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feat(data-pipeline): add runtime-independent agentless sending - #2389

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feat(data-pipeline): add runtime-independent agentless sending#2389
gh-worker-dd-mergequeue-cf854d[bot] merged 8 commits into
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rochdev/host-managed-data-pipeline

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@rochdev

@rochdev rochdev commented Aug 21, 2026

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What does this PR do?

Adds a runtime-independent agentless data-pipeline send path. Rust owns trace
preparation, JSON encoding, compression, retry policy, timeouts, backoff, and
response handling; the host provides only HTTP and sleep capabilities.

The existing libdd-data-pipeline exporter now uses the same high-level send
path, so native and WASM consumers share the behavior without requiring a
specific async runtime.

Motivation

Node.js needs equivalent native and WASM data-pipeline implementations without
embedding Tokio and Hyper in the native extension. Keeping the send lifecycle
in Rust preserves retry behavior and makes the capability boundary reusable by
future targets.

Additional Notes

  • Request bodies are compressed once before the retry loop.
  • Native HTTP/runtime dependencies remain optional.
  • Node-specific v0.4 trace decoding remains in libdatadog-nodejs.

This PR was generated by Codex.

How to test the change?

  • cargo test -p libdd-data-pipeline-core --features compression
  • cargo test -p libdd-trace-utils send_with_retry
  • cargo test -p libdd-data-pipeline agentless
  • cargo clippy -p libdd-data-pipeline-core --all-targets --features compression -- -D warnings
  • cargo clippy -p libdd-trace-utils --lib --tests -- -D warnings
  • cargo clippy -p libdd-data-pipeline --lib -- -D warnings

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Tests

All CI checks and tests passed.

🎉 All green!

🧪 All tests passed
❄️ No new flaky tests detected

🎯 Code Coverage (details)
Patch Coverage: 90.20%
Overall Coverage: 76.69% (+0.00%)

This comment will be updated automatically if new data arrives.
🔗 Commit SHA: 85cf00d | Docs | View more details | Give us feedback!

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dd-octo-sts Bot commented Aug 21, 2026

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Artifact Size Benchmark Report

aarch64-alpine-linux-musl
Artifact Baseline Commit Change
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.so 8.26 MB 8.26 MB -0% (-24 B) 👌
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.a 89.73 MB 89.73 MB -0% (-2.46 KB) 👌
aarch64-unknown-linux-gnu
Artifact Baseline Commit Change
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.a 100.95 MB 100.95 MB +0% (+2.96 KB) 👌
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.so 11.13 MB 11.07 MB --.55% (-63.32 KB) 💪
libdatadog-x64-windows
Artifact Baseline Commit Change
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.dll 26.67 MB 26.68 MB +.01% (+5.00 KB) 🔍
/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 181.05 MB 181.16 MB +.06% (+120.00 KB) 🔍
/libdatadog-x64-windows/debug/static/datadog_profiling_ffi.lib 768.50 MB 771.58 MB +.40% (+3.08 MB) 🔍
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.dll 8.75 MB 8.75 MB +.03% (+3.00 KB) 🔍
/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 25.69 MB 25.69 MB 0% (0 B) 👌
/libdatadog-x64-windows/release/static/datadog_profiling_ffi.lib 51.16 MB 51.16 MB +0% (+3.24 KB) 👌
libdatadog-x86-windows
Artifact Baseline Commit Change
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.dll 23.25 MB 23.25 MB --.01% (-4.50 KB) 💪
/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 186.01 MB 186.10 MB +.04% (+88.00 KB) 🔍
/libdatadog-x86-windows/debug/static/datadog_profiling_ffi.lib 755.69 MB 755.40 MB --.03% (-297.75 KB) 💪
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.dll 6.76 MB 6.76 MB +.02% (+1.50 KB) 🔍
/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 27.63 MB +.02% (+8.00 KB) 🔍
/libdatadog-x86-windows/release/static/datadog_profiling_ffi.lib 48.69 MB 48.70 MB +.02% (+13.40 KB) 🔍
x86_64-alpine-linux-musl
Artifact Baseline Commit Change
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.a 79.98 MB 80.01 MB +.02% (+23.05 KB) 🔍
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.so 9.17 MB 9.18 MB +.04% (+3.96 KB) 🔍
x86_64-unknown-linux-gnu
Artifact Baseline Commit Change
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.a 95.71 MB 95.73 MB +.02% (+23.29 KB) 🔍
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.so 11.19 MB 11.20 MB +.04% (+5.17 KB) 🔍

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Benchmarks

Comparison

Benchmark execution time: 2026-08-26 22:29:06

Comparing candidate commit 85cf00d in PR branch rochdev/host-managed-data-pipeline with baseline commit a0f2872 in branch main.

Found 5 performance improvements and 19 performance regressions! Performance is the same for 129 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:otlp/e2e_json/1x1000

  • 🟩 execution_time [-370.793µs; -368.571µs] or [-8.192%; -8.143%]

scenario:otlp/encode_json/1x1000

  • 🟩 execution_time [-369.676µs; -367.854µs] or [-16.831%; -16.748%]

scenario:otlp/encode_protobuf/1x1000

  • 🟥 execution_time [+46.267µs; +46.658µs] or [+4.351%; +4.388%]

scenario:vec_map/as_deduped_map/needs_dedup_1_in_10/8

  • 🟥 execution_time [+29.088ns; +29.339ns] or [+8.194%; +8.265%]

scenario:vec_map/as_deduped_map/needs_dedup_1_in_2/8

  • 🟥 execution_time [+28.261ns; +28.496ns] or [+6.069%; +6.120%]

scenario:vec_map/as_deduped_map/needs_dedup_1_in_4/16

  • 🟥 execution_time [+35.198ns; +35.609ns] or [+4.569%; +4.622%]

scenario:vec_map/as_deduped_map/needs_dedup_1_in_4/8

  • 🟥 execution_time [+30.153ns; +30.413ns] or [+7.651%; +7.717%]

scenario:vec_map/contains_key/128

  • 🟥 execution_time [+651.197ns; +660.175ns] or [+4.327%; +4.386%]
  • 🟥 throughput [-357504.542op/s; -352591.777op/s] or [-4.204%; -4.146%]

scenario:vec_map/contains_key/16

  • 🟥 execution_time [+22.215ns; +22.648ns] or [+9.567%; +9.753%]
  • 🟥 throughput [-6130088.876op/s; -6011070.928op/s] or [-8.896%; -8.724%]

scenario:vec_map/contains_key/64

  • 🟥 execution_time [+226.087ns; +229.843ns] or [+5.664%; +5.758%]
  • 🟥 throughput [-873338.377op/s; -859137.766op/s] or [-5.447%; -5.358%]

scenario:vec_map/contains_key/8

  • 🟥 execution_time [+4.469ns; +4.696ns] or [+6.385%; +6.710%]
  • 🟥 throughput [-7220828.459op/s; -6855731.967op/s] or [-6.316%; -5.997%]

scenario:vec_map/dedup/dup_1_in_10/8

  • 🟥 execution_time [+17.125ns; +23.955ns] or [+4.239%; +5.930%]

scenario:vec_map/get_hit/16

  • 🟥 execution_time [+34.780ns; +35.167ns] or [+17.318%; +17.510%]
  • 🟥 throughput [-11872391.282op/s; -11755868.462op/s] or [-14.902%; -14.756%]

scenario:vec_map/get_hit/8

  • 🟥 execution_time [+10.824ns; +10.877ns] or [+20.037%; +20.134%]
  • 🟥 throughput [-24834928.500op/s; -24705804.884op/s] or [-16.770%; -16.683%]

scenario:vec_map/get_miss/128

  • 🟥 execution_time [+3.978ns; +4.150ns] or [+5.187%; +5.410%]

scenario:vec_map/get_miss/16

  • 🟩 execution_time [-17.540ns; -17.252ns] or [-63.396%; -62.353%]

scenario:vec_map/get_miss/64

  • 🟩 execution_time [-21.167ns; -21.039ns] or [-41.646%; -41.395%]

scenario:vec_map/get_miss/8

  • 🟩 execution_time [-12.618ns; -12.424ns] or [-69.044%; -67.981%]

Benchmark execution time: 2026-08-26 22:35:03

Comparing candidate commit 85cf00d in PR branch rochdev/host-managed-data-pipeline with baseline commit a0f2872 in branch main.

Found 9 performance improvements and 16 performance regressions! Performance is the same for 143 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:credit_card/is_card_number/ 378282246310005

  • 🟥 execution_time [+4.678µs; +4.777µs] or [+6.845%; +6.989%]
  • 🟥 throughput [-955532.678op/s; -936972.959op/s] or [-6.531%; -6.404%]

scenario:credit_card/is_card_number/378282246310005

  • 🟥 execution_time [+4.677µs; +4.765µs] or [+7.179%; +7.314%]
  • 🟥 throughput [-1045823.828op/s; -1027762.135op/s] or [-6.814%; -6.696%]

scenario:credit_card/is_card_number/37828224631000521389798

  • 🟥 execution_time [+6.446µs; +6.471µs] or [+14.067%; +14.121%]
  • 🟥 throughput [-2701206.327op/s; -2690123.966op/s] or [-12.378%; -12.328%]

scenario:credit_card/is_card_number/x371413321323331

  • 🟩 execution_time [-591.476ns; -586.734ns] or [-8.918%; -8.847%]
  • 🟩 throughput [+14643251.242op/s; +14754277.604op/s] or [+9.711%; +9.785%]

scenario:credit_card/is_card_number_no_luhn/ 378282246310005

  • 🟥 execution_time [+5.224µs; +5.288µs] or [+9.766%; +9.885%]
  • 🟥 throughput [-1681477.200op/s; -1662847.944op/s] or [-8.995%; -8.895%]

scenario:credit_card/is_card_number_no_luhn/378282246310005

  • 🟥 execution_time [+5.204µs; +5.252µs] or [+10.351%; +10.446%]
  • 🟥 throughput [-1881238.997op/s; -1865580.833op/s] or [-9.458%; -9.379%]

scenario:credit_card/is_card_number_no_luhn/37828224631000521389798

  • 🟥 execution_time [+6.462µs; +6.491µs] or [+14.109%; +14.172%]
  • 🟥 throughput [-2711448.173op/s; -2698259.669op/s] or [-12.419%; -12.359%]

scenario:credit_card/is_card_number_no_luhn/x371413321323331

  • 🟩 execution_time [-585.029ns; -579.497ns] or [-8.830%; -8.747%]
  • 🟩 throughput [+14478191.437op/s; +14606848.312op/s] or [+9.592%; +9.677%]

scenario:glob_matcher/ascii_case_insensitive_match/wall_time

  • 🟩 execution_time [-2.961ns; -2.949ns] or [-10.006%; -9.966%]

scenario:glob_matcher/ascii_exact_match/wall_time

  • 🟩 execution_time [-2.945ns; -2.931ns] or [-9.953%; -9.904%]

scenario:glob_matcher/ascii_exact_miss/wall_time

  • 🟩 execution_time [-3.095ns; -3.046ns] or [-21.202%; -20.860%]

scenario:no_profiler/short_circuit/4096

  • 🟥 execution_time [+6.641ns; +6.763ns] or [+7.390%; +7.525%]

scenario:profiler_attached/fast_path_system/4096

  • 🟩 execution_time [-15.815ns; -15.684ns] or [-15.269%; -15.142%]

scenario:profiler_attached/slow_path_system/4096

  • 🟩 execution_time [-6.978ns; -6.854ns] or [-4.512%; -4.432%]

scenario:tags/replace_trace_tags

  • 🟥 execution_time [+157.810ns; +166.628ns] or [+6.699%; +7.074%]

scenario:trace_buffer/2_senders/no_delay

  • 🟥 execution_time [+36.724µs; +44.554µs] or [+4.214%; +5.112%]
  • 🟥 throughput [-101115.972op/s; -83355.462op/s] or [-4.893%; -4.034%]

Candidate

Omitted due to size.

Baseline

Omitted due to size.

@rochdev
rochdev marked this pull request as ready for review August 21, 2026 14:01
@rochdev
rochdev requested review from a team as code owners August 21, 2026 14:01

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💡 Codex Review

Here are some automated review suggestions for this pull request.

Reviewed commit: fc9ff139a3

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Comment thread libdd-data-pipeline-core/src/agentless.rs Outdated
Comment thread libdd-data-pipeline-core/src/agentless.rs Outdated
Comment thread libdd-data-pipeline-core/src/agentless.rs Outdated
Comment thread libdd-common/src/lib.rs
@rochdev
rochdev force-pushed the rochdev/host-managed-data-pipeline branch 2 times, most recently from 1c04286 to 52dfcbb Compare August 21, 2026 17:26
bengl
bengl previously approved these changes Aug 21, 2026

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Seems fine to me, but @DataDog/apm-common-components-core should probably review.

@rochdev
rochdev dismissed bengl’s stale review August 23, 2026 03:03

Implementation changed significantly to keep retries on the Rust side.

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@codex review

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💡 Codex Review

Here are some automated review suggestions for this pull request.

Reviewed commit: 322d9336fe

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Comment thread libdd-common/src/lib.rs

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Overall, I'd like to push back against this pull request.
First without the matching libdatadog-nodejs PR it is very hard to reason about which APIs are necessary and which are not.

But more than this, I don't understand why we need the PreparedRequest level of abstraction, and this is not really motivated in the PR description.

What is the goal here

  1. Is it getting just a bag of data with the request and then doing the http request fully in NodeJS?
  2. Or is it to have a send_agentless function that takes messagepack &[u8] serialized trace chunk and uses the existing capabilities implementation to drive calling to the node http stack from rust?

While I am not completely against 1), I would much prefer option 2) as it doesn't expose as much details of libdatadog to nodeJS and you should just be able to hook the exisitng WASM capabilities implementation.

We should just do something like

NodeJS                      |   Rust                                               | NodeJS
send(chunk) -> encode msp   -> send(traces: &[u8]) -> encode() -> send_with_retry ->  http capability impl

and not

NodeJS                        |   Rust                                              | NodeJS                         | Rust             | NodeJS           
prepare(chunk) -> encode msp  -> prepare(traces: &[u8]) -> returns prepared request -> send_rust(prepared_request)   -> send_with_retry ->  http capability 

Comment thread libdd-trace-utils/src/send_with_retry/mod.rs Outdated
Comment thread libdd-common/Cargo.toml
Comment thread libdd-trace-utils/src/send_with_retry/retry_strategy.rs Outdated
Comment thread libdd-data-pipeline-core/src/agentless.rs Outdated
Comment thread libdd-trace-utils/src/send_with_retry/mod.rs Outdated
@rochdev rochdev changed the title feat(data-pipeline): add runtime-independent request preparation feat(data-pipeline): add runtime-independent agentless sending Aug 26, 2026

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LGTM!

@rochdev
rochdev force-pushed the rochdev/host-managed-data-pipeline branch from b442108 to 85cf00d Compare August 26, 2026 21:51
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/merge

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2026-08-26 22:52:01 UTC ℹ️ Start processing command /merge


2026-08-26 22:52:08 UTC ℹ️ MergeQueue: Pull request is not mergeable yet

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2026-08-26 23:33:42 UTC ⚠️ MergeQueue: This merge request was unqueued

roch.devost@datadoghq.com unqueued this merge request

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/code blockers

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2026-08-26 23:13:42 UTC ℹ️ Devflow:

Checking merge blockers for #2389...


2026-08-26 23:13:46 UTC ℹ️ Devflow: /code blockers

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/merge

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/merge -c

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/merge

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2026-08-26 23:34:29 UTC ℹ️ MergeQueue: pull request added to the queue

The expected merge time in main is approximately 53m (p90).


2026-08-27 00:06:20 UTC ℹ️ MergeQueue: This merge request was merged

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