Skip to content

Conversation

@AlexandreYang
Copy link
Member

@AlexandreYang AlexandreYang commented Jan 12, 2026

PR by Bits
View Dev Agent Session

You can ask for changes by mentioning @DataDog in a comment.

Feedback (especially what can be better) welcome in #code-gen-feedback!


What does this PR do?

Adds a new networkpath bundle to the private action runner with a traceroute action.

The bundle:

  • Creates a new com.datadoghq.networkpath bundle with the traceroute action
  • Uses the existing traceroute.Component for executing traceroutes
  • Accepts configuration parameters: hostname, port, sourceService, destinationService, maxTTL, protocol, tcpMethod, timeout, tracerouteQueries, e2eQueries, and namespace
  • Returns the full NetworkPath payload as output

Motivation

Enable network path tracing capabilities through the private action runner framework.

Describe how you validated your changes

  • Added unit tests for the traceroute handler in pkg/privateactionrunner/bundles/networkpath/traceroute_test.go
  • Tests cover successful execution, error handling, and config mapping
  • All files formatted with gofmt

Additional Notes

  • The traceroute.Component is injected as an optional dependency via option.Option[traceroute.Component]
  • The bundle is only registered when the traceroute component is available
  • Follows the existing bundle pattern in pkg/privateactionrunner/bundles/

@datadog-datadog-prod-us1
Copy link
Contributor

datadog-datadog-prod-us1 bot commented Jan 12, 2026

Bits AI Dev Agent Status: ✅ Done [Fix CI Errors] [View Dev Agent Session]

Status History (2 entries)
2026-01-12 23:00:57 UTC ✅ Processed user query
2026-01-12 23:02:17 UTC ✅ Pushed a commit per user request

You can ask for changes by mentioning @DataDog in a comment.

@github-actions github-actions bot added the medium review PR review might take time label Jan 12, 2026
@agent-platform-auto-pr
Copy link
Contributor

Static quality checks

✅ Please find below the results from static quality gates
Comparison made with ancestor a991a9c
📊 Static Quality Gates Dashboard

Successful checks

Info

Quality gate Change Size (prev → curr → max)
agent_deb_amd64 -16.98 KiB (0.00% reduction) 705.336 → 705.319 → 708.410
agent_deb_amd64_fips -16.98 KiB (0.00% reduction) 700.617 → 700.601 → 704.000
agent_heroku_amd64 -16.98 KiB (0.01% reduction) 326.935 → 326.919 → 329.530
agent_msi -17.2 KiB (0.00% reduction) 571.471 → 571.454 → 982.080
agent_rpm_amd64 -16.98 KiB (0.00% reduction) 705.322 → 705.306 → 708.380
agent_rpm_amd64_fips -16.98 KiB (0.00% reduction) 700.604 → 700.587 → 703.990
agent_rpm_arm64 -16.98 KiB (0.00% reduction) 686.906 → 686.890 → 693.520
agent_rpm_arm64_fips -16.98 KiB (0.00% reduction) 682.989 → 682.972 → 688.480
agent_suse_amd64 -16.98 KiB (0.00% reduction) 705.322 → 705.306 → 708.380
agent_suse_amd64_fips -16.98 KiB (0.00% reduction) 700.604 → 700.587 → 703.990
agent_suse_arm64 -16.98 KiB (0.00% reduction) 686.906 → 686.890 → 693.520
agent_suse_arm64_fips -16.98 KiB (0.00% reduction) 682.989 → 682.972 → 688.480
docker_agent_amd64 -16.98 KiB (0.00% reduction) 767.549 → 767.532 → 770.720
docker_agent_arm64 -16.98 KiB (0.00% reduction) 773.692 → 773.676 → 780.200
docker_agent_jmx_amd64 -16.98 KiB (0.00% reduction) 958.427 → 958.411 → 961.600
docker_agent_jmx_arm64 -16.99 KiB (0.00% reduction) 953.290 → 953.274 → 959.800
15 successful checks with minimal change (< 2 KiB)
Quality gate Current Size
docker_cluster_agent_amd64 180.788 MiB
docker_cluster_agent_arm64 196.618 MiB
docker_cws_instrumentation_amd64 7.135 MiB
docker_cws_instrumentation_arm64 6.689 MiB
docker_dogstatsd_amd64 38.808 MiB
docker_dogstatsd_arm64 37.128 MiB
dogstatsd_deb_amd64 30.031 MiB
dogstatsd_deb_arm64 28.176 MiB
dogstatsd_rpm_amd64 30.031 MiB
dogstatsd_suse_amd64 30.031 MiB
iot_agent_deb_amd64 43.037 MiB
iot_agent_deb_arm64 40.155 MiB
iot_agent_deb_armhf 40.736 MiB
iot_agent_rpm_amd64 43.038 MiB
iot_agent_suse_amd64 43.038 MiB
On-wire sizes (compressed)
Quality gate Change Size (prev → curr → max)
agent_deb_amd64 neutral 173.355 MiB
agent_deb_amd64_fips -79.47 KiB (0.05% reduction) 172.299 → 172.222 → 173.750
agent_heroku_amd64 -11.2 KiB (0.01% reduction) 87.131 → 87.120 → 88.450
agent_msi +4.0 KiB (0.00% increase) 142.906 → 142.910 → 143.020
agent_rpm_amd64 -27.18 KiB (0.02% reduction) 176.128 → 176.101 → 177.660
agent_rpm_amd64_fips -19.42 KiB (0.01% reduction) 175.048 → 175.029 → 176.600
agent_rpm_arm64 +29.07 KiB (0.02% increase) 159.362 → 159.391 → 161.260
agent_rpm_arm64_fips -7.82 KiB (0.00% reduction) 158.778 → 158.770 → 160.550
agent_suse_amd64 -27.18 KiB (0.02% reduction) 176.128 → 176.101 → 177.660
agent_suse_amd64_fips -19.42 KiB (0.01% reduction) 175.048 → 175.029 → 176.600
agent_suse_arm64 +29.07 KiB (0.02% increase) 159.362 → 159.391 → 161.260
agent_suse_arm64_fips -7.82 KiB (0.00% reduction) 158.778 → 158.770 → 160.550
docker_agent_amd64 -6.43 KiB (0.00% reduction) 261.082 → 261.076 → 262.450
docker_agent_arm64 -2.87 KiB (0.00% reduction) 250.112 → 250.109 → 252.630
docker_agent_jmx_amd64 +2.53 KiB (0.00% increase) 329.711 → 329.714 → 331.080
docker_agent_jmx_arm64 -10.63 KiB (0.00% reduction) 314.740 → 314.730 → 317.270
docker_cluster_agent_amd64 neutral 63.877 MiB
docker_cluster_agent_arm64 neutral 60.160 MiB
docker_cws_instrumentation_amd64 neutral 2.994 MiB
docker_cws_instrumentation_arm64 neutral 2.726 MiB
docker_dogstatsd_amd64 neutral 15.026 MiB
docker_dogstatsd_arm64 neutral 14.351 MiB
dogstatsd_deb_amd64 neutral 7.945 MiB
dogstatsd_deb_arm64 neutral 6.824 MiB
dogstatsd_rpm_amd64 neutral 7.956 MiB
dogstatsd_suse_amd64 neutral 7.956 MiB
iot_agent_deb_amd64 neutral 11.275 MiB
iot_agent_deb_arm64 -2.23 KiB (0.02% reduction) 9.641 → 9.639 → 10.450
iot_agent_deb_armhf neutral 9.834 MiB
iot_agent_rpm_amd64 -2.14 KiB (0.02% reduction) 11.293 → 11.291 → 12.060
iot_agent_suse_amd64 -2.14 KiB (0.02% reduction) 11.293 → 11.291 → 12.060

@cit-pr-commenter
Copy link

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: efbb120a-25b0-43ae-a9fd-a4fd5aa236dd

Baseline: adfcd28
Comparison: b74c9d7
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 +2.17 [-0.79, +5.13] 1 Logs

Fine details of change detection per experiment

perf experiment goal Δ mean % Δ mean % CI trials links
docker_containers_cpu % cpu utilization +2.17 [-0.79, +5.13] 1 Logs
quality_gate_logs % cpu utilization +0.61 [-0.87, +2.09] 1 Logs bounds checks dashboard
quality_gate_metrics_logs memory utilization +0.61 [+0.39, +0.83] 1 Logs bounds checks dashboard
ddot_metrics memory utilization +0.39 [+0.18, +0.60] 1 Logs
ddot_metrics_sum_delta memory utilization +0.17 [-0.03, +0.38] 1 Logs
file_to_blackhole_1000ms_latency egress throughput +0.02 [-0.39, +0.44] 1 Logs
uds_dogstatsd_to_api_v3 ingress throughput +0.01 [-0.12, +0.13] 1 Logs
tcp_dd_logs_filter_exclude ingress throughput +0.00 [-0.07, +0.08] 1 Logs
uds_dogstatsd_to_api ingress throughput +0.00 [-0.13, +0.13] 1 Logs
file_tree memory utilization +0.00 [-0.05, +0.05] 1 Logs
file_to_blackhole_100ms_latency egress throughput -0.03 [-0.08, +0.02] 1 Logs
ddot_metrics_sum_cumulativetodelta_exporter memory utilization -0.04 [-0.27, +0.19] 1 Logs
file_to_blackhole_500ms_latency egress throughput -0.05 [-0.42, +0.33] 1 Logs
quality_gate_idle memory utilization -0.05 [-0.10, -0.01] 1 Logs bounds checks dashboard
otlp_ingest_logs memory utilization -0.06 [-0.16, +0.04] 1 Logs
file_to_blackhole_0ms_latency egress throughput -0.09 [-0.48, +0.30] 1 Logs
quality_gate_idle_all_features memory utilization -0.31 [-0.35, -0.28] 1 Logs bounds checks dashboard
uds_dogstatsd_20mb_12k_contexts_20_senders memory utilization -0.36 [-0.41, -0.30] 1 Logs
tcp_syslog_to_blackhole ingress throughput -0.45 [-0.52, -0.37] 1 Logs
docker_containers_memory memory utilization -0.48 [-0.55, -0.40] 1 Logs
ddot_metrics_sum_cumulative memory utilization -0.51 [-0.67, -0.36] 1 Logs
otlp_ingest_metrics memory utilization -0.75 [-0.91, -0.60] 1 Logs
ddot_logs memory utilization -1.23 [-1.31, -1.16] 1 Logs

Bounds Checks: ❌ Failed

perf experiment bounds_check_name replicates_passed links
docker_containers_cpu simple_check_run 10/10
docker_containers_memory memory_usage 10/10
docker_containers_memory simple_check_run 10/10
file_to_blackhole_0ms_latency lost_bytes 10/10
file_to_blackhole_0ms_latency memory_usage 10/10
file_to_blackhole_1000ms_latency lost_bytes 10/10
file_to_blackhole_1000ms_latency memory_usage 10/10
file_to_blackhole_100ms_latency lost_bytes 10/10
file_to_blackhole_100ms_latency memory_usage 10/10
file_to_blackhole_500ms_latency lost_bytes 10/10
file_to_blackhole_500ms_latency memory_usage 10/10
quality_gate_idle intake_connections 10/10 bounds checks dashboard
quality_gate_idle memory_usage 10/10 bounds checks dashboard
quality_gate_idle_all_features intake_connections 10/10 bounds checks dashboard
quality_gate_idle_all_features memory_usage 10/10 bounds checks dashboard
quality_gate_logs intake_connections 10/10 bounds checks dashboard
quality_gate_logs lost_bytes 10/10 bounds checks dashboard
quality_gate_logs memory_usage 10/10 bounds checks dashboard
quality_gate_metrics_logs cpu_usage 10/10 bounds checks dashboard
quality_gate_metrics_logs intake_connections 10/10 bounds checks dashboard
quality_gate_metrics_logs lost_bytes 10/10 bounds checks dashboard
quality_gate_metrics_logs memory_usage 9/10 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

Failed. Some Quality Gates were violated.

  • 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.
  • 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_metrics_logs, bounds check lost_bytes: 10/10 replicas passed. Gate passed.
  • quality_gate_metrics_logs, bounds check memory_usage: 9/10 replicas passed. Failed 1 which is > 0. Gate FAILED.
  • quality_gate_metrics_logs, bounds check cpu_usage: 10/10 replicas passed. Gate passed.
  • quality_gate_metrics_logs, bounds check intake_connections: 10/10 replicas passed. Gate passed.
  • quality_gate_logs, bounds check lost_bytes: 10/10 replicas passed. Gate passed.
  • quality_gate_logs, bounds check memory_usage: 10/10 replicas passed. Gate passed.
  • quality_gate_logs, bounds check intake_connections: 10/10 replicas passed. Gate passed.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Labels

Bits AI medium review PR review might take time

Projects

None yet

Development

Successfully merging this pull request may close these issues.

2 participants