Add analyze-quality-gate-security-mean-fs-load skill

[preinlein]

What does this PR do?

Adds a new Claude Code skill analyze-quality-gate-security-mean-fs-load that compares production CWS perf_buffer.events.write open rates against the quality_gate_security_mean_fs_load SMP experiment, using quality_gate_security_no_fs_load as the no-load baseline, and proposes lading config changes when a mismatch is found.

Motivation

The quality_gate_security_mean_fs_load lading config should reflect production filesystem workload so the SMP regression detector catches real-world CWS overhead. This skill formalizes the comparison procedure — pinning analysis to a specific SMP job_id, subtracting the no-load noise floor, and proposing concrete YAML changes — so tuning decisions are traceable and reproducible across sessions.

Describe how you validated your changes

Skill is read-only documentation that drives pup metrics query and the existing explain-lading-config skill; no code paths are exercised. Validated by inspection of the procedure against the two regression cases under test/regression/cases/quality_gate_security_{mean,no}_fs_load/.

Additional Notes

• Adds a CODEOWNERS entry assigning the skill to @DataDog/single-machine-performance and @DataDog/agent-security.

[preinlein]

Warning

This pull request is not mergeable via GitHub because a downstack PR is open. Once all requirements are satisfied, merge this PR as a stack on Graphite.
Learn more

• Add analyze-quality-gate-security-mean-fs-load skill #50375 👈 (View in Graphite)
• Add explain-lading-config skill #50374
• Setup CWS Quality Gates #50373
• main

This stack of pull requests is managed by Graphite. Learn more about stacking.

[dd-octo-sts]

Files inventory check summary

File checks results against ancestor 8f67edd8:

Results for datadog-agent_7.80.0~devel.git.486.d1bab2e.pipeline.111593521-1_amd64.deb:

No change detected

[dd-octo-sts]

Static quality checks

✅ Please find below the results from static quality gates
Comparison made with ancestor 8f67edd
📊 Static Quality Gates Dashboard
🔗 SQG Job

32 successful checks with minimal change (< 2 KiB)

	Quality gate	Current Size
✅	agent_deb_amd64	740.963 MiB
✅	agent_deb_amd64_fips	699.147 MiB
✅	agent_heroku_amd64	309.076 MiB
✅	agent_rpm_amd64	740.946 MiB
✅	agent_rpm_amd64_fips	699.131 MiB
✅	agent_rpm_arm64	719.021 MiB
✅	agent_rpm_arm64_fips	680.300 MiB
✅	agent_suse_amd64	740.946 MiB
✅	agent_suse_amd64_fips	699.131 MiB
✅	agent_suse_arm64	719.021 MiB
✅	agent_suse_arm64_fips	680.300 MiB
✅	docker_agent_amd64	801.342 MiB
✅	docker_agent_arm64	804.245 MiB
✅	docker_agent_jmx_amd64	992.262 MiB
✅	docker_agent_jmx_arm64	983.943 MiB
✅	docker_cluster_agent_amd64	206.603 MiB
✅	docker_cluster_agent_arm64	220.634 MiB
✅	docker_cws_instrumentation_amd64	7.142 MiB
✅	docker_cws_instrumentation_arm64	6.689 MiB
✅	docker_host_profiler_amd64	301.101 MiB
✅	docker_host_profiler_arm64	312.622 MiB
✅	docker_dogstatsd_amd64	39.374 MiB
✅	docker_dogstatsd_arm64	37.628 MiB
✅	dogstatsd_deb_amd64	30.032 MiB
✅	dogstatsd_deb_arm64	28.173 MiB
✅	dogstatsd_rpm_amd64	30.032 MiB
✅	dogstatsd_suse_amd64	30.032 MiB
✅	iot_agent_deb_amd64	44.462 MiB
✅	iot_agent_deb_arm64	41.439 MiB
✅	iot_agent_deb_armhf	42.179 MiB
✅	iot_agent_rpm_amd64	44.462 MiB
✅	iot_agent_suse_amd64	44.462 MiB

On-wire sizes (compressed)

	Quality gate	Change	Size (prev → curr → max)
✅	agent_deb_amd64	+33.02 KiB (0.02% increase)	175.252 → 175.285 → 179.160
✅	agent_deb_amd64_fips	-17.38 KiB (0.01% reduction)	167.041 → 167.024 → 174.440
✅	agent_heroku_amd64	+11.15 KiB (0.01% increase)	74.949 → 74.960 → 80.310
✅	agent_rpm_amd64	+9.71 KiB (0.01% increase)	177.289 → 177.298 → 182.080
✅	agent_rpm_amd64_fips	-23.53 KiB (0.01% reduction)	168.418 → 168.395 → 174.140
✅	agent_rpm_arm64	+3.62 KiB (0.00% increase)	159.375 → 159.378 → 163.610
✅	agent_rpm_arm64_fips	-23.57 KiB (0.02% reduction)	151.753 → 151.730 → 156.850
✅	agent_suse_amd64	+9.71 KiB (0.01% increase)	177.289 → 177.298 → 182.080
✅	agent_suse_amd64_fips	-23.53 KiB (0.01% reduction)	168.418 → 168.395 → 174.140
✅	agent_suse_arm64	+3.62 KiB (0.00% increase)	159.375 → 159.378 → 163.610
✅	agent_suse_arm64_fips	-23.57 KiB (0.02% reduction)	151.753 → 151.730 → 156.850
✅	docker_agent_amd64	neutral	267.709 MiB → 272.990
✅	docker_agent_arm64	+4.23 KiB (0.00% increase)	254.715 → 254.719 → 261.470
✅	docker_agent_jmx_amd64	neutral	336.343 MiB → 341.610
✅	docker_agent_jmx_arm64	-5.71 KiB (0.00% reduction)	319.363 → 319.358 → 326.050
✅	docker_cluster_agent_amd64	neutral	72.424 MiB → 73.460
✅	docker_cluster_agent_arm64	neutral	67.884 MiB → 68.680
✅	docker_cws_instrumentation_amd64	neutral	2.999 MiB → 3.330
✅	docker_cws_instrumentation_arm64	neutral	2.729 MiB → 3.090
✅	docker_host_profiler_amd64	neutral	110.740 MiB → 125.600
✅	docker_host_profiler_arm64	neutral	105.089 MiB → 120.000
✅	docker_dogstatsd_amd64	neutral	15.240 MiB → 15.870
✅	docker_dogstatsd_arm64	neutral	14.558 MiB → 14.890
✅	dogstatsd_deb_amd64	neutral	7.943 MiB → 8.830
✅	dogstatsd_deb_arm64	neutral	6.827 MiB → 7.750
✅	dogstatsd_rpm_amd64	neutral	7.952 MiB → 8.840
✅	dogstatsd_suse_amd64	neutral	7.952 MiB → 8.840
✅	iot_agent_deb_amd64	-2.12 KiB (0.02% reduction)	11.702 → 11.700 → 13.210
✅	iot_agent_deb_arm64	neutral	9.995 MiB → 11.620
✅	iot_agent_deb_armhf	+2.39 KiB (0.02% increase)	10.209 → 10.212 → 11.780
✅	iot_agent_rpm_amd64	neutral	11.721 MiB → 13.230
✅	iot_agent_suse_amd64	neutral	11.721 MiB → 13.230

[cit-pr-commenter-54b7da]

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: 6b8a6277-91c6-47aa-b363-fdcce175306b

Baseline: 8f67edd
Comparison: d1bab2e
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	+1.05	[-1.87, +3.96]	1	Logs

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	docker_containers_cpu	% cpu utilization	+1.05	[-1.87, +3.96]	1	Logs
➖	ddot_logs	memory utilization	+0.78	[+0.72, +0.85]	1	Logs
➖	quality_gate_metrics_logs	memory utilization	+0.67	[+0.42, +0.92]	1	Logs bounds checks dashboard
➖	quality_gate_security_idle	memory utilization	+0.26	[+0.19, +0.33]	1	Logs bounds checks dashboard
➖	quality_gate_idle_all_features	memory utilization	+0.25	[+0.21, +0.29]	1	Logs bounds checks dashboard
➖	quality_gate_security_no_fs_load	memory utilization	+0.24	[+0.15, +0.34]	1	Logs bounds checks dashboard
➖	ddot_metrics	memory utilization	+0.22	[+0.03, +0.42]	1	Logs
➖	ddot_metrics_sum_delta	memory utilization	+0.21	[+0.03, +0.39]	1	Logs
➖	docker_containers_memory	memory utilization	+0.20	[+0.10, +0.30]	1	Logs
➖	quality_gate_security_mean_fs_load	memory utilization	+0.17	[+0.13, +0.20]	1	Logs bounds checks dashboard
➖	file_to_blackhole_1000ms_latency	egress throughput	+0.07	[-0.36, +0.50]	1	Logs
➖	otlp_ingest_metrics	memory utilization	+0.07	[-0.08, +0.23]	1	Logs
➖	file_to_blackhole_0ms_latency	egress throughput	+0.01	[-0.51, +0.53]	1	Logs
➖	uds_dogstatsd_to_api_v3	ingress throughput	+0.01	[-0.19, +0.22]	1	Logs
➖	tcp_dd_logs_filter_exclude	ingress throughput	+0.01	[-0.08, +0.11]	1	Logs
➖	file_to_blackhole_100ms_latency	egress throughput	-0.03	[-0.17, +0.12]	1	Logs
➖	uds_dogstatsd_to_api	ingress throughput	-0.04	[-0.26, +0.18]	1	Logs
➖	file_to_blackhole_500ms_latency	egress throughput	-0.04	[-0.44, +0.36]	1	Logs
➖	ddot_metrics_sum_cumulativetodelta_exporter	memory utilization	-0.09	[-0.33, +0.15]	1	Logs
➖	ddot_metrics_sum_cumulative	memory utilization	-0.15	[-0.31, +0.01]	1	Logs
➖	uds_dogstatsd_20mb_12k_contexts_20_senders	memory utilization	-0.27	[-0.32, -0.22]	1	Logs
➖	quality_gate_idle	memory utilization	-0.43	[-0.48, -0.38]	1	Logs bounds checks dashboard
➖	quality_gate_logs	% cpu utilization	-0.74	[-1.73, +0.24]	1	Logs bounds checks dashboard
➖	tcp_syslog_to_blackhole	ingress throughput	-0.75	[-0.96, -0.55]	1	Logs
➖	otlp_ingest_logs	memory utilization	-0.92	[-1.04, -0.81]	1	Logs

Bounds Checks: ✅ Passed

perf	experiment	bounds_check_name	replicates_passed	observed_value	links
✅	docker_containers_cpu	simple_check_run	10/10	576 ≥ 26
✅	docker_containers_memory	memory_usage	10/10	241.85MiB ≤ 370MiB
✅	docker_containers_memory	simple_check_run	10/10	723 ≥ 26
✅	file_to_blackhole_0ms_latency	memory_usage	10/10	0.16GiB ≤ 1.20GiB
✅	file_to_blackhole_0ms_latency	missed_bytes	10/10	0B = 0B
✅	file_to_blackhole_1000ms_latency	memory_usage	10/10	0.21GiB ≤ 1.20GiB
✅	file_to_blackhole_1000ms_latency	missed_bytes	10/10	0B = 0B
✅	file_to_blackhole_100ms_latency	memory_usage	10/10	0.17GiB ≤ 1.20GiB
✅	file_to_blackhole_100ms_latency	missed_bytes	10/10	0B = 0B
✅	file_to_blackhole_500ms_latency	memory_usage	10/10	0.19GiB ≤ 1.20GiB
✅	file_to_blackhole_500ms_latency	missed_bytes	10/10	0B = 0B
✅	quality_gate_idle	intake_connections	10/10	3 ≤ 4	bounds checks dashboard
✅	quality_gate_idle	memory_usage	10/10	140.34MiB ≤ 147MiB	bounds checks dashboard
✅	quality_gate_idle_all_features	intake_connections	10/10	3 ≤ 4	bounds checks dashboard
✅	quality_gate_idle_all_features	memory_usage	10/10	471.50MiB ≤ 495MiB	bounds checks dashboard
✅	quality_gate_logs	intake_connections	10/10	3 ≤ 6	bounds checks dashboard
✅	quality_gate_logs	memory_usage	10/10	174.58MiB ≤ 195MiB	bounds checks dashboard
✅	quality_gate_logs	missed_bytes	10/10	0B = 0B	bounds checks dashboard
✅	quality_gate_metrics_logs	cpu_usage	10/10	386.83 ≤ 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	384.29MiB ≤ 430MiB	bounds checks dashboard
✅	quality_gate_metrics_logs	missed_bytes	10/10	0B = 0B	bounds checks dashboard
✅	quality_gate_security_idle	cpu_usage	10/10	24.93 ≤ 40	bounds checks dashboard
✅	quality_gate_security_idle	memory_usage	10/10	287.44MiB ≤ 330MiB	bounds checks dashboard
✅	quality_gate_security_mean_fs_load	cpu_usage	10/10	55.12 ≤ 70	bounds checks dashboard
✅	quality_gate_security_mean_fs_load	memory_usage	10/10	265.17MiB ≤ 320MiB	bounds checks dashboard
✅	quality_gate_security_no_fs_load	cpu_usage	10/10	20.94 ≤ 40	bounds checks dashboard
✅	quality_gate_security_no_fs_load	memory_usage	10/10	274.20MiB ≤ 320MiB	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 memory_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 cpu_usage: 10/10 replicas passed. Gate passed.
• quality_gate_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_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 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_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_no_fs_load, 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_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.

[chatgpt-codex-connector]

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[goxberry]

This part seems potentially scriptable in the future. I don't think it's worth blocking on writing a script for this operation -- I'd rather have the skill in the repo sooner -- but worth noting as a potential variance-reducing optimization.

[goxberry]

+1; Python is probably more cross-platform than date from GNU Coreutils.

[goxberry]

The background noise floor drift is an interesting observation. I wonder if we can model that in the future.

[goxberry]

Good call-out here.