[crashtracking] Allow runtimes to register runtime stack collection callbacks

[gyuheon0h]

What does this PR do?

This PR allows runtimes to register a callback to extract runtime stack. They can choose either to emit frames frame by frame, or to dump a whole stacktrace string. The important contract is that the logic to retrieve the runtime stack is happening within a fork of the crashing process, from a signal handler, so it must be async-signal-safe.

Currently, we add runtime stacks as a new runtime_stacks field in the Experimental field. If runtimes choose to emit frames one by one using ddog_RuntimeStackFrame, the runtime_stacks field will be nicely propagated. If they choose to dump the whole traceback string, additional parsing will have to be implemented in the Receiver side appropriate for each different runtime's style/syntax of tracebacks.

Motivation

Current crash tracking captures only native stack traces, which are insufficient for applications using interpreted languages. When a Python/Ruby/PHP application crashes, developers need visibility into both:

1. The native call stack (C/C++ level)
2. The runtime call stack (Python/Ruby/PHP script level)

Without runtime stack traces, debugging crashes in interpreted languages is significantly hampered as the native stack only shows interpreter internals and native extension modules, not the actual application code execution path.

Additional Notes

Anything else we should know when reviewing?

How to test the change?

Unit tests.

There is a very dummy implementation of dd-trace-py consuming this API in this experimental PR: DataDog/dd-trace-py#14765

By triggering a crash with the tracer and agent attached, we can see outputted Experimental fields:

1. Frame by Frame

{
  "ucontext": "ucontext_t { uc_flags: 7, uc_link: 0x0, uc_stack: stack_t { ss_sp: 0x743deadc0000, ss_flags: 0, ss_size: 65536 }, uc_mcontext: mcontext_t { gregs: [0, 127809331044922, 0, 127809325475264, 140726899625856, 140726899626064, 1, 0, 0, -1, 0, 4294967295, 127809325530248, 0, 140726899625160, 140726899625368, 127809330854360, 66179, 12103423998558259, 4, 14, 0, 0], fpregs: 0x743deadcf540, __private: [0, 0, 0, 0, 0, 0, 0, 0] }, uc_sigmask: sigset_t { __val: [0, 11, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] }, __private: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 127, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 160, 31, 0, 0, 255, 255, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 255, 255, 255, 255, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 99, 0, 116, 0, 111, 0, 114, 0, 0, 0, 0, 0, 0, 0, 0, 0, 116, 0, 114, 0, 0, 0, 0, 0, 99, 0, 111, 0, 0, 0, 0, 0, 105, 0, 101, 0, 111, 0, 32, 0, 0, 0, 0, 0, 0, 0, 0, 0, 117, 0, 0, 0, 99, 0, 0, 0, 104, 0, 0, 0, 32, 0, 0, 0, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 32, 0, 0, 0, 111, 0, 0, 0, 114, 0, 0, 0, 32, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 128, 199, 48, 49, 93, 136, 85, 59, 0, 0, 0, 0, 0, 0, 0, 0, 100, 171, 99, 130, 7, 91, 229, 191, 0, 0, 0, 0, 0, 0, 0, 0, 27, 99, 108, 213, 49, 161, 233, 63, 0, 0, 0, 0, 0, 0, 0, 0, 233, 69, 72, 155, 91, 73, 242, 191, 0, 0, 0, 0, 0, 0, 0, 0, 52, 121, 227, 150, 79, 248, 140, 67, 143, 13, 128, 21, 35, 58, 40, 13, 211, 19, 203, 193, 101, 194, 7, 72, 227, 201, 177, 122, 54, 74, 46, 67, 23, 38, 50, 64, 173, 107, 173, 144, 4, 8, 252, 226, 102, 193, 248, 241, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 83, 88, 80, 70, 140, 10, 0, 0, 255, 2, 0, 0, 0, 0, 0, 0, 136, 10, 0, 0, 0, 0, 0, 0] }",
  "runtime_stack": {
    "format": "Datadog Runtime Callback 1.0",
    "frames": [
      {
        "function": "string_at",
        "file": "/home/bits/.pyenv/versions/3.11.13/lib/python3.11/ctypes/__init__.py",
        "line": 519
      },
      {
        "function": "func16",
        "file": "tests/internal/crashtracker/test_crashtracker.py",
        "line": 724
      },
     ........
      {
        "function": "func2",
        "file": "tests/internal/crashtracker/test_crashtracker.py",
        "line": 682
      },
      {
        "function": "func1",
        "file": "tests/internal/crashtracker/test_crashtracker.py",
        "line": 679
      },
      {
        "function": "<module>",
        "file": "tests/internal/crashtracker/test_crashtracker.py",
        "line": 734
      }
    ],
    "runtime_type": "python"
  }
}

2. Whole traceback string

{
  "ucontext": "ucontext_t { uc_flags: 7, uc_link: 0x0, uc_stack: stack_t { ss_sp: 0x7c4c9c841000, ss_flags: 0, ss_size: 65536 }, uc_mcontext: mcontext_t { gregs: [0, 136668534166074, 0, 136668528596416, 140724573444400, 140724573444608, 1, 0, 0, -1, 0, 4294967295, 136668528651400, 0, 140724573443704, 140724573443912, 136668533975512, 66179, 12103423998558259, 4, 14, 0, 0], fpregs: 0x7c4c9c850540, __private: [0, 0, 0, 0, 0, 0, 0, 0] }, uc_sigmask: sigset_t { __val: [0, 11, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] }, __private: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 127, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 160, 31, 0, 0, 255, 255, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 255, 255, 255, 255, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 99, 0, 116, 0, 111, 0, 114, 0, 0, 0, 0, 0, 0, 0, 0, 0, 116, 0, 114, 0, 0, 0, 0, 0, 99, 0, 111, 0, 0, 0, 0, 0, 105, 0, 101, 0, 111, 0, 32, 0, 0, 0, 0, 0, 0, 0, 0, 0, 117, 0, 0, 0, 99, 0, 0, 0, 104, 0, 0, 0, 32, 0, 0, 0, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 32, 0, 0, 0, 111, 0, 0, 0, 114, 0, 0, 0, 32, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 128, 199, 48, 49, 93, 136, 85, 59, 0, 0, 0, 0, 0, 0, 0, 0, 100, 171, 99, 130, 7, 91, 229, 191, 0, 0, 0, 0, 0, 0, 0, 0, 27, 99, 108, 213, 49, 161, 233, 63, 0, 0, 0, 0, 0, 0, 0, 0, 233, 69, 72, 155, 91, 73, 242, 191, 0, 0, 0, 0, 0, 0, 0, 0, 255, 52, 127, 42, 141, 178, 13, 152, 156, 26, 175, 206, 42, 181, 80, 159, 182, 24, 207, 207, 28, 16, 244, 61, 0, 111, 67, 149, 212, 73, 16, 112, 165, 200, 182, 175, 115, 89, 172, 247, 213, 71, 73, 142, 243, 74, 61, 65, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 83, 88, 80, 70, 140, 10, 0, 0, 255, 2, 0, 0, 0, 0, 0, 0, 136, 10, 0, 0, 0, 0, 0, 0] }",
  "runtime_stack": {
    "format": "Datadog Runtime Callback 1.0",
    "stacktrace_string": "Current thread 0x00007c4c9f46db80 (most recent call first):\n  File \"/home/bits/.pyenv/versions/3.11.13/lib/python3.11/ctypes/__init__.py\", line 519 in string_at\n  File \"tests/internal/crashtracker/test_crashtracker.py\", line 724 in func16\n  File \"tests/internal/crashtracker/test_crashtracker.py\", line 721 in func15\n  File \"tests/internal/crashtracker/test_crashtracker.py\", line 718 in func14\n  File \"tests/internal/crashtracker/test_crashtracker.py\", line 715 in func13\n  File \"tests/internal/crashtracker/test_crashtracker.py\", line 712 in func12\n  File \"tests/internal/crashtracker/test_crashtracker.py\", line 709 in func11\n  File \"tests/internal/crashtracker/test_crashtracker.py\", line 706 in func10\n  File \"tests/internal/crashtracker/test_crashtracker.py\", line 703 in func9\n  File \"tests/internal/crashtracker/test_crashtracker.py\", line 700 in func8\n  File \"tests/internal/crashtracker/test_crashtracker.py\", line 697 in func7\n  File \"tests/internal/crashtracker/test_crashtracker.py\", line 694 in func6\n  File \"tests/internal/crashtracker/test_crashtracker.py\", line 691 in func5\n  File \"tests/internal/crashtracker/test_crashtracker.py\", line 688 in func4\n  File \"tests/internal/crashtracker/test_crashtracker.py\", line 685 in func3\n  File \"tests/internal/crashtracker/test_crashtracker.py\", line 682 in func2\n  File \"tests/internal/crashtracker/test_crashtracker.py\", line 679 in func1\n  File \"tests/internal/crashtracker/test_crashtracker.py\", line 734 in <module>",
    "runtime_type": "python"
  }
}

[datadog-official]

✅ Tests

🎉 All green!

❄️ No new flaky tests detected
🧪 All tests passed

_{This comment will be updated automatically if new data arrives.
🔗 Commit SHA: 2e9dcc8 | Docs | Datadog PR Page | Was this helpful? Give us feedback!}

[pr-commenter]

Benchmarks

Comparison

Benchmark execution time: 2025-11-03 15:31:04

Comparing candidate commit 2e9dcc8 in PR branch gyuheon0h/prof-12432-runtime-stacks with baseline commit c4a66e2 in branch main.

Found 12 performance improvements and 4 performance regressions! Performance is the same for 39 metrics, 2 unstable metrics.

scenario:benching serializing traces from their internal representation to msgpack

• 🟩 execution_time [-625.379µs; -612.724µs] or [-4.207%; -4.122%]

scenario:credit_card/is_card_number/37828224631000521389798

• 🟩 execution_time [-6.504µs; -6.475µs] or [-12.460%; -12.405%]
• 🟩 throughput [+2713239.202op/s; +2726826.716op/s] or [+14.162%; +14.233%]

scenario:credit_card/is_card_number/x371413321323331

• 🟥 execution_time [+592.987ns; +597.461ns] or [+9.826%; +9.900%]
• 🟥 throughput [-14930277.586op/s; -14822255.524op/s] or [-9.010%; -8.945%]

scenario:credit_card/is_card_number_no_luhn/ 378282246310005

• 🟩 execution_time [-4.579µs; -4.541µs] or [-7.896%; -7.831%]
• 🟩 throughput [+1465933.630op/s; +1477279.660op/s] or [+8.501%; +8.567%]

scenario:credit_card/is_card_number_no_luhn/378282246310005

• 🟩 execution_time [-4.622µs; -4.569µs] or [-8.433%; -8.335%]
• 🟩 throughput [+1660511.881op/s; +1678442.798op/s] or [+9.101%; +9.200%]

scenario:credit_card/is_card_number_no_luhn/37828224631000521389798

• 🟩 execution_time [-6.515µs; -6.487µs] or [-12.479%; -12.426%]
• 🟩 throughput [+2717937.496op/s; +2730943.931op/s] or [+14.190%; +14.258%]

scenario:credit_card/is_card_number_no_luhn/x371413321323331

• 🟥 execution_time [+586.268ns; +590.452ns] or [+9.715%; +9.785%]
• 🟥 throughput [-14769518.005op/s; -14672312.861op/s] or [-8.913%; -8.854%]

scenario:normalization/normalize_service/normalize_service/[empty string]

• 🟩 execution_time [-1.869µs; -1.815µs] or [-4.840%; -4.700%]
• 🟩 throughput [+1278007.524op/s; +1317058.691op/s] or [+4.936%; +5.087%]

scenario:redis/obfuscate_redis_string

• 🟩 execution_time [-2.239µs; -1.856µs] or [-6.427%; -5.326%]

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	2e9dcc8	1762183029	gyuheon0h/prof-12432-runtime-stacks

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	10.677ms	10.713ms ± 0.014ms	10.712ms ± 0.008ms	10.721ms	10.736ms	10.762ms	10.784ms	0.67%	1.244	4.411	0.13%	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	[10.711ms; 10.715ms] or [-0.019%; +0.019%]	None	None	None

Group 2

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	2e9dcc8	1762183029	gyuheon0h/prof-12432-runtime-stacks

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	240.472ns	253.745ns ± 13.663ns	245.875ns ± 3.786ns	262.914ns	283.865ns	286.958ns	288.379ns	17.29%	1.063	-0.112	5.37%	0.966ns	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	[251.852ns; 255.639ns] or [-0.746%; +0.746%]	None	None	None

Group 3

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	2e9dcc8	1762183029	gyuheon0h/prof-12432-runtime-stacks

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	2.460µs	2.487µs ± 0.021µs	2.482µs ± 0.009µs	2.494µs	2.551µs	2.556µs	2.557µs	3.02%	1.969	3.752	0.85%	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	[2.484µs; 2.490µs] or [-0.118%; +0.118%]	None	None	None

Group 4

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	2e9dcc8	1762183029	gyuheon0h/prof-12432-runtime-stacks

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	86.220µs	86.415µs ± 0.156µs	86.390µs ± 0.047µs	86.438µs	86.652µs	87.035µs	87.680µs	1.49%	4.172	24.876	0.18%	0.011µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
sql/obfuscate_sql_string	execution_time	[86.393µs; 86.437µs] or [-0.025%; +0.025%]	None	None	None

Group 5

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	2e9dcc8	1762183029	gyuheon0h/prof-12432-runtime-stacks

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	32.262µs	32.793µs ± 0.950µs	32.343µs ± 0.038µs	32.492µs	34.750µs	34.815µs	37.070µs	14.62%	1.861	2.195	2.89%	0.067µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
redis/obfuscate_redis_string	execution_time	[32.662µs; 32.925µs] or [-0.402%; +0.402%]	None	None	None

Group 6

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	2e9dcc8	1762183029	gyuheon0h/prof-12432-runtime-stacks

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	1.247µs	3.267µs ± 1.453µs	3.040µs ± 0.028µs	3.064µs	3.711µs	14.526µs	14.897µs	389.98%	7.308	54.655	44.38%	0.103µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
write only interface	execution_time	[3.066µs; 3.468µs] or [-6.166%; +6.166%]	None	None	None

Group 7

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	2e9dcc8	1762183029	gyuheon0h/prof-12432-runtime-stacks

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	4.980µs	5.048µs ± 0.047µs	5.031µs ± 0.038µs	5.088µs	5.140µs	5.144µs	5.152µs	2.41%	0.417	-0.963	0.92%	0.003µs	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	[5.041µs; 5.054µs] or [-0.128%; +0.128%]	None	None	None

Group 8

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	2e9dcc8	1762183029	gyuheon0h/prof-12432-runtime-stacks

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	121.474µs	123.030µs ± 1.838µs	122.680µs ± 0.387µs	123.086µs	124.948µs	131.090µs	138.276µs	12.71%	5.616	37.925	1.49%	0.130µs	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	[122.776µs; 123.285µs] or [-0.207%; +0.207%]	None	None	None

Group 9

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	2e9dcc8	1762183029	gyuheon0h/prof-12432-runtime-stacks

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	162.247µs	163.264µs ± 0.493µs	163.244µs ± 0.151µs	163.385µs	163.644µs	163.989µs	169.153µs	3.62%	8.494	99.775	0.30%	0.035µs	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	[163.196µs; 163.333µs] or [-0.042%; +0.042%]	None	None	None

Group 10

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	2e9dcc8	1762183029	gyuheon0h/prof-12432-runtime-stacks

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	3.915µs ± 0.003µs	3.915µs ± 0.002µs	3.917µs	3.921µs	3.923µs	3.925µs	0.24%	-1.178	9.687	0.08%	0.000µs	1	200
credit_card/is_card_number/	throughput	254791145.554op/s	255402893.265op/s ± 202557.880op/s	255400981.040op/s ± 127599.983op/s	255529743.667op/s	255668865.474op/s	255739576.927op/s	256782629.233op/s	0.54%	1.203	9.858	0.08%	14323.005op/s	1	200
credit_card/is_card_number/ 3782-8224-6310-005	execution_time	77.892µs	78.620µs ± 0.620µs	78.517µs ± 0.409µs	78.910µs	79.782µs	80.205µs	82.756µs	5.40%	2.170	9.616	0.79%	0.044µs	1	200
credit_card/is_card_number/ 3782-8224-6310-005	throughput	12083786.119op/s	12720111.866op/s ± 98612.346op/s	12736107.502op/s ± 66340.539op/s	12802675.022op/s	12825892.872op/s	12834463.854op/s	12838308.380op/s	0.80%	-2.015	8.347	0.77%	6972.946op/s	1	200
credit_card/is_card_number/ 378282246310005	execution_time	71.399µs	71.736µs ± 0.444µs	71.539µs ± 0.073µs	71.795µs	72.536µs	73.970µs	74.218µs	3.74%	2.917	10.638	0.62%	0.031µs	1	200
credit_card/is_card_number/ 378282246310005	throughput	13473880.017op/s	13940618.709op/s ± 84778.917op/s	13978306.367op/s ± 14237.007op/s	13988130.372op/s	13995321.224op/s	13999715.597op/s	14005840.435op/s	0.20%	-2.842	10.061	0.61%	5994.775op/s	1	200
credit_card/is_card_number/37828224631	execution_time	3.893µs	3.915µs ± 0.003µs	3.914µs ± 0.002µs	3.916µs	3.921µs	3.924µs	3.925µs	0.29%	-0.357	8.254	0.09%	0.000µs	1	200
credit_card/is_card_number/37828224631	throughput	254762589.684op/s	255452512.983op/s ± 220356.999op/s	255490789.590op/s ± 102857.117op/s	255564069.917op/s	255703263.644op/s	255757790.046op/s	256859738.397op/s	0.54%	0.384	8.397	0.09%	15581.593op/s	1	200
credit_card/is_card_number/378282246310005	execution_time	68.235µs	68.623µs ± 0.283µs	68.588µs ± 0.232µs	68.818µs	69.134µs	69.354µs	69.633µs	1.52%	0.759	0.063	0.41%	0.020µs	1	200
credit_card/is_card_number/378282246310005	throughput	14361094.575op/s	14572685.223op/s ± 59813.113op/s	14579896.510op/s ± 49256.244op/s	14629526.407op/s	14647402.291op/s	14651237.434op/s	14655194.393op/s	0.52%	-0.741	0.016	0.41%	4229.426op/s	1	200
credit_card/is_card_number/37828224631000521389798	execution_time	45.416µs	45.708µs ± 0.100µs	45.708µs ± 0.073µs	45.782µs	45.854µs	45.907µs	45.918µs	0.46%	-0.223	-0.322	0.22%	0.007µs	1	200
credit_card/is_card_number/37828224631000521389798	throughput	21777913.020op/s	21877999.554op/s ± 47760.445op/s	21878128.437op/s ± 34670.229op/s	21908656.659op/s	21954732.052op/s	21994506.524op/s	22018477.021op/s	0.64%	0.234	-0.310	0.22%	3377.173op/s	1	200
credit_card/is_card_number/x371413321323331	execution_time	6.587µs	6.630µs ± 0.014µs	6.633µs ± 0.004µs	6.637µs	6.640µs	6.645µs	6.718µs	1.27%	0.722	10.226	0.20%	0.001µs	1	200
credit_card/is_card_number/x371413321323331	throughput	148854353.803op/s	150829512.986op/s ± 306691.965op/s	150750169.283op/s ± 99761.086op/s	150955583.386op/s	151465783.046op/s	151652371.470op/s	151821918.319op/s	0.71%	-0.652	9.842	0.20%	21686.397op/s	1	200
credit_card/is_card_number_no_luhn/	execution_time	3.896µs	3.915µs ± 0.003µs	3.915µs ± 0.002µs	3.917µs	3.919µs	3.922µs	3.924µs	0.22%	-1.463	12.421	0.07%	0.000µs	1	200
credit_card/is_card_number_no_luhn/	throughput	254839633.131op/s	255418833.278op/s ± 177571.982op/s	255406065.902op/s ± 107343.727op/s	255523206.912op/s	255652303.260op/s	255721674.340op/s	256696909.797op/s	0.51%	1.489	12.612	0.07%	12556.235op/s	1	200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	execution_time	65.602µs	65.729µs ± 0.053µs	65.736µs ± 0.035µs	65.765µs	65.817µs	65.831µs	65.837µs	0.15%	-0.275	-0.365	0.08%	0.004µs	1	200
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	throughput	15188986.734op/s	15214104.709op/s ± 12263.424op/s	15212440.995op/s ± 8064.095op/s	15222351.167op/s	15235358.509op/s	15241612.523op/s	15243537.935op/s	0.20%	0.279	-0.363	0.08%	867.155op/s	1	200
credit_card/is_card_number_no_luhn/ 378282246310005	execution_time	53.352µs	53.430µs ± 0.042µs	53.423µs ± 0.024µs	53.447µs	53.512µs	53.552µs	53.630µs	0.39%	1.258	2.586	0.08%	0.003µs	1	200
credit_card/is_card_number_no_luhn/ 378282246310005	throughput	18646416.922op/s	18716139.556op/s ± 14709.335op/s	18718453.060op/s ± 8316.906op/s	18726579.170op/s	18735713.085op/s	18739527.041op/s	18743428.584op/s	0.13%	-1.251	2.556	0.08%	1040.107op/s	1	200
credit_card/is_card_number_no_luhn/37828224631	execution_time	3.897µs	3.915µs ± 0.003µs	3.915µs ± 0.002µs	3.917µs	3.919µs	3.921µs	3.922µs	0.20%	-0.979	7.209	0.07%	0.000µs	1	200
credit_card/is_card_number_no_luhn/37828224631	throughput	254943498.172op/s	255441997.771op/s ± 183704.814op/s	255454654.523op/s ± 112308.829op/s	255560217.090op/s	255677769.660op/s	255768174.195op/s	256624483.724op/s	0.46%	0.996	7.331	0.07%	12989.892op/s	1	200
credit_card/is_card_number_no_luhn/378282246310005	execution_time	50.143µs	50.215µs ± 0.031µs	50.213µs ± 0.021µs	50.234µs	50.271µs	50.303µs	50.310µs	0.19%	0.421	-0.009	0.06%	0.002µs	1	200
credit_card/is_card_number_no_luhn/378282246310005	throughput	19876811.473op/s	19914335.240op/s ± 12470.792op/s	19915325.017op/s ± 8511.398op/s	19923612.869op/s	19931784.365op/s	19939407.077op/s	19942774.209op/s	0.14%	-0.417	-0.013	0.06%	881.818op/s	1	200
credit_card/is_card_number_no_luhn/37828224631000521389798	execution_time	45.427µs	45.708µs ± 0.094µs	45.722µs ± 0.060µs	45.773µs	45.857µs	45.896µs	45.920µs	0.43%	-0.329	-0.185	0.21%	0.007µs	1	200
credit_card/is_card_number_no_luhn/37828224631000521389798	throughput	21776999.153op/s	21878315.563op/s ± 45101.310op/s	21871462.119op/s ± 28667.778op/s	21913389.081op/s	21956730.816op/s	21984562.102op/s	22013335.659op/s	0.65%	0.340	-0.176	0.21%	3189.144op/s	1	200
credit_card/is_card_number_no_luhn/x371413321323331	execution_time	6.572µs	6.623µs ± 0.014µs	6.627µs ± 0.010µs	6.634µs	6.639µs	6.647µs	6.651µs	0.38%	-0.738	0.221	0.22%	0.001µs	1	200
credit_card/is_card_number_no_luhn/x371413321323331	throughput	150342304.852op/s	150992404.870op/s ± 330772.156op/s	150908060.062op/s ± 218064.934op/s	151203680.364op/s	151604918.012op/s	151861939.277op/s	152150768.422op/s	0.82%	0.749	0.246	0.22%	23389.123op/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	[3.915µs; 3.916µs] or [-0.011%; +0.011%]	None	None	None
credit_card/is_card_number/	throughput	[255374820.691op/s; 255430965.839op/s] or [-0.011%; +0.011%]	None	None	None
credit_card/is_card_number/ 3782-8224-6310-005	execution_time	[78.535µs; 78.706µs] or [-0.109%; +0.109%]	None	None	None
credit_card/is_card_number/ 3782-8224-6310-005	throughput	[12706445.144op/s; 12733778.589op/s] or [-0.107%; +0.107%]	None	None	None
credit_card/is_card_number/ 378282246310005	execution_time	[71.674µs; 71.797µs] or [-0.086%; +0.086%]	None	None	None
credit_card/is_card_number/ 378282246310005	throughput	[13928869.166op/s; 13952368.252op/s] or [-0.084%; +0.084%]	None	None	None
credit_card/is_card_number/37828224631	execution_time	[3.914µs; 3.915µs] or [-0.012%; +0.012%]	None	None	None
credit_card/is_card_number/37828224631	throughput	[255421973.622op/s; 255483052.343op/s] or [-0.012%; +0.012%]	None	None	None
credit_card/is_card_number/378282246310005	execution_time	[68.584µs; 68.662µs] or [-0.057%; +0.057%]	None	None	None
credit_card/is_card_number/378282246310005	throughput	[14564395.701op/s; 14580974.746op/s] or [-0.057%; +0.057%]	None	None	None
credit_card/is_card_number/37828224631000521389798	execution_time	[45.694µs; 45.722µs] or [-0.030%; +0.030%]	None	None	None
credit_card/is_card_number/37828224631000521389798	throughput	[21871380.416op/s; 21884618.693op/s] or [-0.030%; +0.030%]	None	None	None
credit_card/is_card_number/x371413321323331	execution_time	[6.628µs; 6.632µs] or [-0.028%; +0.028%]	None	None	None
credit_card/is_card_number/x371413321323331	throughput	[150787008.430op/s; 150872017.543op/s] or [-0.028%; +0.028%]	None	None	None
credit_card/is_card_number_no_luhn/	execution_time	[3.915µs; 3.916µs] or [-0.010%; +0.010%]	None	None	None
credit_card/is_card_number_no_luhn/	throughput	[255394223.509op/s; 255443443.047op/s] or [-0.010%; +0.010%]	None	None	None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	execution_time	[65.721µs; 65.736µs] or [-0.011%; +0.011%]	None	None	None
credit_card/is_card_number_no_luhn/ 3782-8224-6310-005	throughput	[15212405.117op/s; 15215804.302op/s] or [-0.011%; +0.011%]	None	None	None
credit_card/is_card_number_no_luhn/ 378282246310005	execution_time	[53.424µs; 53.436µs] or [-0.011%; +0.011%]	None	None	None
credit_card/is_card_number_no_luhn/ 378282246310005	throughput	[18714100.984op/s; 18718178.129op/s] or [-0.011%; +0.011%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631	execution_time	[3.914µs; 3.915µs] or [-0.010%; +0.010%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631	throughput	[255416538.051op/s; 255467457.492op/s] or [-0.010%; +0.010%]	None	None	None
credit_card/is_card_number_no_luhn/378282246310005	execution_time	[50.211µs; 50.219µs] or [-0.009%; +0.009%]	None	None	None
credit_card/is_card_number_no_luhn/378282246310005	throughput	[19912606.909op/s; 19916063.572op/s] or [-0.009%; +0.009%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631000521389798	execution_time	[45.695µs; 45.721µs] or [-0.029%; +0.029%]	None	None	None
credit_card/is_card_number_no_luhn/37828224631000521389798	throughput	[21872064.955op/s; 21884566.170op/s] or [-0.029%; +0.029%]	None	None	None
credit_card/is_card_number_no_luhn/x371413321323331	execution_time	[6.621µs; 6.625µs] or [-0.030%; +0.030%]	None	None	None
credit_card/is_card_number_no_luhn/x371413321323331	throughput	[150946563.031op/s; 151038246.710op/s] 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	2e9dcc8	1762183029	gyuheon0h/prof-12432-runtime-stacks

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	6.197ms	6.417ms ± 0.060ms	6.426ms ± 0.017ms	6.446ms	6.471ms	6.494ms	6.785ms	5.59%	-0.447	9.591	0.93%	0.004ms	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	[6.409ms; 6.426ms] or [-0.130%; +0.130%]	None	None	None

Group 12

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	2e9dcc8	1762183029	gyuheon0h/prof-12432-runtime-stacks

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	496.120µs	497.068µs ± 0.975µs	496.914µs ± 0.258µs	497.163µs	497.643µs	500.837µs	504.652µs	1.56%	5.202	33.309	0.20%	0.069µs	1	200
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000...	throughput	1981562.224op/s	2011804.888op/s ± 3905.546op/s	2012422.573op/s ± 1043.516op/s	2013478.843op/s	2014662.591op/s	2015553.358op/s	2015642.054op/s	0.16%	-5.154	32.778	0.19%	276.164op/s	1	200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	execution_time	370.095µs	370.772µs ± 0.275µs	370.740µs ± 0.161µs	370.922µs	371.275µs	371.416µs	371.907µs	0.31%	0.495	1.154	0.07%	0.019µs	1	200
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	throughput	2688847.712op/s	2697078.040op/s ± 2001.606op/s	2697310.933op/s ± 1171.793op/s	2698269.345op/s	2700075.412op/s	2701319.154op/s	2702007.674op/s	0.17%	-0.489	1.139	0.07%	141.535op/s	1	200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	execution_time	168.439µs	168.807µs ± 0.155µs	168.792µs ± 0.095µs	168.902µs	169.098µs	169.217µs	169.260µs	0.28%	0.495	0.105	0.09%	0.011µs	1	200
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	throughput	5908071.236op/s	5923921.199op/s ± 5432.496op/s	5924442.009op/s ± 3340.856op/s	5927531.720op/s	5932521.909op/s	5933464.159op/s	5936878.828op/s	0.21%	-0.490	0.099	0.09%	384.135op/s	1	200
normalization/normalize_service/normalize_service/[empty string]	execution_time	36.465µs	36.781µs ± 0.190µs	36.757µs ± 0.104µs	36.869µs	37.036µs	37.276µs	38.100µs	3.65%	3.019	17.402	0.52%	0.013µs	1	200
normalization/normalize_service/normalize_service/[empty string]	throughput	26246569.226op/s	27188387.320op/s ± 138361.653op/s	27205859.054op/s ± 76826.362op/s	27272323.116op/s	27356133.931op/s	27385256.915op/s	27423632.041op/s	0.80%	-2.864	16.094	0.51%	9783.646op/s	1	200
normalization/normalize_service/normalize_service/test_ASCII	execution_time	46.157µs	46.304µs ± 0.118µs	46.292µs ± 0.040µs	46.334µs	46.419µs	46.479µs	47.727µs	3.10%	8.818	103.383	0.25%	0.008µs	1	200
normalization/normalize_service/normalize_service/test_ASCII	throughput	20952715.309op/s	21596352.142op/s ± 53888.854op/s	21602105.774op/s ± 18595.576op/s	21619928.385op/s	21640797.838op/s	21649949.797op/s	21665321.812op/s	0.29%	-8.608	100.009	0.25%	3810.517op/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	[496.933µs; 497.203µs] or [-0.027%; +0.027%]	None	None	None
normalization/normalize_service/normalize_service/A0000000000000000000000000000000000000000000000000...	throughput	[2011263.617op/s; 2012346.159op/s] or [-0.027%; +0.027%]	None	None	None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	execution_time	[370.734µs; 370.810µs] or [-0.010%; +0.010%]	None	None	None
normalization/normalize_service/normalize_service/Data🐨dog🐶 繋がっ⛰てて	throughput	[2696800.637op/s; 2697355.443op/s] or [-0.010%; +0.010%]	None	None	None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	execution_time	[168.786µs; 168.829µs] or [-0.013%; +0.013%]	None	None	None
normalization/normalize_service/normalize_service/Test Conversion 0f Weird !@#$%^&**() Characters	throughput	[5923168.307op/s; 5924674.091op/s] or [-0.013%; +0.013%]	None	None	None
normalization/normalize_service/normalize_service/[empty string]	execution_time	[36.755µs; 36.808µs] or [-0.072%; +0.072%]	None	None	None
normalization/normalize_service/normalize_service/[empty string]	throughput	[27169211.725op/s; 27207562.914op/s] or [-0.071%; +0.071%]	None	None	None
normalization/normalize_service/normalize_service/test_ASCII	execution_time	[46.288µs; 46.321µs] or [-0.035%; +0.035%]	None	None	None
normalization/normalize_service/normalize_service/test_ASCII	throughput	[21588883.665op/s; 21603820.619op/s] or [-0.035%; +0.035%]	None	None	None

Group 13

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	2e9dcc8	1762183029	gyuheon0h/prof-12432-runtime-stacks

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	185.446µs	185.890µs ± 0.290µs	185.865µs ± 0.163µs	186.025µs	186.277µs	186.799µs	187.955µs	1.12%	2.658	14.794	0.16%	0.021µs	1	200
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo...	throughput	5320435.180op/s	5379535.511op/s ± 8356.762op/s	5380249.468op/s ± 4730.320op/s	5385289.167op/s	5389411.380op/s	5390635.104op/s	5392417.695op/s	0.23%	-2.613	14.408	0.15%	590.912op/s	1	200
normalization/normalize_name/normalize_name/bad-name	execution_time	17.779µs	17.865µs ± 0.113µs	17.859µs ± 0.033µs	17.889µs	17.935µs	17.958µs	19.342µs	8.30%	11.109	142.340	0.63%	0.008µs	1	200
normalization/normalize_name/normalize_name/bad-name	throughput	51701949.989op/s	55976362.926op/s ± 332230.466op/s	55995428.139op/s ± 102083.912op/s	56108037.682op/s	56223253.945op/s	56237224.236op/s	56246425.516op/s	0.45%	-10.708	135.448	0.59%	23492.242op/s	1	200
normalization/normalize_name/normalize_name/good	execution_time	10.525µs	10.573µs ± 0.023µs	10.567µs ± 0.012µs	10.586µs	10.616µs	10.642µs	10.650µs	0.79%	0.899	0.703	0.21%	0.002µs	1	200
normalization/normalize_name/normalize_name/good	throughput	93894425.395op/s	94576530.135op/s ± 203044.646op/s	94635264.162op/s ± 111840.627op/s	94721910.761op/s	94811797.141op/s	94950041.503op/s	95009464.683op/s	0.40%	-0.887	0.675	0.21%	14357.425op/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	[185.850µs; 185.930µs] or [-0.022%; +0.022%]	None	None	None
normalization/normalize_name/normalize_name/Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Long-.Too-Lo...	throughput	[5378377.344op/s; 5380693.678op/s] or [-0.022%; +0.022%]	None	None	None
normalization/normalize_name/normalize_name/bad-name	execution_time	[17.850µs; 17.881µs] or [-0.088%; +0.088%]	None	None	None
normalization/normalize_name/normalize_name/bad-name	throughput	[55930318.978op/s; 56022406.873op/s] or [-0.082%; +0.082%]	None	None	None
normalization/normalize_name/normalize_name/good	execution_time	[10.570µs; 10.577µs] or [-0.030%; +0.030%]	None	None	None
normalization/normalize_name/normalize_name/good	throughput	[94548390.100op/s; 94604670.171op/s] or [-0.030%; +0.030%]	None	None	None

Group 14

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	2e9dcc8	1762183029	gyuheon0h/prof-12432-runtime-stacks

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	17.839µs	25.430µs ± 9.481µs	18.029µs ± 0.137µs	33.432µs	42.419µs	43.339µs	69.443µs	285.18%	1.133	1.655	37.19%	0.670µs	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
two way interface	execution_time	[24.116µs; 26.744µs] or [-5.167%; +5.167%]	None	None	None

Group 15

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	2e9dcc8	1762183029	gyuheon0h/prof-12432-runtime-stacks

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	14.202ms	14.247ms ± 0.030ms	14.242ms ± 0.011ms	14.252ms	14.303ms	14.356ms	14.439ms	1.38%	2.841	11.597	0.21%	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	[14.243ms; 14.251ms] or [-0.029%; +0.029%]	None	None	None

Group 16

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	2e9dcc8	1762183029	gyuheon0h/prof-12432-runtime-stacks

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	171.682ns	175.570ns ± 3.132ns	174.851ns ± 2.014ns	177.068ns	181.286ns	185.414ns	190.427ns	8.91%	1.521	3.344	1.78%	0.221ns	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	[175.136ns; 176.004ns] or [-0.247%; +0.247%]	None	None	None

Group 17

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	2e9dcc8	1762183029	gyuheon0h/prof-12432-runtime-stacks

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	61.804ms	62.397ms ± 2.293ms	62.077ms ± 0.073ms	62.146ms	62.320ms	78.852ms	81.962ms	32.03%	7.674	58.467	3.67%	0.162ms	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	[62.079ms; 62.714ms] or [-0.509%; +0.509%]	None	None	None

Baseline

Omitted due to size.

[codecov-commenter]

Codecov Report

❌ Patch coverage is 58.28488% with 287 lines in your changes missing coverage. Please review.
✅ Project coverage is 71.70%. Comparing base (c55d7fd) to head (2e9dcc8).
⚠️ Report is 5 commits behind head on main.

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #1252      +/-   ##
==========================================
- Coverage   72.11%   71.70%   -0.42%     
==========================================
  Files         368      373       +5     
  Lines       58111    58987     +876     
==========================================
+ Hits        41907    42295     +388     
- Misses      16204    16692     +488     

Components	Coverage Δ
datadog-crashtracker	52.12% <63.93%> (+1.49%)	⬆️
datadog-crashtracker-ffi	11.15% <63.51%> (+5.28%)	⬆️
datadog-alloc	98.73% <ø> (ø)
data-pipeline	87.89% <ø> (-0.30%)	⬇️
data-pipeline-ffi	88.19% <ø> (ø)
ddcommon	81.11% <ø> (+0.15%)	⬆️
ddcommon-ffi	74.28% <ø> (+0.44%)	⬆️
ddtelemetry	60.02% <ø> (ø)
ddtelemetry-ffi	21.24% <ø> (ø)
dogstatsd-client	83.26% <ø> (ø)
datadog-ipc	82.39% <ø> (-0.11%)	⬇️
datadog-profiling	76.50% <ø> (-0.40%)	⬇️
datadog-profiling-ffi	62.11% <ø> (-0.01%)	⬇️
datadog-sidecar	36.32% <ø> (-1.31%)	⬇️
datdog-sidecar-ffi	9.53% <ø> (-6.36%)	⬇️
spawn-worker	55.18% <ø> (ø)
tinybytes	92.44% <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	90.19% <ø> (ø)
datadog-tracer-flare	61.03% <ø> (-3.95%)	⬇️
datadog-log	75.57% <ø> (ø)

🚀 New features to boost your workflow:

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

[dd-octo-sts]

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% (+16 B) 👌
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.a	71.36 MB	71.45 MB	+.12% (+93.57 KB) 🔍

aarch64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.a	83.71 MB	83.86 MB	+.18% (+156.60 KB) 🔍
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.so	9.20 MB	9.27 MB	+.73% (+68.82 KB) 🔍

libdatadog-x64-windows

Artifact	Baseline	Commit	Change
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.dll	18.61 MB	18.61 MB	--.04% (-8.00 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	131.06 MB	131.01 MB	--.03% (-48.00 KB) 💪
/libdatadog-x64-windows/debug/static/datadog_profiling_ffi.lib	692.07 MB	692.41 MB	+.04% (+352.02 KB) 🔍
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.dll	5.93 MB	5.93 MB	+0% (+512 B) 👌
/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	17.51 MB	17.51 MB	0% (0 B) 👌
/libdatadog-x64-windows/release/static/datadog_profiling_ffi.lib	32.46 MB	32.46 MB	+0% (+110 B) 👌

libdatadog-x86-windows

Artifact	Baseline	Commit	Change
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.dll	15.85 MB	15.84 MB	--.02% (-3.50 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	133.16 MB	133.13 MB	--.01% (-24.00 KB) 💪
/libdatadog-x86-windows/debug/static/datadog_profiling_ffi.lib	680.69 MB	681.05 MB	+.05% (+364.26 KB) 🔍
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.dll	4.54 MB	4.55 MB	+.04% (+2.00 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	18.66 MB	18.66 MB	+.04% (+8.00 KB) 🔍
/libdatadog-x86-windows/release/static/datadog_profiling_ffi.lib	30.52 MB	30.52 MB	+.02% (+8.29 KB) 🔍

x86_64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.a	63.98 MB	64.07 MB	+.13% (+85.44 KB) 🔍
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.so	8.56 MB	8.57 MB	+.13% (+12.01 KB) 🔍

x86_64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.a	78.42 MB	78.56 MB	+.17% (+137.60 KB) 🔍
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.so	9.91 MB	9.92 MB	+.11% (+11.32 KB) 🔍

[gyuheon0h]

• [crashtracking] Allow runtimes to register runtime stack collection callbacks #1252 👈 (View in Graphite)
• main

This stack of pull requests is managed by Graphite. Learn more about stacking.

[gyuheon0h]

TODO: Fix Frame emitting allocation issue

[gyuheon0h]

TODO: add a type_name field to RuntimeStackFrame

[bwoebi]

Non-ffi crates should not depend on ffi crates. Actually, I don't see that you're even using that dep in this crate? Leftover maybe?

[gyuheon0h]

Ah I am. I was defining the runtime stack frame struct in the non ffi crate and exporting it in the ffi crate. I should probably have an FFI specific version?

[bwoebi]

Yes.