Bump github.com/DataDog/agent-payload/v5 from 5.0.137 to 5.0.138

[dependabot]

Bumps github.com/DataDog/agent-payload/v5 from 5.0.137 to 5.0.138.

Release notes

Sourced from github.com/DataDog/agent-payload/v5's releases.

v5.0.138

What's Changed

• [CWS] Add protocol field to bindNode by @​mftoure in DataDog/agent-payload#356
• [CODEOWNERS] Update processes to container-intake by @​robertjli in DataDog/agent-payload#357
• Add tags to manifest by @​aureleoules in DataDog/agent-payload#355

New Contributors

• @​mftoure made their first contribution in DataDog/agent-payload#356

Full Changelog: DataDog/agent-payload@v5.0.137...v5.0.138

Commits

• 9c811a1 Merge pull request #355 from DataDog/aurele.oules/add-tags-to-manifest
• e8f5da6 Add tags to manifest
• 756b62f Merge pull request #357 from DataDog/robertjli/PROCS-4380-cont-codeowners
• e13bfb0 [CODEOWNERS] Update processes to container-intake
• 1a267ea Merge pull request #356 from DataDog/momar/add-protocol-to-bindNode
• See full diff in compare view

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[cit-pr-commenter]

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: 2ac5d257-d3e3-4250-a398-2d262e83c511

Baseline: be4b703
Comparison: cf5d1c3
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_idle	memory utilization	+0.27	[+0.22, +0.33]	1	Logs bounds checks dashboard
➖	file_to_blackhole_300ms_latency	egress throughput	+0.23	[-0.40, +0.87]	1	Logs
➖	quality_gate_logs	% cpu utilization	+0.23	[-2.76, +3.22]	1	Logs
➖	file_tree	memory utilization	+0.05	[-0.10, +0.19]	1	Logs
➖	file_to_blackhole_100ms_latency	egress throughput	+0.03	[-0.71, +0.77]	1	Logs
➖	file_to_blackhole_0ms_latency	egress throughput	+0.02	[-0.75, +0.79]	1	Logs
➖	tcp_dd_logs_filter_exclude	ingress throughput	+0.00	[-0.01, +0.01]	1	Logs
➖	uds_dogstatsd_to_api	ingress throughput	-0.02	[-0.11, +0.08]	1	Logs
➖	pycheck_lots_of_tags	% cpu utilization	-0.02	[-3.58, +3.54]	1	Logs
➖	file_to_blackhole_1000ms_latency_linear_load	egress throughput	-0.02	[-0.48, +0.44]	1	Logs
➖	file_to_blackhole_1000ms_latency	egress throughput	-0.05	[-0.82, +0.73]	1	Logs
➖	file_to_blackhole_500ms_latency	egress throughput	-0.11	[-0.89, +0.66]	1	Logs
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	-0.29	[-1.01, +0.43]	1	Logs
➖	tcp_syslog_to_blackhole	ingress throughput	-0.30	[-0.39, -0.21]	1	Logs
➖	basic_py_check	% cpu utilization	-0.31	[-4.12, +3.51]	1	Logs
➖	otel_to_otel_logs	ingress throughput	-0.78	[-1.44, -0.12]	1	Logs
➖	quality_gate_idle_all_features	memory utilization	-0.91	[-1.03, -0.78]	1	Logs bounds checks dashboard

Bounds Checks: ❌ Failed

perf	experiment	bounds_check_name	replicates_passed	links
❌	file_to_blackhole_300ms_latency	lost_bytes	7/10
❌	file_to_blackhole_100ms_latency	lost_bytes	9/10
✅	file_to_blackhole_0ms_latency	lost_bytes	10/10
✅	file_to_blackhole_0ms_latency	memory_usage	10/10
✅	file_to_blackhole_1000ms_latency	memory_usage	10/10
✅	file_to_blackhole_1000ms_latency_linear_load	memory_usage	10/10
✅	file_to_blackhole_100ms_latency	memory_usage	10/10
✅	file_to_blackhole_300ms_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	memory_usage	10/10	bounds checks dashboard
✅	quality_gate_idle_all_features	memory_usage	10/10	bounds checks dashboard
✅	quality_gate_logs	lost_bytes	10/10
✅	quality_gate_logs	memory_usage	10/10

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_idle, bounds check memory_usage: 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_idle_all_features, bounds check memory_usage: 10/10 replicas passed. Gate passed.