feat(metrics-v3): add Datadog V3 payload encoder by atanzu · Pull Request #2223 · DataDog/libdatadog

atanzu · 2026-07-10T12:17:14Z

What does this PR do?

Add a new library which allows to encode metric payloads using V3 columnar format.

Motivation

This library enables users to encode their metric payloads using an efficient column-based protocol. For performance and compatibility reasons (we also want to keep this crate no_std so we could use it in very resource-constrained environments) this crate does manual protobuf serialization.

Additional Notes

How to test the change?

We do correctness test by comparing the resulting encoded payload with the one produced from protobuf-generated code.

github-actions · 2026-07-10T12:18:48Z

📚 Documentation Check Results

⚠️ 1 documentation warning(s) found

📦 `libdd-metrics-v3` - 1 warning(s)

Updated: 2026-07-16 08:00:35 UTC | Commit: 57db033 | missing-docs job results

datadog-datadog-prod-us1-2 · 2026-07-10T12:20:40Z

Tests

🎉 All green!

🧪 All tests passed
❄️ No new flaky tests detected

🎯 Code Coverage (details)
• Patch Coverage: 97.59%
• Overall Coverage: 75.01% (+0.26%)

_{This comment will be updated automatically if new data arrives.

🔗 Commit SHA: 8f065a5 | Docs | Datadog PR Page | Give us feedback!}

github-actions · 2026-07-10T12:20:58Z

🔒 Cargo Deny Results

✅ No issues found!

📦 `libdd-metrics-v3` - ✅ No issues

Updated: 2026-07-16 08:02:52 UTC | Commit: 57db033 | dependency-check job results

pr-commenter · 2026-07-10T13:04:30Z

Benchmarks

Comparison

Benchmark execution time: 2026-07-16 08:38:39

Comparing candidate commit 8f065a5 in PR branch mark.kirichenko/AGTMETRICS-536/add-metrics-v3-encoder with baseline commit 407f8f2 in branch main.

Found 20 performance improvements and 17 performance regressions! Performance is the same for 105 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

🟩 throughput [+49903.185op/s; +50269.617op/s] or [+4.039%; +4.069%]

scenario:msgpack_decoder::v05/low_sharing/10000

🟩 execution_time [-913.123µs; -850.491µs] or [-5.034%; -4.688%]
🟩 throughput [+27281.242op/s; +28907.160op/s] or [+4.948%; +5.243%]

scenario:msgpack_decoder::v05/low_sharing/200

🟩 execution_time [-15.935µs; -15.657µs] or [-4.423%; -4.346%]
🟩 throughput [+25236.850op/s; +25659.585op/s] or [+4.546%; +4.623%]

scenario:msgpack_decoder::v05/low_sharing/2000

🟩 execution_time [-172.468µs; -170.622µs] or [-4.763%; -4.712%]
🟩 throughput [+27325.899op/s; +27618.647op/s] or [+4.947%; +5.000%]

scenario:otlp/e2e_json/1x1000

🟥 execution_time [+432.438µs; +444.323µs] or [+10.606%; +10.898%]

scenario:otlp/encode_json/1x1000

🟥 execution_time [+423.943µs; +424.444µs] or [+24.003%; +24.031%]

scenario:vec_map/as_deduped_map/already_deduped/16

🟥 execution_time [+1.190ns; +1.274ns] or [+4.934%; +5.281%]

scenario:vec_map/as_deduped_map/already_deduped/8

🟥 execution_time [+1.211ns; +1.227ns] or [+8.365%; +8.481%]

scenario:vec_map/contains_key/128

🟩 execution_time [-1.371µs; -1.359µs] or [-8.405%; -8.332%]
🟩 throughput [+713857.979op/s; +719743.211op/s] or [+9.095%; +9.170%]

scenario:vec_map/contains_key/16

🟩 execution_time [-266.785ns; -266.339ns] or [-53.630%; -53.540%]
🟩 throughput [+37090887.579op/s; +37174492.727op/s] or [+115.319%; +115.579%]

scenario:vec_map/contains_key/64

🟩 execution_time [-702.742ns; -695.791ns] or [-15.077%; -14.928%]
🟩 throughput [+2412596.442op/s; +2433743.525op/s] or [+17.570%; +17.724%]

scenario:vec_map/contains_key/8

🟩 execution_time [-140.953ns; -140.876ns] or [-66.877%; -66.840%]
🟩 throughput [+76518615.408op/s; +76631546.544op/s] or [+201.593%; +201.890%]

scenario:vec_map/get_hit/128

🟥 execution_time [+1.148µs; +1.167µs] or [+9.245%; +9.400%]
🟥 throughput [-887155.909op/s; -871568.728op/s] or [-8.605%; -8.454%]

scenario:vec_map/get_hit/16

🟩 execution_time [-13.352ns; -13.164ns] or [-6.263%; -6.175%]
🟩 throughput [+4941830.049op/s; +5010214.279op/s] or [+6.585%; +6.676%]

scenario:vec_map/get_hit/64

🟥 execution_time [+292.248ns; +295.421ns] or [+8.591%; +8.684%]
🟥 throughput [-1504097.842op/s; -1487776.548op/s] or [-7.995%; -7.908%]

scenario:vec_map/get_hit/8

🟩 execution_time [-7.901ns; -7.748ns] or [-12.792%; -12.544%]
🟩 throughput [+18615871.699op/s; +18939340.435op/s] or [+14.372%; +14.622%]

scenario:vec_map/get_miss/128

🟩 execution_time [-3.735ns; -3.582ns] or [-4.645%; -4.454%]

scenario:vec_map/get_miss/16

🟥 execution_time [+16.970ns; +17.176ns] or [+163.349%; +165.331%]

scenario:vec_map/get_miss/64

🟥 execution_time [+21.172ns; +21.240ns] or [+70.993%; +71.219%]

scenario:vec_map/get_miss/8

🟥 execution_time [+12.113ns; +12.286ns] or [+203.840%; +206.743%]

scenario:vec_map/get_mut/128

🟥 execution_time [+2.229µs; +2.318µs] or [+16.281%; +16.934%]
🟥 throughput [-1359459.530op/s; -1305323.027op/s] or [-14.535%; -13.956%]

scenario:vec_map/get_mut/16

🟥 execution_time [+20.306ns; +30.351ns] or [+7.305%; +10.918%]
🟥 throughput [-6042599.796op/s; -3971377.412op/s] or [-10.398%; -6.834%]

scenario:vec_map/get_mut/64

🟥 execution_time [+469.117ns; +506.440ns] or [+12.127%; +13.091%]
🟥 throughput [-1933357.581op/s; -1784547.167op/s] or [-11.678%; -10.779%]

Benchmark execution time: 2026-07-16 08:52:06

Comparing candidate commit 8f065a5 in PR branch mark.kirichenko/AGTMETRICS-536/add-metrics-v3-encoder with baseline commit 407f8f2 in branch main.

Found 3 performance improvements and 25 performance regressions! Performance is the same for 149 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:alloc_free/sampled_system_fast_path/4096

🟥 execution_time [+4.879ns; +5.073ns] or [+4.963%; +5.159%]

scenario:alloc_free/sampled_system_slow_path/16

🟥 execution_time [+12.930ns; +13.046ns] or [+14.951%; +15.086%]

scenario:alloc_free/sampled_system_slow_path/256

🟥 execution_time [+12.862ns; +12.959ns] or [+14.853%; +14.965%]

scenario:alloc_free/sampled_system_slow_path/4096

🟥 execution_time [+12.717ns; +12.830ns] or [+8.064%; +8.136%]

scenario:alloc_free/sampled_system_slow_path/64

🟥 execution_time [+12.767ns; +12.870ns] or [+14.746%; +14.866%]

scenario:alloc_free/sampled_system_slow_path/65536

🟥 execution_time [+22.158ns; +22.298ns] or [+13.996%; +14.084%]

scenario:credit_card/is_card_number/ 3782-8224-6310-005

🟥 execution_time [+4.767µs; +4.947µs] or [+6.343%; +6.583%]
🟥 throughput [-823948.655op/s; -792955.875op/s] or [-6.191%; -5.958%]

scenario:credit_card/is_card_number/ 378282246310005

🟥 execution_time [+5.603µs; +5.666µs] or [+8.265%; +8.359%]
🟥 throughput [-1137977.035op/s; -1125989.306op/s] or [-7.714%; -7.633%]

scenario:credit_card/is_card_number/378282246310005

🟥 execution_time [+5.595µs; +5.675µs] or [+8.665%; +8.789%]
🟥 throughput [-1251139.552op/s; -1234784.037op/s] or [-8.078%; -7.973%]

scenario:credit_card/is_card_number/37828224631000521389798

🟥 execution_time [+6.969µs; +7.012µs] or [+15.391%; +15.486%]
🟥 throughput [-2963979.892op/s; -2943350.309op/s] or [-13.421%; -13.328%]

scenario:credit_card/is_card_number_no_luhn/ 378282246310005

🟥 execution_time [+5.148µs; +5.200µs] or [+9.696%; +9.795%]
🟥 throughput [-1680439.680op/s; -1664769.842op/s] or [-8.921%; -8.838%]

scenario:credit_card/is_card_number_no_luhn/378282246310005

🟥 execution_time [+5.418µs; +5.492µs] or [+10.854%; +11.003%]
🟥 throughput [-1985481.027op/s; -1961023.224op/s] or [-9.911%; -9.789%]

scenario:credit_card/is_card_number_no_luhn/37828224631000521389798

🟥 execution_time [+6.886µs; +6.927µs] or [+15.177%; +15.265%]
🟥 throughput [-2921048.951op/s; -2902041.504op/s] or [-13.254%; -13.168%]

scenario:glob_matcher/ascii_case_insensitive_match/wall_time

🟥 execution_time [+1.978ns; +2.004ns] or [+7.241%; +7.338%]

scenario:glob_matcher/ascii_exact_match/wall_time

🟥 execution_time [+1.990ns; +2.035ns] or [+7.281%; +7.447%]

scenario:glob_matcher/ascii_exact_miss/wall_time

🟥 execution_time [+2.205ns; +2.258ns] or [+17.722%; +18.154%]

scenario:glob_matcher/unicode_pattern_ascii_subject/wall_time

🟥 execution_time [+4.679ns; +4.814ns] or [+5.174%; +5.324%]

scenario:receiver_entry_point/report/2644

🟥 execution_time [+145.328µs; +149.770µs] or [+4.000%; +4.122%]

scenario:sql/obfuscate_sql_string

🟩 execution_time [-20.384µs; -20.105µs] or [-6.635%; -6.544%]

scenario:trace_buffer/4_senders/no_delay

🟩 execution_time [-127.642µs; -98.622µs] or [-5.232%; -4.042%]
🟩 throughput [+63202.980op/s; +82147.582op/s] or [+4.280%; +5.563%]

Candidate

Omitted due to size.

Baseline

Omitted due to size.

dd-octo-sts · 2026-07-10T13:20:17Z

Artifact Size Benchmark Report

aarch64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.a	85.88 MB	85.88 MB	0% (0 B) 👌
/aarch64-alpine-linux-musl/lib/libdatadog_profiling.so	7.88 MB	7.88 MB	0% (0 B) 👌

aarch64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.a	97.10 MB	97.10 MB	0% (0 B) 👌
/aarch64-unknown-linux-gnu/lib/libdatadog_profiling.so	10.61 MB	10.61 MB	0% (0 B) 👌

libdatadog-x64-windows

Artifact	Baseline	Commit	Change
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.dll	25.45 MB	25.45 MB	0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.lib	88.44 KB	88.44 KB	0% (0 B) 👌
/libdatadog-x64-windows/debug/dynamic/datadog_profiling_ffi.pdb	184.54 MB	184.55 MB	+0% (+8.00 KB) 👌
/libdatadog-x64-windows/debug/static/datadog_profiling_ffi.lib	946.77 MB	946.77 MB	0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.dll	8.32 MB	8.32 MB	0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.lib	88.44 KB	88.44 KB	0% (0 B) 👌
/libdatadog-x64-windows/release/dynamic/datadog_profiling_ffi.pdb	24.62 MB	24.62 MB	0% (0 B) 👌
/libdatadog-x64-windows/release/static/datadog_profiling_ffi.lib	49.03 MB	49.03 MB	0% (0 B) 👌

libdatadog-x86-windows

Artifact	Baseline	Commit	Change
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.dll	22.05 MB	22.05 MB	0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.lib	89.82 KB	89.82 KB	0% (0 B) 👌
/libdatadog-x86-windows/debug/dynamic/datadog_profiling_ffi.pdb	188.76 MB	188.77 MB	+0% (+16.00 KB) 👌
/libdatadog-x86-windows/debug/static/datadog_profiling_ffi.lib	935.45 MB	935.45 MB	0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.dll	6.43 MB	6.43 MB	0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.lib	89.82 KB	89.82 KB	0% (0 B) 👌
/libdatadog-x86-windows/release/dynamic/datadog_profiling_ffi.pdb	26.43 MB	26.43 MB	0% (0 B) 👌
/libdatadog-x86-windows/release/static/datadog_profiling_ffi.lib	46.66 MB	46.66 MB	0% (0 B) 👌

x86_64-alpine-linux-musl

Artifact	Baseline	Commit	Change
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.a	76.58 MB	76.58 MB	0% (0 B) 👌
/x86_64-alpine-linux-musl/lib/libdatadog_profiling.so	8.78 MB	8.78 MB	0% (0 B) 👌

x86_64-unknown-linux-gnu

Artifact	Baseline	Commit	Change
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.a	92.10 MB	92.10 MB	0% (0 B) 👌
/x86_64-unknown-linux-gnu/lib/libdatadog_profiling.so	10.69 MB	10.69 MB	0% (0 B) 👌

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Allows to encode metric payloads using V3 columnar format. This library enables users to encode their metric payloads using an efficient column-based protocol. For performance and compatibility reasons (we also want to keep this crate `no_std` so we could use it in very resource-constrained environments) this crate does manual protobuf serialization. Signed-off-by: Mark Kirichenko <mark.kirichenko@datadoghq.com>

github-actions Bot added the ci-build label Jul 10, 2026

atanzu force-pushed the mark.kirichenko/AGTMETRICS-536/add-metrics-v3-encoder branch from db0bdea to f0b893c Compare July 10, 2026 12:42

atanzu force-pushed the mark.kirichenko/AGTMETRICS-536/add-metrics-v3-encoder branch 2 times, most recently from f6a9fc0 to a743570 Compare July 10, 2026 14:28

atanzu marked this pull request as ready for review July 10, 2026 15:19

atanzu requested review from a team as code owners July 10, 2026 15:19

chatgpt-codex-connector Bot reviewed Jul 10, 2026

View reviewed changes

Comment thread libdd-metrics-v3/src/writer.rs

Comment thread libdd-metrics-v3/src/writer.rs

Comment thread libdd-metrics-v3/src/writer.rs

Comment thread libdd-metrics-v3/src/writer.rs Outdated

Comment thread libdd-metrics-v3/src/writer.rs

atanzu force-pushed the mark.kirichenko/AGTMETRICS-536/add-metrics-v3-encoder branch from a743570 to 8f065a5 Compare July 16, 2026 07:59

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feat(metrics-v3): add Datadog V3 payload encoder#2223

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What does this PR do?

Motivation

Additional Notes

How to test the change?

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📚 Documentation Check Results

📦 libdd-metrics-v3 - 1 warning(s)

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🔒 Cargo Deny Results

📦 libdd-metrics-v3 - ✅ No issues

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Benchmarks

Comparison

Explanation

More details about the CI and significant changes

scenario:msgpack_decoder::v05/high_sharing/2000

scenario:msgpack_decoder::v05/low_sharing/10000

scenario:msgpack_decoder::v05/low_sharing/200

scenario:msgpack_decoder::v05/low_sharing/2000

scenario:otlp/e2e_json/1x1000

scenario:otlp/encode_json/1x1000

scenario:vec_map/as_deduped_map/already_deduped/16

scenario:vec_map/as_deduped_map/already_deduped/8

scenario:vec_map/contains_key/128

scenario:vec_map/contains_key/16

scenario:vec_map/contains_key/64

scenario:vec_map/contains_key/8

scenario:vec_map/get_hit/128

scenario:vec_map/get_hit/16

scenario:vec_map/get_hit/64

scenario:vec_map/get_hit/8

scenario:vec_map/get_miss/128

scenario:vec_map/get_miss/16

scenario:vec_map/get_miss/64

scenario:vec_map/get_miss/8

scenario:vec_map/get_mut/128

scenario:vec_map/get_mut/16

scenario:vec_map/get_mut/64

Explanation

More details about the CI and significant changes

scenario:alloc_free/sampled_system_fast_path/4096

scenario:alloc_free/sampled_system_slow_path/16

scenario:alloc_free/sampled_system_slow_path/256

scenario:alloc_free/sampled_system_slow_path/4096

scenario:alloc_free/sampled_system_slow_path/64

scenario:alloc_free/sampled_system_slow_path/65536

scenario:credit_card/is_card_number/ 3782-8224-6310-005

scenario:credit_card/is_card_number/ 378282246310005

scenario:credit_card/is_card_number/378282246310005

scenario:credit_card/is_card_number/37828224631000521389798

scenario:credit_card/is_card_number_no_luhn/ 378282246310005

scenario:credit_card/is_card_number_no_luhn/378282246310005

scenario:credit_card/is_card_number_no_luhn/37828224631000521389798

scenario:glob_matcher/ascii_case_insensitive_match/wall_time

scenario:glob_matcher/ascii_exact_match/wall_time

scenario:glob_matcher/ascii_exact_miss/wall_time

scenario:glob_matcher/unicode_pattern_ascii_subject/wall_time

scenario:receiver_entry_point/report/2644

scenario:sql/obfuscate_sql_string

scenario:trace_buffer/4_senders/no_delay

Candidate

Baseline

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Artifact Size Benchmark Report

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📦 `libdd-metrics-v3` - 1 warning(s)

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📦 `libdd-metrics-v3` - ✅ No issues

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