chore(crashtracking): use RAII remote ptrace API

[gyuheon0h]

PROF-15821

What does this PR do?

Uses RAII wrapper

• UnwAddrSpace::new() to create address space with the ptrace accessors, and
• UptInfo::new(tid) to create the per thread trace unwinding state

There is no need to manually manage the memory with this.

I did not use RemoteUnwindResources. It pairs one address space with one _UPT_create, so using it per thread would build a fresh address space for each thread and throw away libunwind's cached DWARF info between threads.

This will be worked on in a follow up.

Motivation

We have an RAII api. We should use it.

Additional Notes

Anything else we should know when reviewing?

How to test the change?

Describe here in detail how the change can be validated.

[gyuheon0h]

• chore(crashtracking): use RAII remote ptrace API #2416 👈 (View in Graphite)
• main

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[datadog-prod-us1-6]

✅ All CI checks and tests passed.

🎉 All green!

🧪 All tests passed
❄️ No new flaky tests detected

🎯 Code Coverage (details)
• Patch Coverage: 63.64%
• Overall Coverage: 76.70% (-0.00%)

_{This comment will be updated automatically if new data arrives.
🔗 Commit SHA: 609d070 | Docs | View more details | Give us feedback!}

[pr-commenter]

Benchmarks

Comparison

Benchmark execution time: 2026-08-25 18:00:36

Comparing candidate commit 609d070 in PR branch gyuheon0h/remote-ptrace-raii with baseline commit 1766e7e in branch main.

Found 0 performance improvements and 0 performance regressions! Performance is the same for 1 metrics, 0 unstable metrics.

Explanation

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

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

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

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

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

More details about the CI and significant changes

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

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

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

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

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

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

Candidate

Candidate benchmark details

Group 1

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	609d070	1787680214	gyuheon0h/remote-ptrace-raii

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/2644	execution_time	3.542ms	3.581ms ± 0.030ms	3.572ms ± 0.011ms	3.587ms	3.655ms	3.682ms	3.710ms	3.88%	1.930	3.632	0.84%	0.002ms	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
receiver_entry_point/report/2644	execution_time	[3.577ms; 3.585ms] or [-0.117%; +0.117%]	None	None	None

Baseline

Baseline benchmark details

Group 1

cpu_model	git_commit_sha	git_commit_date	git_branch
Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	1766e7e	1787678449	main

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/2644	execution_time	3.527ms	3.575ms ± 0.030ms	3.565ms ± 0.013ms	3.584ms	3.649ms	3.659ms	3.664ms	2.79%	1.296	1.051	0.85%	0.002ms	1	200

scenario	metric	95% CI mean	Shapiro-Wilk pvalue	Ljung-Box pvalue (lag=1)	Dip test pvalue
receiver_entry_point/report/2644	execution_time	[3.571ms; 3.579ms] or [-0.118%; +0.118%]	None	None	None

[dd-octo-sts]

Artifact Size Benchmark Report

aarch64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.a	89.69 MB	89.69 MB	+0% (+2.77 KB) 👌
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.so	8.26 MB	8.26 MB	0% (0 B) 👌

aarch64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.so	11.07 MB	11.07 MB	0% (0 B) 👌
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.a	100.91 MB	100.92 MB	+0% (+2.65 KB) 👌

libdatadog-x64-windows

Artifact	Baseline	Commit	Change
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.dll	26.65 MB	26.65 MB	0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.lib	94.96 KB	94.96 KB	0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.pdb	180.95 MB	180.94 MB	-0% (-16.00 KB) 👌
/libdatadog-x64-windows/debug/static/datadog_profiling_ffi.lib	773.55 MB	773.55 MB	0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.dll	8.74 MB	8.74 MB	0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.lib	94.96 KB	94.96 KB	0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.pdb	25.68 MB	25.68 MB	0% (0 B) 👌
/libdatadog-x64-windows/release/static/datadog_profiling_ffi.lib	51.15 MB	51.15 MB	0% (0 B) 👌

libdatadog-x86-windows

Artifact	Baseline	Commit	Change
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.dll	23.23 MB	23.23 MB	0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.lib	96.45 KB	96.45 KB	0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.pdb	185.86 MB	185.84 MB	-0% (-16.00 KB) 👌
/libdatadog-x86-windows/debug/static/datadog_profiling_ffi.lib	760.32 MB	760.32 MB	0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.dll	6.75 MB	6.75 MB	0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.lib	96.45 KB	96.45 KB	0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.pdb	27.62 MB	27.62 MB	0% (0 B) 👌
/libdatadog-x86-windows/release/static/datadog_profiling_ffi.lib	48.67 MB	48.67 MB	0% (0 B) 👌

x86_64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.a	79.96 MB	79.96 MB	+0% (+2.75 KB) 👌
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.so	9.17 MB	9.17 MB	0% (0 B) 👌

x86_64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.a	95.67 MB	95.67 MB	+0% (+2.56 KB) 👌
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.so	11.19 MB	11.19 MB	0% (0 B) 👌