feat(dogstatsd): add units for timed metrics

[atanzu]

Summary

Send unit information for aggregate metrics calculated from timed metrics.

Currently there is no way to distinguish between abstract histograms and timed metrics which are represented as histograms. To disambiguate, we send the unit information with the aggregate metrics calculated from the histogram values.

Change Type

• Bug fix
• New feature
• Non-functional (chore, refactoring, docs)
• Performance

How did you test this PR?

• added autotests to validate the new code.
• did an end-to-end test with a personal account to confirm that timed metrics have units:

References

• Closes: AGTMETRICS-433

[chatgpt-codex-connector]

💡 Codex Review

Here are some automated review suggestions for this pull request.

Reviewed commit: 399dd0254b

ℹ️ About Codex in GitHub

Codex has been enabled to automatically review pull requests in this repo. Reviews are triggered when you

• Open a pull request for review
• Mark a draft as ready
• Comment "@codex review".

If Codex has suggestions, it will comment; otherwise it will react with 👍.

When you sign up for Codex through ChatGPT, Codex can also answer questions or update the PR, like "@codex address that feedback".

[tobz]

We should use MetaString instead of Arc<str> because otherwise we're always allocating for a string that can be inlined.

[pr-commenter]

Binary Size Analysis (Agent Data Plane)

Target: 507d913 (baseline) vs a53e5a9 (comparison) diff
Analysis Type: Stripped binaries (debug symbols excluded)
Baseline Size: 36.78 MiB
Comparison Size: 36.78 MiB
Size Change: +5.10 KiB (+0.01%)
Pass/Fail Threshold: +5%
Result: PASSED ✅

Changes by Module

Module	File Size	Symbols
saluki_env::helpers::remote_agent	+22.18 KiB	2
backon	-16.86 KiB	1
tower_layer	-9.07 KiB	9
tonic	+4.33 KiB	11
anon.556381182ece2d1a34385503d73c0a9e.62.llvm.2819371484686640837	+3.47 KiB	1
anon.94dd6a447bf9f9fbd0442074f35f7515.1.llvm.5913085556691654484	-3.47 KiB	1
anon.f553f6e9457fd909f79c926efd29eb66.22.llvm.1648316244533297028	+2.63 KiB	1
anon.40340ab29c26454e228b882d4ecb70d4.0.llvm.14605026808982526804	-2.63 KiB	1
tokio_util	+2.41 KiB	6
[sections]	+2.17 KiB	7
saluki_components::transforms::aggregate	+2.00 KiB	3
h2	-1.87 KiB	24
anon.f83dfb2c1817ba3cab755df2ab972865.513.llvm.15290961048654791904	-1.70 KiB	1
anon.3c5982eca991f49048e400a152bf1b31.1.llvm.14102024339487881263	+1.69 KiB	1
anon.ecdd43b268ff7a1e667e42f6ad0a8f5e.120.llvm.12321406416096248332	-1.66 KiB	1
anon.0fe9e463a009e606f5a30416b38b62f1.3.llvm.9230630131155697409	+1.66 KiB	1
otlp_protos::otlp_include::opentelemetry	+1.40 KiB	32
anon.ff07114ed2750c9bbe4cae6748dc8434.728.llvm.15665205255274019542	+1.33 KiB	1
anon.3ed47645e4aa12c6a9402ef231b44275.5.llvm.12051301733971437701	-1.33 KiB	1
saluki_io::deser::framing	-1.24 KiB	2

Detailed Symbol Changes

    FILE SIZE        VM SIZE    
 --------------  -------------- 
  [NEW] +21.8Ki  [NEW] +21.6Ki    saluki_env::helpers::remote_agent::client::RemoteAgentClient::from_configuration::_{{closure}}::_{{closure}}::_{{closure}}::hd91eede76d55b01a
  [NEW] +3.67Ki  [NEW] +3.50Ki    _<futures_util::future::try_future::AndThen<Fut1,Fut2,F> as core::future::future::Future>::poll::h262539ce92b8b8ea
  [NEW] +3.47Ki  [NEW]     +16    anon.556381182ece2d1a34385503d73c0a9e.62.llvm.2819371484686640837
  [NEW] +2.63Ki  [NEW]     +80    anon.f553f6e9457fd909f79c926efd29eb66.22.llvm.1648316244533297028
  [NEW] +2.56Ki  [NEW]    +147    _<std::sync::poison::PoisonError<T> as core::fmt::Debug>::fmt::hd6b6612e86e8e73c
   +98% +2.19Ki  +103% +2.19Ki    tonic::transport::channel::service::connection::Connection::new::h4781e93189c77695
   +88% +2.06Ki   +92% +2.06Ki    tonic::transport::channel::service::connection::Connection::new::h62edff03ab540486
  +7.2% +2.00Ki  +7.3% +2.00Ki    _<saluki_components::transforms::aggregate::Aggregate as saluki_core::components::transforms::Transform>::run::_{{closure}}::hf3bb4cb9d5f8836a
  [NEW] +1.89Ki  [NEW] +1.07Ki    core::ptr::drop_in_place<saluki_core::data_model::event::metric::metadata::MetricMetadata>::h585763ecc6b086e0
  [NEW] +1.79Ki  [NEW]    +315    core::ptr::drop_in_place<tokio::sync::mpsc::bounded::Permit<saluki_components::sources::otlp::OtlpResource>>::h4e161ccc5730da5a
  [NEW] +1.69Ki  [NEW]     +97    anon.3c5982eca991f49048e400a152bf1b31.1.llvm.14102024339487881263
  [NEW] +1.66Ki  [NEW]     +77    anon.0fe9e463a009e606f5a30416b38b62f1.3.llvm.9230630131155697409
  [DEL] -1.66Ki  [DEL]     -77    anon.ecdd43b268ff7a1e667e42f6ad0a8f5e.120.llvm.12321406416096248332
  [DEL] -1.70Ki  [DEL]     -97    anon.f83dfb2c1817ba3cab755df2ab972865.513.llvm.15290961048654791904
  [DEL] -1.70Ki  [DEL] -1.02Ki    core::ptr::drop_in_place<saluki_core::data_model::event::metric::metadata::MetricMetadata>::hb3a7e3a5c655a987
  [DEL] -1.80Ki  [DEL]    -315    core::ptr::drop_in_place<tokio::sync::mpsc::bounded::Permit<saluki_components::relays::otlp::OtlpPayload>>::hf384fa397e3644cb
  [DEL] -2.63Ki  [DEL]     -80    anon.40340ab29c26454e228b882d4ecb70d4.0.llvm.14605026808982526804
  [DEL] -3.47Ki  [DEL]     -16    anon.94dd6a447bf9f9fbd0442074f35f7515.1.llvm.5913085556691654484
  [DEL] -3.73Ki  [DEL] -3.50Ki    _<futures_util::future::try_future::try_flatten::TryFlatten<Fut,<Fut as futures_core::future::TryFuture>::Ok> as core::future::future::Future>::poll::hc4f1f75d8f6192a2
  -0.1% -8.80Ki  -0.1% -6.04Ki    [6983 Others]
 -91.4% -16.9Ki -92.2% -16.9Ki    _<backon::retry::Retry<B,T,E,Fut,FutureFn,SF$C&C$NF,AF> as core::future::future::Future>::poll::he82a83420d3eaeff
  +0.0% +5.10Ki  +0.0% +5.16Ki    TOTAL

[pr-commenter]

Regression Detector (Agent Data Plane)

Regression Detector Results

Run ID: e054e046-3629-4561-ad27-e567a1b7bb7d

Baseline: 507d913
Comparison: a53e5a9
Diff

Optimization Goals: ✅ No significant changes detected

Experiments ignored for regressions

Regressions in experiments with settings containing erratic: true are ignored.

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	otlp_ingest_logs_5mb_memory	memory utilization	+2.30	[+1.99, +2.61]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_logs_5mb_throughput	ingress throughput	+0.02	[-0.10, +0.15]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_logs_5mb_cpu	% cpu utilization	-2.47	[-7.10, +2.15]	1	(metrics) (profiles) (logs)

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	otlp_ingest_metrics_5mb_memory	memory utilization	+4.29	[+4.09, +4.49]	1	(metrics) (profiles) (logs)
➖	dsd_uds_10mb_3k_contexts_cpu	% cpu utilization	+3.22	[-26.23, +32.67]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_traces_5mb_cpu	% cpu utilization	+2.60	[+0.68, +4.51]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_logs_5mb_memory	memory utilization	+2.30	[+1.99, +2.61]	1	(metrics) (profiles) (logs)
➖	quality_gates_rss_dsd_heavy	memory utilization	+1.40	[+1.27, +1.53]	1	(metrics) (profiles) (logs)
➖	quality_gates_rss_dsd_ultraheavy	memory utilization	+1.03	[+0.90, +1.16]	1	(metrics) (profiles) (logs)
➖	quality_gates_rss_dsd_medium	memory utilization	+0.72	[+0.56, +0.89]	1	(metrics) (profiles) (logs)
➖	dsd_uds_500mb_3k_contexts_memory	memory utilization	+0.59	[+0.45, +0.74]	1	(metrics) (profiles) (logs)
➖	quality_gates_rss_idle	memory utilization	+0.41	[+0.37, +0.44]	1	(metrics) (profiles) (logs)
➖	dsd_uds_1mb_3k_contexts_memory	memory utilization	+0.38	[+0.23, +0.53]	1	(metrics) (profiles) (logs)
➖	dsd_uds_10mb_3k_contexts_memory	memory utilization	+0.38	[+0.22, +0.54]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_traces_5mb_throughput	ingress throughput	+0.34	[+0.26, +0.41]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_traces_ottl_filtering_5mb_throughput	ingress throughput	+0.18	[+0.10, +0.25]	1	(metrics) (profiles) (logs)
➖	quality_gates_rss_dsd_low	memory utilization	+0.14	[-0.02, +0.31]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_traces_ottl_filtering_5mb_memory	memory utilization	+0.07	[-0.17, +0.31]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_logs_5mb_throughput	ingress throughput	+0.02	[-0.10, +0.15]	1	(metrics) (profiles) (logs)
➖	dsd_uds_512kb_3k_contexts_memory	memory utilization	+0.01	[-0.13, +0.16]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_metrics_5mb_throughput	ingress throughput	+0.01	[-0.16, +0.17]	1	(metrics) (profiles) (logs)
➖	dsd_uds_10mb_3k_contexts_throughput	ingress throughput	+0.01	[-0.16, +0.17]	1	(metrics) (profiles) (logs)
➖	dsd_uds_1mb_3k_contexts_throughput	ingress throughput	+0.00	[-0.06, +0.06]	1	(metrics) (profiles) (logs)
➖	dsd_uds_512kb_3k_contexts_throughput	ingress throughput	-0.00	[-0.05, +0.05]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_traces_ottl_transform_5mb_throughput	ingress throughput	-0.00	[-0.08, +0.07]	1	(metrics) (profiles) (logs)
➖	dsd_uds_100mb_3k_contexts_throughput	ingress throughput	-0.01	[-0.05, +0.03]	1	(metrics) (profiles) (logs)
➖	dsd_uds_100mb_3k_contexts_memory	memory utilization	-0.04	[-0.19, +0.12]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_traces_ottl_transform_5mb_memory	memory utilization	-0.12	[-0.28, +0.04]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_traces_5mb_memory	memory utilization	-0.17	[-0.33, -0.00]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_metrics_5mb_cpu	% cpu utilization	-0.28	[-5.92, +5.37]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_traces_ottl_filtering_5mb_cpu	% cpu utilization	-0.47	[-2.84, +1.90]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_traces_ottl_transform_5mb_cpu	% cpu utilization	-0.57	[-2.59, +1.45]	1	(metrics) (profiles) (logs)
➖	dsd_uds_100mb_3k_contexts_cpu	% cpu utilization	-0.76	[-6.40, +4.88]	1	(metrics) (profiles) (logs)
➖	dsd_uds_500mb_3k_contexts_cpu	% cpu utilization	-0.83	[-2.23, +0.57]	1	(metrics) (profiles) (logs)
➖	dsd_uds_512kb_3k_contexts_cpu	% cpu utilization	-0.97	[-56.63, +54.69]	1	(metrics) (profiles) (logs)
➖	dsd_uds_500mb_3k_contexts_throughput	ingress throughput	-1.27	[-1.39, -1.15]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_logs_5mb_cpu	% cpu utilization	-2.47	[-7.10, +2.15]	1	(metrics) (profiles) (logs)
➖	dsd_uds_1mb_3k_contexts_cpu	% cpu utilization	-3.50	[-55.36, +48.35]	1	(metrics) (profiles) (logs)

Bounds Checks: ✅ Passed

perf	experiment	bounds_check_name	replicates_passed	observed_value	links
✅	quality_gates_rss_dsd_heavy	memory_usage	10/10	122.66MiB ≤ 140MiB	(metrics) (profiles) (logs)
✅	quality_gates_rss_dsd_low	memory_usage	10/10	40.11MiB ≤ 50MiB	(metrics) (profiles) (logs)
✅	quality_gates_rss_dsd_medium	memory_usage	10/10	62.03MiB ≤ 75MiB	(metrics) (profiles) (logs)
✅	quality_gates_rss_dsd_ultraheavy	memory_usage	10/10	178.83MiB ≤ 200MiB	(metrics) (profiles) (logs)
✅	quality_gates_rss_idle	memory_usage	10/10	27.55MiB ≤ 40MiB	(metrics) (profiles) (logs)

Explanation

Confidence level: 90.00%
Effect size tolerance: |Δ mean %| ≥ 5.00%

Performance changes are noted in the perf column of each table:

• ✅ = significantly better comparison variant performance
• ❌ = significantly worse comparison variant performance
• ➖ = no significant change in performance

A regression test is an A/B test of target performance in a repeatable rig, where "performance" is measured as "comparison variant minus baseline variant" for an optimization goal (e.g., ingress throughput). Due to intrinsic variability in measuring that goal, we can only estimate its mean value for each experiment; we report uncertainty in that value as a 90.00% confidence interval denoted "Δ mean % CI".

For each experiment, we decide whether a change in performance is a "regression" -- a change worth investigating further -- if all of the following criteria are true:

1. Its estimated |Δ mean %| ≥ 5.00%, indicating the change is big enough to merit a closer look.

2. Its 90.00% confidence interval "Δ mean % CI" does not contain zero, indicating that if our statistical model is accurate, there is at least a 90.00% chance there is a difference in performance between baseline and comparison variants.

3. Its configuration does not mark it "erratic".

[tobz]

LGTM. 👍🏻