feat(trace-utils)!: add v1 decoder

[anais-raison]

What does this PR do?

Adds a V1 msgpack decoder in libdd-trace-utils and wires the V1 variant through the trace pipeline so any V1 payload can be decoded, inspected, and re-encoded.

Motivation

APMSP-2813 : Prerequisite for the sidecar V1-native path. Splitting out the libdd-trace-utils / libdd-data-pipeline plumbing so it can land before the sidecar wiring.

Additional Notes

• Mirrors the existing v04 decoder structure.
• trace_serializer.rs now dispatches on (TraceChunks, OutputFormat); the existing v0.4 → V1 cross-encode path is preserved.
• trace_utils::collect_trace_chunks renamed to convert_trace_chunks_v04_to_v05.

⚠️ You can focus on those folders/files only as I merged the others from the PR #2145 to get all the refactors:

• libdd-data-pipeline/src/trace_exporter/trace_serializer.rs
• libdd-trace-utils/src/msgpack_decoder/
• libdd-trace-utils/src/span/mod.rs
• libdd-trace-utils/src/span/vec_map.rs
• libdd-trace-utils/src/trace_utils.rs
• libdd-trace-utils/src/tracer_payload.rs
• libdd-trace-utils/tests/snapshots/compare_v1_full_payload_snapshot_test.json
• libdd-trace-utils/tests/test_send_data.rs

[github-actions]

Clippy Allow Annotation Report

Tracked Clippy allow annotations changed vs main: ⚠️ +1 (8 → 9)

Rule	Base	PR	Δ
unwrap_used	5	6	⚠️ +1

By file and crate

By file

File	Base	PR	Δ
libdd-trace-utils/src/send_data/mod.rs	5	6	⚠️ +1

By crate

Crate	Base	PR	Δ
libdd-trace-utils	11	12	⚠️ +1

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. Panic-inducing macros in particular should be avoided. In the future, this report may become a PR-blocking quality gate.

[datadog-datadog-prod-us1-2]

🎉 All green!

🧪 All tests passed
❄️ No new flaky tests detected

🎯 Code Coverage (details)
• Patch Coverage: 62.75%
• Overall Coverage: 74.60% (-0.12%)

_{This comment will be updated automatically if new data arrives.
🔗 Commit SHA: 8245c33 | Docs | Datadog PR Page | Give us feedback!}

[dd-octo-sts]

Artifact Size Benchmark Report

aarch64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.a	86.33 MB	86.47 MB	+.16% (+142.10 KB) 🔍
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.so	7.88 MB	7.95 MB	+.79% (+64.00 KB) 🔍

aarch64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.so	10.62 MB	10.69 MB	+.62% (+68.00 KB) 🔍
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.a	97.54 MB	97.68 MB	+.13% (+139.10 KB) 🔍

libdatadog-x64-windows

Artifact	Baseline	Commit	Change
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.dll	25.58 MB	25.62 MB	+.15% (+41.50 KB) 🔍
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.lib	89.18 KB	89.18 KB	0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.pdb	185.54 MB	186.35 MB	+.43% (+832.00 KB) 🔍
/libdatadog-x64-windows/debug/static/datadog_profiling_ffi.lib	958.60 MB	962.77 MB	+.43% (+4.16 MB) 🔍
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.dll	8.37 MB	8.38 MB	+.12% (+10.50 KB) 🔍
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.lib	89.18 KB	89.18 KB	0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.pdb	24.76 MB	24.80 MB	+.15% (+40.00 KB) 🔍
/libdatadog-x64-windows/release/static/datadog_profiling_ffi.lib	49.28 MB	49.36 MB	+.15% (+76.58 KB) 🔍

libdatadog-x86-windows

Artifact	Baseline	Commit	Change
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.dll	22.23 MB	22.27 MB	+.16% (+38.50 KB) 🔍
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.lib	90.58 KB	90.58 KB	0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.pdb	190.01 MB	190.80 MB	+.41% (+808.00 KB) 🔍
/libdatadog-x86-windows/debug/static/datadog_profiling_ffi.lib	946.54 MB	950.99 MB	+.47% (+4.45 MB) 🔍
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.dll	6.47 MB	6.48 MB	+.12% (+8.50 KB) 🔍
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.lib	90.58 KB	90.58 KB	0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.pdb	26.58 MB	26.62 MB	+.14% (+40.00 KB) 🔍
/libdatadog-x86-windows/release/static/datadog_profiling_ffi.lib	46.89 MB	46.97 MB	+.15% (+74.75 KB) 🔍

x86_64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.a	77.08 MB	77.21 MB	+.16% (+131.85 KB) 🔍
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.so	8.83 MB	8.84 MB	+.13% (+12.00 KB) 🔍

x86_64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.a	92.50 MB	92.63 MB	+.14% (+137.35 KB) 🔍
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.so	10.74 MB	10.75 MB	+.10% (+11.68 KB) 🔍

[chatgpt-codex-connector]

💡 Codex Review

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Reviewed commit: 5434161c71

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[ajgajg1134]

Another thing we can do here to build confidence in the decoder is take the working dd-trace-go implementation and generate a bunch of various traces and put them just in to flat files, then decode them with this implementation and the trace-agent implementation to make sure they align? (Maybe there's an easier way to check this though)

[ekump]

Approving as none of my suggestions are blocking. But, I think mine, @Aaalibaba42 and @yannham's suggestions are simple enough that they can be addressed before merging and will improve the decoder.

[pr-commenter]

Benchmarks

Comparison

Benchmark execution time: 2026-07-20 09:49:24

Comparing candidate commit a2fbd74 in PR branch anais/add-v1-decoder with baseline commit d7980db in branch main.

Found 1 performance improvements and 2 performance regressions! Performance is the same for 136 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 ----------------------------------'

scenario:msgpack_decoder::v05/high_sharing/2000

• 🟥 execution_time [+76.140µs; +76.644µs] or [+4.895%; +4.928%]
• 🟥 throughput [-60392.305op/s; -60000.522op/s] or [-4.697%; -4.666%]

scenario:vec_map/as_deduped_map/needs_dedup_1_in_10/8

• 🟩 execution_time [-18.720ns; -18.572ns] or [-5.039%; -4.999%]

Benchmark execution time: 2026-07-20 09:48:12

Comparing candidate commit a2fbd74 in PR branch anais/add-v1-decoder with baseline commit d7980db in branch main.

Found 3 performance improvements and 0 performance regressions! Performance is the same for 72 metrics, 10 unstable metrics.

Explanation

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

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

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

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

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

More details about the CI and significant changes

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

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

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

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

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

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

scenario:datadog_sample_span/service_rule_not_matching/wall_time

• 🟩 execution_time [-10.624ns; -10.364ns] or [-7.540%; -7.355%]

scenario:trace_buffer/2_senders/no_delay

• 🟩 execution_time [-68.468µs; -61.421µs] or [-7.270%; -6.522%]
• 🟩 throughput [+134137.588op/s; +149673.874op/s] or [+7.016%; +7.828%]

Candidate

Omitted due to size.

Baseline

Omitted due to size.

[ajgajg1134]

From a V1 perspective this looks good! (And I saw some new rust things I don't see often so that was cool 😎 )