_time	46.281µs	46.823µs ± 0.217µs	46.836µs ± 0.145µs	46.964µs	47.109µs	47.196µs	48.096µs	2.69%	0.713	4.767	0.46%	0.015µs	1	200
normalization/normalize_service/normalize_service/test_ASCII	throughput	20791821.883op/s	21357697.950op/s ± 98479.704op/s	21350874.621op/s ± 66468.001op/s	21426283.411op/s	21522641.771op/s	21573856.722op/s	21607227.185op/s	1.20%	-0.629	4.283	0.46%	6963.567op/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	[535.991µs; 536.438µs] or [-0.042%; +0.042%]	None	None	None
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000...	throughput	[1864168.896op/s; 1865715.866op/s] or [-0.041%; +0.041%]	None	None	None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	execution_time	[383.973µs; 384.068µs] or [-0.012%; +0.012%]	None	None	None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	throughput	[2603710.326op/s; 2604350.664op/s] or [-0.012%; +0.012%]	None	None	None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	execution_time	[190.691µs; 190.770µs] or [-0.021%; +0.021%]	None	None	None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	throughput	[5241918.594op/s; 5244100.911op/s] or [-0.021%; +0.021%]	None	None	None
normalization/normalize_service/normalize_service/[empty string]	execution_time	[37.064µs; 37.090µs] or [-0.035%; +0.035%]	None	None	None
normalization/normalize_service/normalize_service/[empty string]	throughput	[26961511.464op/s; 26980226.055op/s] or [-0.035%; +0.035%]	None	None	None
normalization/normalize_service/normalize_service/test_ASCII	execution_time	[46.793µs; 46.853µs] or [-0.064%; +0.064%]	None	None	None
normalization/normalize_service/normalize_service/test_ASCII	throughput	[21344049.611op/s; 21371346.290op/s] or [-0.064%; +0.064%]	None	None	None

Group 15

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	`57a4e3d`	1760000332	dmehala/win-memfd

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	17.804µs	26.222µs ± 10.123µs	18.355µs ± 0.198µs	35.169µs	45.137µs	50.344µs	70.400µs	283.55%	0.960	0.510	38.51%	0.716µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
two way interface	execution_time	[24.819µs; 27.625µs] or [-5.350%; +5.350%]	None	None	None

Baseline

Omitted due to size.

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codecov-commenter commentedOct 8, 2025•
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Codecov Report

❌ Patch coverage is0% with11 lines in your changes missing coverage. Please review.
✅ Project coverage is 71.80%. Comparing base (f65f27b) to head (57a4e3d).

Additional details and impacted files

@@            Coverage Diff             @@##             main    #1262      +/-   ##==========================================- Coverage   71.85%   71.80%   -0.05%==========================================  Files         356      356                Lines       56685    56692       +7     ==========================================- Hits        40731    40709      -22- Misses      15954    15983      +29

Components	Coverage Δ
datadog-crashtracker	`49.28% <ø> (-0.05%)`	⬇️
datadog-crashtracker-ffi	`5.93% <ø> (ø)`
datadog-alloc	`98.73% <ø> (ø)`
data-pipeline	`88.01% <ø> (ø)`
data-pipeline-ffi	`88.19% <ø> (ø)`
ddcommon	`84.54% <ø> (ø)`
ddcommon-ffi	`73.84% <ø> (ø)`
ddtelemetry	`59.49% <ø> (+0.03%)`	⬆️
ddtelemetry-ffi	`21.24% <ø> (ø)`
dogstatsd-client	`83.26% <ø> (ø)`
datadog-ipc	`82.39% <ø> (ø)`
datadog-profiling	`76.90% <ø> (ø)`
datadog-profiling-ffi	`62.12% <ø> (ø)`
datadog-sidecar	`37.01% <ø> (ø)`
datdog-sidecar-ffi	`11.03% <ø> (ø)`
spawn-worker	`55.35% <ø> (ø)`
tinybytes	`92.22% <ø> (ø)`
datadog-trace-normalization	`98.24% <ø> (ø)`
datadog-trace-obfuscation	`94.17% <ø> (ø)`
datadog-trace-protobuf	`59.65% <ø> (ø)`
datadog-trace-utils	`89.84% <ø> (ø)`
datadog-tracer-flare	`54.52% <ø> (ø)`
datadog-log	`76.31% <ø> (ø)`

🚀 New features to boost your workflow:

❄️Test Analytics: Detect flaky tests, report on failures, and find test suite problems.

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datadog-officialbot commentedOct 8, 2025•
edited by datadog-datadog-prod-us1bot
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✅ Tests

🎉 All green!

❄️ No newflaky tests detected
🧪 Alltests passed

_{This comment will be updated automatically if new data arrives.
🔗 Commit SHA:57a4e3d |Docs | Was this helpful? Give usfeedback!}

dmehala added2 commits

October 9, 2025 10:45

fix CI

cb602eb

fix CI 2

57a4e3d

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dd-octo-stsbot commentedOct 9, 2025•
edited
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Artifact Size Benchmark Report

aarch64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.so	7.25 MB	7.25 MB	0% (0 B) 👌
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.a	71.31 MB	71.31 MB	+0% (+1.36 KB) 👌

aarch64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.a	83.64 MB	83.64 MB	+0% (+816 B) 👌
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.so	9.20 MB	9.20 MB	+0% (+72 B) 👌

libdatadog-x64-windows

Artifact	Baseline	Commit	Change
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.dll	18.50 MB	18.59 MB	+.47% (+90.00 KB) 🔍
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.lib	65.77 KB	65.77 KB	0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.pdb	125.68 MB	126.48 MB	+.64% (+824.00 KB) 🔍
/libdatadog-x64-windows/debug/static/datadog_profiling_ffi.lib	656.43 MB	660.64 MB	+.64% (+4.21 MB) 🔍
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.dll	5.92 MB	5.93 MB	+.21% (+13.00 KB) 🔍
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.lib	65.77 KB	65.77 KB	0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.pdb	17.44 MB	17.52 MB	+.49% (+88.00 KB) 🔍
/libdatadog-x64-windows/release/static/datadog_profiling_ffi.lib	32.40 MB	32.56 MB	+.49% (+163.06 KB) 🔍

libdatadog-x86-windows

Artifact	Baseline	Commit	Change
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.dll	15.78 MB	15.85 MB	+.47% (+76.00 KB) 🔍
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.lib	66.79 KB	66.79 KB	0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.pdb	128.00 MB	128.86 MB	+.67% (+880.00 KB) 🔍
/libdatadog-x86-windows/debug/static/datadog_profiling_ffi.lib	645.48 MB	649.56 MB	+.63% (+4.07 MB) 🔍
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.dll	4.53 MB	4.54 MB	+.22% (+10.50 KB) 🔍
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.lib	66.79 KB	66.79 KB	0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.pdb	18.57 MB	18.66 MB	+.46% (+88.00 KB) 🔍
/libdatadog-x86-windows/release/static/datadog_profiling_ffi.lib	30.42 MB	30.60 MB	+.59% (+183.87 KB) 🔍

x86_64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.a	63.91 MB	63.91 MB	+0% (+1.07 KB) 👌
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.so	8.55 MB	8.55 MB	0% (0 B) 👌

x86_64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.a	78.37 MB	78.37 MB	+0% (+816 B) 👌
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.so	9.90 MB	9.90 MB	0% (0 B) 👌

dmehala marked this pull request as ready for review

October 12, 2025 17:47

dmehala requested review froma team ascode owners

October 12, 2025 17:47

gleocadie reviewed

Oct 14, 2025

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I might have missed it, but do we have test running in CI for that ?

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Not a windows dev, but if you are writing a null byte down below on line 173, shouldn't this bebuf.len() + 1?

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datadog-library-config/src/tracer_metadata.rs

		}

		// EEEEEEEEEHHHH can this be outside of `unsafe`?
		let dest = addr.Valueas*mutu8;

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pimluOct 23, 2025•
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Casting to a pointer is safe, but actually using it (like as incopy_nonoverlapping) is unsafe. In practice though, pointer casting gets put into the unsafe code since, how else do you know the pointer is safe to use lol

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		)
		.context("failed to create a memory file mapping")?;

		let addr =MapViewOfFile(handle,FILE_MAP_WRITE,0,0, buf.len());

Movatterモバイル変換

feat(library-config): support windows memory file#1262

Are you sure you want to change the base?

feat(library-config): support windows memory file#1262

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dmehala commentedOct 14, 2025

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dmehala commentedOct 8, 2025•
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