feat(aggregate): support configurable sub-10s aggregation windows

[lukesteensen]

Summary

• Introduces aggregator_bucket_size_seconds as a serde alias for the existing aggregate_window_duration, enabling sub-10s aggregation windows (e.g. 1 Hz) for the aggregated pipeline without changing default behavior.
• Pins the pass-through (pre-aggregated) batcher to the default bucket size regardless of the new knob. The wire protocol for pass-through metrics carries no client-supplied interval, so letting the knob leak there would silently reinterpret every rate sample from every client on that path.
• Accepts the config value as either an integer number of seconds (new, matches the _seconds suffix) or the legacy serde Duration struct form (preserves existing configs).

Implementation notes

• DEFAULT_BUCKET_SIZE = 10s is now the single named constant referenced everywhere the legacy value is still required.
• AggregateConfiguration::build_passthrough_batcher is the lone construction site for the pass-through batcher and encodes the pinning invariant. A comment explains why (protocol convention, not an internal knob).
• Custom deserialize_with on window_duration accepts either u64 seconds or the struct form — no new field, no resolver.

Test plan

• aggregated_counters_at_1s_bucket_width — aggregated pipeline at 1 Hz emits one series with points at the expected bucket starts, interval = 1s, and retains the open-bucket value across a subsequent flush.
• passthrough_pinned_to_default_despite_1hz_config — window_duration = 1s does not change the pass-through batcher's emitted rate interval.
• aliased_bucket_size_config_key_deserializes_as_integer_seconds — new key accepts {"aggregator_bucket_size_seconds": 1}.
• legacy_window_duration_struct_form_still_deserializes — existing {"aggregate_window_duration": {"secs": 7, "nanos": 0}} configs still work.
• Existing aggregate tests all pass.

[pr-commenter]

Binary Size Analysis (Agent Data Plane)

Target: dc8f4b9 (baseline) vs 06f3965 (comparison) diff
Analysis Type: Stripped binaries (debug symbols excluded)
Baseline Size: 37.11 MiB
Comparison Size: 37.00 MiB
Size Change: -111.50 KiB (-0.29%)
Pass/Fail Threshold: +5%
Result: PASSED ✅

Changes by Module

Module	File Size	Symbols
figment	-118.82 KiB	125
otlp_protos::otlp_include::opentelemetry	-41.79 KiB	103
hyper	+25.69 KiB	76
prost	+24.60 KiB	66
hyper_util	-14.05 KiB	13
hashbrown	+11.34 KiB	72
h2	-8.86 KiB	92
[sections]	-8.52 KiB	6
tonic	-7.37 KiB	33
core	-7.09 KiB	878
serde_core	+6.51 KiB	85
serde	+6.39 KiB	18
tower	+5.15 KiB	11
async_compression	+4.62 KiB	19
tokio_util	+3.94 KiB	14
alloc	+3.76 KiB	50
saluki_components::sources::otlp	+3.75 KiB	17
tokio	+3.67 KiB	124
saluki_core::data_model::event	-3.40 KiB	8
futures_channel	-3.35 KiB	7

Detailed Symbol Changes

    FILE SIZE        VM SIZE    
 --------------  -------------- 
  [NEW] +18.5Ki  [NEW] +18.3Ki    saluki_components::transforms::apm_stats::span_concentrator::SpanConcentrator::flush::h4cec187aab531472
  [NEW] +16.5Ki  [NEW] +16.4Ki    saluki_components::transforms::apm_stats::span_concentrator::SpanConcentrator::add_span::hf95b8e429cc5bbe0
  [NEW] +16.1Ki  [NEW] +16.0Ki    saluki_components::transforms::apm_stats::span_concentrator::SpanConcentrator::new_stat_span_from_span::h831751497d326aef
  +283% +15.9Ki  +288% +15.9Ki    h2::proto::connection::DynConnection<B>::recv_frame::h9d7adeb5727e1522
  [NEW] +12.3Ki  [NEW] +12.1Ki    _<core::marker::PhantomData<T> as serde_core::de::DeserializeSeed>::deserialize::hf9a832fc7767a946
  [NEW] +9.39Ki  [NEW] +9.23Ki    _<hyper::proto::h2::server::Server<T,S,B,E> as core::future::future::Future>::poll::h7fad89436d42473e
  +750% +6.74Ki  +828% +6.74Ki    prost::encoding::message::merge_repeated::hc52fda914c63fb75
  [NEW] +6.50Ki  [NEW] +6.28Ki    saluki_components::common::datadog::apm::_::_<impl serde_core::de::Deserialize for saluki_components::common::datadog::apm::ApmConfiguration>::deserialize::h2b55df90d15c8dc3
  +739% +6.39Ki  +819% +6.39Ki    prost::encoding::message::merge_repeated::h125609fe5afef278
  [DEL] -6.56Ki  [DEL] -6.41Ki    _<core::marker::PhantomData<T> as serde_core::de::DeserializeSeed>::deserialize::h14607bccbe25f0f5
 -24.0% -8.01Ki -24.1% -7.98Ki    _<saluki_components::transforms::apm_stats::ApmStats as saluki_core::components::transforms::Transform>::run::_{{closure}}::h63fe22416badd464
  [DEL] -8.13Ki  [DEL] -8.00Ki    figment::value::de::_<impl figment::value::value::Value>::deserialize_from::hc178e2144edf2db7
 -67.1% -9.24Ki -67.7% -9.24Ki    saluki_components::transforms::trace_obfuscation::sql::obfuscate_sql_string::hbc6c7c370aac7ff9
  [DEL] -9.49Ki  [DEL] -9.34Ki    _<figment::value::magic::Tagged<T> as figment::value::magic::Magic>::deserialize_from::h44f59c3078bb5bee
  [DEL] -9.74Ki  [DEL] -9.59Ki    _<figment::value::magic::RelativePathBuf as figment::value::magic::Magic>::deserialize_from::h795d206f112d7dfd
 -81.7% -10.1Ki -82.6% -10.1Ki    _<core::pin::Pin<P> as core::future::future::Future>::poll::h901e76ef802f2f4c
  [DEL] -11.6Ki  [DEL] -11.5Ki    _<figment::value::de::ConfiguredValueDe<I> as serde_core::de::Deserializer>::deserialize_struct::h262edabf8ad9b351
  [DEL] -15.4Ki  [DEL] -15.3Ki    _<figment::value::magic::Tagged<T> as figment::value::magic::Magic>::deserialize_from::hf4491bd4db3bec82
  [DEL] -15.9Ki  [DEL] -15.7Ki    _<figment::value::magic::RelativePathBuf as figment::value::magic::Magic>::deserialize_from::hf41c2cc956726b9d
  [DEL] -32.1Ki  [DEL] -32.0Ki    saluki_components::transforms::apm_stats::ApmStats::process_trace::h7d2f794f20a992a4
  -1.4% -83.5Ki  -1.4% -69.0Ki    [4675 Others]
  -0.3%  -111Ki  -0.3% -96.7Ki    TOTAL

[pr-commenter]

Regression Detector (Agent Data Plane)

Regression Detector Results

Run ID: 26ebc309-0848-41cc-bae6-362bc763ec27

Baseline: dc8f4b9
Comparison: 06f3965
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_throughput	ingress throughput	+0.02	[-0.10, +0.14]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_logs_5mb_cpu	% cpu utilization	-2.15	[-6.95, +2.65]	1	(metrics) (profiles) (logs)
✅	otlp_ingest_logs_5mb_memory	memory utilization	-10.69	[-11.06, -10.32]	1	(metrics) (profiles) (logs)

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	dsd_uds_10mb_3k_contexts_cpu	% cpu utilization	+6.51	[-25.35, +38.36]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_traces_ottl_filtering_5mb_cpu	% cpu utilization	+1.49	[-0.91, +3.88]	1	(metrics) (profiles) (logs)
➖	dsd_uds_500mb_3k_contexts_memory	memory utilization	+0.50	[+0.35, +0.65]	1	(metrics) (profiles) (logs)
➖	dsd_uds_512kb_3k_contexts_memory	memory utilization	+0.41	[+0.26, +0.56]	1	(metrics) (profiles) (logs)
➖	dsd_uds_100mb_3k_contexts_memory	memory utilization	+0.30	[+0.14, +0.45]	1	(metrics) (profiles) (logs)
➖	quality_gates_rss_dsd_medium	memory utilization	+0.14	[-0.03, +0.31]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_traces_5mb_throughput	ingress throughput	+0.13	[+0.06, +0.20]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_traces_5mb_memory	memory utilization	+0.07	[-0.09, +0.24]	1	(metrics) (profiles) (logs)
➖	dsd_uds_1mb_3k_contexts_memory	memory utilization	+0.04	[-0.11, +0.18]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_metrics_5mb_throughput	ingress throughput	+0.02	[-0.13, +0.17]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_logs_5mb_throughput	ingress throughput	+0.02	[-0.10, +0.14]	1	(metrics) (profiles) (logs)
➖	dsd_uds_100mb_3k_contexts_throughput	ingress throughput	+0.01	[-0.02, +0.03]	1	(metrics) (profiles) (logs)
➖	dsd_uds_1mb_3k_contexts_throughput	ingress throughput	+0.00	[-0.05, +0.06]	1	(metrics) (profiles) (logs)
➖	dsd_uds_512kb_3k_contexts_throughput	ingress throughput	+0.00	[-0.05, +0.05]	1	(metrics) (profiles) (logs)
➖	dsd_uds_10mb_3k_contexts_throughput	ingress throughput	-0.00	[-0.16, +0.16]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_traces_ottl_transform_5mb_memory	memory utilization	-0.02	[-0.18, +0.15]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_traces_ottl_filtering_5mb_memory	memory utilization	-0.03	[-0.28, +0.22]	1	(metrics) (profiles) (logs)
➖	quality_gates_rss_dsd_low	memory utilization	-0.05	[-0.21, +0.11]	1	(metrics) (profiles) (logs)
➖	quality_gates_rss_dsd_heavy	memory utilization	-0.07	[-0.20, +0.07]	1	(metrics) (profiles) (logs)
➖	dsd_uds_500mb_3k_contexts_throughput	ingress throughput	-0.07	[-0.22, +0.07]	1	(metrics) (profiles) (logs)
➖	dsd_uds_10mb_3k_contexts_memory	memory utilization	-0.10	[-0.26, +0.05]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_traces_ottl_transform_5mb_throughput	ingress throughput	-0.13	[-0.20, -0.05]	1	(metrics) (profiles) (logs)
➖	quality_gates_rss_idle	memory utilization	-0.21	[-0.25, -0.17]	1	(metrics) (profiles) (logs)
➖	quality_gates_rss_dsd_ultraheavy	memory utilization	-0.23	[-0.35, -0.10]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_traces_ottl_filtering_5mb_throughput	ingress throughput	-0.23	[-0.30, -0.15]	1	(metrics) (profiles) (logs)
➖	dsd_uds_100mb_3k_contexts_cpu	% cpu utilization	-0.80	[-6.76, +5.15]	1	(metrics) (profiles) (logs)
➖	dsd_uds_500mb_3k_contexts_cpu	% cpu utilization	-1.07	[-2.56, +0.42]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_traces_5mb_cpu	% cpu utilization	-1.23	[-3.43, +0.97]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_metrics_5mb_cpu	% cpu utilization	-1.45	[-8.59, +5.69]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_traces_ottl_transform_5mb_cpu	% cpu utilization	-1.50	[-3.49, +0.48]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_logs_5mb_cpu	% cpu utilization	-2.15	[-6.95, +2.65]	1	(metrics) (profiles) (logs)
➖	otlp_ingest_metrics_5mb_memory	memory utilization	-2.49	[-2.70, -2.28]	1	(metrics) (profiles) (logs)
➖	dsd_uds_1mb_3k_contexts_cpu	% cpu utilization	-2.65	[-54.86, +49.56]	1	(metrics) (profiles) (logs)
➖	dsd_uds_512kb_3k_contexts_cpu	% cpu utilization	-4.84	[-61.84, +52.17]	1	(metrics) (profiles) (logs)
✅	otlp_ingest_logs_5mb_memory	memory utilization	-10.69	[-11.06, -10.32]	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	119.79MiB ≤ 140MiB	(metrics) (profiles) (logs)
✅	quality_gates_rss_dsd_low	memory_usage	10/10	39.70MiB ≤ 50MiB	(metrics) (profiles) (logs)
✅	quality_gates_rss_dsd_medium	memory_usage	10/10	60.33MiB ≤ 75MiB	(metrics) (profiles) (logs)
✅	quality_gates_rss_dsd_ultraheavy	memory_usage	10/10	177.33MiB ≤ 200MiB	(metrics) (profiles) (logs)
✅	quality_gates_rss_idle	memory_usage	10/10	26.91MiB ≤ 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".