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macos: add ai-usage native host to agent repo#49565

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hongshi/package_ai_native_host
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macos: add ai-usage native host to agent repo#49565
guohdd wants to merge 5 commits intomainfrom
hongshi/package_ai_native_host

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@guohdd guohdd commented Apr 18, 2026

What does this PR do?

This PR adds ai-usage native host to agent repo.

Motivation

WINA-2457

Describe how you validated your changes

Validate through agent packaging, installation, and end-to-end messaging.

Additional Notes

@guohdd guohdd added changelog/no-changelog No changelog entry needed qa/done QA done before merge and regressions are covered by tests labels Apr 18, 2026
@dd-octo-sts dd-octo-sts bot added internal Identify a non-fork PR team/agent-configuration labels Apr 18, 2026
@github-actions github-actions bot added the long review PR is complex, plan time to review it label Apr 18, 2026
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dd-octo-sts bot commented Apr 18, 2026

Files inventory check summary

File checks results against ancestor 345902e2:

Results for datadog-agent_7.80.0~devel.git.41.df4472b.pipeline.108386484-1_amd64.deb:

No change detected

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cit-pr-commenter-54b7da bot commented Apr 18, 2026

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: 25961264-d524-4340-8376-46df47d31cd2

Baseline: 345902e
Comparison: df4472b
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
docker_containers_cpu % cpu utilization -0.03 [-3.05, +2.99] 1 Logs

Fine details of change detection per experiment

perf experiment goal Δ mean % Δ mean % CI trials links
tcp_syslog_to_blackhole ingress throughput +0.57 [+0.40, +0.74] 1 Logs
ddot_metrics_sum_delta memory utilization +0.32 [+0.14, +0.50] 1 Logs
ddot_metrics_sum_cumulative memory utilization +0.23 [+0.07, +0.38] 1 Logs
ddot_logs memory utilization +0.20 [+0.15, +0.26] 1 Logs
ddot_metrics memory utilization +0.19 [+0.01, +0.37] 1 Logs
otlp_ingest_logs memory utilization +0.14 [+0.03, +0.25] 1 Logs
ddot_metrics_sum_cumulativetodelta_exporter memory utilization +0.05 [-0.17, +0.27] 1 Logs
uds_dogstatsd_20mb_12k_contexts_20_senders memory utilization +0.04 [-0.02, +0.11] 1 Logs
file_to_blackhole_0ms_latency egress throughput +0.03 [-0.49, +0.55] 1 Logs
file_to_blackhole_1000ms_latency egress throughput +0.01 [-0.42, +0.44] 1 Logs
tcp_dd_logs_filter_exclude ingress throughput +0.01 [-0.10, +0.11] 1 Logs
file_to_blackhole_100ms_latency egress throughput +0.00 [-0.11, +0.12] 1 Logs
file_to_blackhole_500ms_latency egress throughput +0.00 [-0.39, +0.39] 1 Logs
uds_dogstatsd_to_api ingress throughput -0.00 [-0.21, +0.20] 1 Logs
uds_dogstatsd_to_api_v3 ingress throughput -0.02 [-0.22, +0.19] 1 Logs
docker_containers_cpu % cpu utilization -0.03 [-3.05, +2.99] 1 Logs
file_tree memory utilization -0.05 [-0.11, +0.02] 1 Logs
quality_gate_idle_all_features memory utilization -0.06 [-0.10, -0.02] 1 Logs bounds checks dashboard
docker_containers_memory memory utilization -0.07 [-0.15, +0.01] 1 Logs
otlp_ingest_metrics memory utilization -0.14 [-0.29, +0.02] 1 Logs
quality_gate_idle memory utilization -0.35 [-0.41, -0.30] 1 Logs bounds checks dashboard
quality_gate_metrics_logs memory utilization -0.94 [-1.18, -0.71] 1 Logs bounds checks dashboard
quality_gate_logs % cpu utilization -3.01 [-4.64, -1.38] 1 Logs bounds checks dashboard

Bounds Checks: ✅ Passed

perf experiment bounds_check_name replicates_passed observed_value links
docker_containers_cpu simple_check_run 10/10 718 ≥ 26
docker_containers_memory memory_usage 10/10 276.48MiB ≤ 370MiB
docker_containers_memory simple_check_run 10/10 679 ≥ 26
file_to_blackhole_0ms_latency memory_usage 10/10 0.19GiB ≤ 1.20GiB
file_to_blackhole_0ms_latency missed_bytes 10/10 0B = 0B
file_to_blackhole_1000ms_latency memory_usage 10/10 0.24GiB ≤ 1.20GiB
file_to_blackhole_1000ms_latency missed_bytes 10/10 0B = 0B
file_to_blackhole_100ms_latency memory_usage 10/10 0.20GiB ≤ 1.20GiB
file_to_blackhole_100ms_latency missed_bytes 10/10 0B = 0B
file_to_blackhole_500ms_latency memory_usage 10/10 0.22GiB ≤ 1.20GiB
file_to_blackhole_500ms_latency missed_bytes 10/10 0B = 0B
quality_gate_idle intake_connections 10/10 4 = 4 bounds checks dashboard
quality_gate_idle memory_usage 10/10 175.90MiB ≤ 181MiB bounds checks dashboard
quality_gate_idle_all_features intake_connections 10/10 4 = 4 bounds checks dashboard
quality_gate_idle_all_features memory_usage 10/10 501.75MiB ≤ 550MiB bounds checks dashboard
quality_gate_logs intake_connections 10/10 4 ≤ 6 bounds checks dashboard
quality_gate_logs memory_usage 10/10 215.23MiB ≤ 220MiB bounds checks dashboard
quality_gate_logs missed_bytes 10/10 0B = 0B bounds checks dashboard
quality_gate_metrics_logs cpu_usage 10/10 359.83 ≤ 2000 bounds checks dashboard
quality_gate_metrics_logs intake_connections 10/10 4 ≤ 6 bounds checks dashboard
quality_gate_metrics_logs memory_usage 10/10 401.82MiB ≤ 475MiB bounds checks dashboard
quality_gate_metrics_logs missed_bytes 10/10 0B = 0B bounds checks dashboard

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".

CI Pass/Fail Decision

Passed. All Quality Gates passed.

  • quality_gate_metrics_logs, bounds check cpu_usage: 10/10 replicas passed. Gate passed.
  • quality_gate_metrics_logs, bounds check missed_bytes: 10/10 replicas passed. Gate passed.
  • quality_gate_metrics_logs, bounds check intake_connections: 10/10 replicas passed. Gate passed.
  • quality_gate_metrics_logs, bounds check memory_usage: 10/10 replicas passed. Gate passed.
  • quality_gate_logs, bounds check intake_connections: 10/10 replicas passed. Gate passed.
  • quality_gate_logs, bounds check missed_bytes: 10/10 replicas passed. Gate passed.
  • quality_gate_logs, bounds check memory_usage: 10/10 replicas passed. Gate passed.
  • quality_gate_idle, bounds check intake_connections: 10/10 replicas passed. Gate passed.
  • quality_gate_idle, bounds check memory_usage: 10/10 replicas passed. Gate passed.
  • quality_gate_idle_all_features, bounds check memory_usage: 10/10 replicas passed. Gate passed.
  • quality_gate_idle_all_features, bounds check intake_connections: 10/10 replicas passed. Gate passed.

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