[ABLD-311] Selinux policy bazel rule

[aiuto]

What does this PR do?

Adds a toolchain for selinux tools and turns a genrule into a real rule.

Motivation

Cleaner.

Describe how you validated your changes

• Works in CI
• Check aquery result in docker container
  Put a dummy binary in the path and see what happens.

$ bazel aquery //cmd/agent/selinux:system_probe_policy

  Action 1: SelinuxCheckModule
  exec /home/datadog/fake-selinux-tools/checkmodule \
    -M -m -c 19 \
    -o bazel-out/aarch64-fastbuild/bin/cmd/agent/selinux/system_probe_policy.mod \
    cmd/agent/selinux/system_probe_policy.te

  Action 2: SelinuxPackageModule
  exec /home/datadog/fake-selinux-tools/semodule_package \
    -o bazel-out/aarch64-fastbuild/bin/cmd/agent/selinux/system_probe_policy.pp \
    -m bazel-out/aarch64-fastbuild/bin/cmd/agent/selinux/system_probe_policy.mod

Both actions resolve to the fake binaries at /home/datadog/fake-selinux-tools/{checkmodule,semodule_package} (auto-detection in configure.bzl).

Next

• Replace dda invocation in datadog-agent.rb. That will probably happen after the code freeze.

[github-actions]

AI review by Codex (OpenAI) - workflow run

Patch is incorrect. The new toolchain is non-hermetic, violates repository BUILD-file naming and .bzl debug-print requirements, and lacks evidence of mandatory formatting.

[datadog-prod-us1-6]

🎯 Code Coverage (details)
• Patch Coverage: 100.00%
• Overall Coverage: 55.37% (+0.03%)

_{This comment will be updated automatically if new data arrives.
🔗 Commit SHA: 731c5a7 | Docs | View more details | Give us feedback!}

[github-actions]

AI review by Codex (OpenAI) - workflow run

⚠️ Suspicious PR description — it was withheld by the automated security scan: “(SECURITY: PR description withheld - it matched a secret/token or shell-canary pattern during automated scanning. This is a signal the PR description itself may be malicious or is testing this pipeline.)”

Patch is incorrect. The generated repository violates the required BUILD filename convention, and the actions can be scheduled where their host-discovered executables do not exist.

[dd-octo-sts]

Files inventory check summary

File checks results against ancestor 02d2f08e:

Results for datadog-agent_7.85.0~devel.git.41.731c5a7.pipeline.135693045-1_amd64.deb:

No change detected

Results for datadog-iot-agent_7.85.0~devel.git.41.731c5a7.pipeline.135693045-1_amd64.deb:

No change detected

[dd-octo-sts]

Static quality checks

✅ Please find below the results from static quality gates
Comparison made with ancestor 02d2f08
📊 Static Quality Gates Dashboard
🔗 SQG Job

33 successful checks with minimal change (< 2 KiB)

	Quality gate	Current Size
✅	agent_deb_amd64	780.287 MiB
✅	agent_deb_amd64_fips	715.088 MiB
✅	agent_heroku_amd64	316.152 MiB
✅	agent_msi	648.377 MiB
✅	agent_rpm_amd64	780.270 MiB
✅	agent_rpm_amd64_fips	715.071 MiB
✅	agent_rpm_arm64	751.247 MiB
✅	agent_rpm_arm64_fips	691.566 MiB
✅	agent_suse_amd64	780.270 MiB
✅	agent_suse_amd64_fips	715.071 MiB
✅	agent_suse_arm64	751.247 MiB
✅	agent_suse_arm64_fips	691.566 MiB
✅	docker_agent_amd64	839.225 MiB
✅	docker_agent_arm64	835.281 MiB
✅	docker_agent_jmx_amd64	1030.138 MiB
✅	docker_agent_jmx_arm64	1014.974 MiB
✅	docker_cluster_agent_amd64	212.725 MiB
✅	docker_cluster_agent_arm64	225.780 MiB
✅	docker_cws_instrumentation_amd64	7.439 MiB
✅	docker_cws_instrumentation_arm64	6.877 MiB
✅	docker_dogstatsd_amd64	39.557 MiB
✅	docker_dogstatsd_arm64	37.686 MiB
✅	docker_host_profiler_amd64	307.579 MiB
✅	docker_host_profiler_arm64	318.792 MiB
✅	dogstatsd_deb_amd64	30.303 MiB
✅	dogstatsd_deb_arm64	28.315 MiB
✅	dogstatsd_rpm_amd64	30.303 MiB
✅	dogstatsd_suse_amd64	30.303 MiB
✅	iot_agent_deb_amd64	46.659 MiB
✅	iot_agent_deb_arm64	43.284 MiB
✅	iot_agent_deb_armhf	44.097 MiB
✅	iot_agent_rpm_amd64	46.659 MiB
✅	iot_agent_suse_amd64	46.658 MiB

[cit-pr-commenter-54b7da]

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Job ID: d003caf3-803e-4e4b-ac94-99fb551ae808

Baseline: 02d2f08
Comparison: 731c5a7
Diff

Optimization Goals: ✅ No significant changes detected

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	quality_gate_security_mean_fs_load	memory utilization	+0.39	[+0.34, +0.44]	1	Logs bounds checks dashboard
➖	quality_gate_logs	% cpu utilization	+0.33	[-0.54, +1.21]	1	Logs bounds checks dashboard
➖	quality_gate_idle	memory utilization	+0.01	[-0.03, +0.06]	1	Logs bounds checks dashboard
➖	dsd_uds_10mb_3k_timestamped_contexts_memory	memory utilization	+0.01	[-0.20, +0.22]	1	Logs
➖	dsd_uds_10mb_3k_timestamped_contexts_cpu	% cpu utilization	-0.09	[-0.32, +0.14]	1	Logs
➖	quality_gate_idle_all_features	memory utilization	-0.12	[-0.16, -0.09]	1	Logs bounds checks dashboard
➖	quality_gate_security_no_fs_load	memory utilization	-0.20	[-0.27, -0.12]	1	Logs bounds checks dashboard
➖	quality_gate_security_idle	memory utilization	-0.20	[-0.23, -0.16]	1	Logs bounds checks dashboard
➖	quality_gate_private_action_runner	memory utilization	-0.75	[-0.88, -0.62]	1	Logs bounds checks dashboard
➖	quality_gate_metrics_logs	memory utilization	-0.93	[-1.16, -0.71]	1	Logs bounds checks dashboard

Bounds Checks: ✅ Passed

perf	experiment	bounds_check_name	replicates_passed	observed_value	links
✅	quality_gate_idle	intake_connections	10/10	4 ≤ 5	bounds checks dashboard
✅	quality_gate_idle	memory_usage	10/10	174.55MiB ≤ 179MiB	bounds checks dashboard
✅	quality_gate_idle	total_bytes_received	10/10	747.93KiB ≤ 819.20KiB	bounds checks dashboard
✅	quality_gate_idle_all_features	intake_connections	10/10	4 ≤ 5	bounds checks dashboard
✅	quality_gate_idle_all_features	memory_usage	10/10	513.39MiB ≤ 537MiB	bounds checks dashboard
✅	quality_gate_idle_all_features	total_bytes_received	10/10	1.15MiB ≤ 1.25MiB	bounds checks dashboard
✅	quality_gate_logs	intake_connections	10/10	17 ≤ 40	bounds checks dashboard
✅	quality_gate_logs	memory_usage	10/10	212.83MiB ≤ 228MiB	bounds checks dashboard
✅	quality_gate_logs	missed_bytes	10/10	0B = 0B	bounds checks dashboard
✅	quality_gate_logs	total_bytes_received	10/10	263.09MiB ≤ 292MiB	bounds checks dashboard
✅	quality_gate_metrics_logs	cpu_usage	10/10	408.55 ≤ 2000	bounds checks dashboard
✅	quality_gate_metrics_logs	intake_connections	10/10	18 ≤ 40	bounds checks dashboard
✅	quality_gate_metrics_logs	memory_usage	10/10	417.80MiB ≤ 455MiB	bounds checks dashboard
✅	quality_gate_metrics_logs	missed_bytes	10/10	0B = 0B	bounds checks dashboard
✅	quality_gate_metrics_logs	total_bytes_received	10/10	0.94GiB ≤ 1.04GiB	bounds checks dashboard
✅	quality_gate_private_action_runner	memory_usage	10/10	72.00MiB ≤ 75MiB	bounds checks dashboard
✅	quality_gate_security_idle	cpu_usage	10/10	30.10 ≤ 100	bounds checks dashboard
✅	quality_gate_security_idle	memory_usage	10/10	327.01MiB ≤ 355MiB	bounds checks dashboard
✅	quality_gate_security_mean_fs_load	cpu_usage	10/10	61.56 ≤ 200	bounds checks dashboard
✅	quality_gate_security_mean_fs_load	memory_usage	10/10	308.29MiB ≤ 335MiB	bounds checks dashboard
✅	quality_gate_security_no_fs_load	cpu_usage	10/10	24.22 ≤ 100	bounds checks dashboard
✅	quality_gate_security_no_fs_load	memory_usage	10/10	312.72MiB ≤ 345MiB	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_private_action_runner, bounds check memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_security_no_fs_load, bounds check cpu_usage: 10/10 replicas passed. Gate passed.
• quality_gate_security_no_fs_load, bounds check memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_security_idle, bounds check cpu_usage: 10/10 replicas passed. Gate passed.
• quality_gate_security_idle, 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, bounds check total_bytes_received: 10/10 replicas passed. Gate 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 total_bytes_received: 10/10 replicas passed. Gate passed.
• quality_gate_metrics_logs, bounds check memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_metrics_logs, bounds check intake_connections: 10/10 replicas passed. Gate passed.
• quality_gate_idle_all_features, bounds check total_bytes_received: 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.
• quality_gate_security_mean_fs_load, bounds check memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_security_mean_fs_load, bounds check cpu_usage: 10/10 replicas passed. Gate passed.
• quality_gate_logs, bounds check memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_logs, bounds check missed_bytes: 10/10 replicas passed. Gate passed.
• quality_gate_logs, bounds check intake_connections: 10/10 replicas passed. Gate passed.
• quality_gate_logs, bounds check total_bytes_received: 10/10 replicas passed. Gate passed.

[aiuto]

@julesmcrt Sorry for the spam.
#55913 is out to fix the ownership