[NPM] teste2e add logs when test failed

[nplanel]

What does this PR do?

Enable logs if any test failed, aim to debug test1HostFakeIntakeNPM

Motivation

Debug flacky tests

Additional Notes

Possible Drawbacks / Trade-offs

Describe how to test/QA your changes

[pr-commenter[bot]]

Bloop Bleep... Dogbot Here

Regression Detector Results

Run ID: ce678544-1441-4eae-bd36-f1bcdc29e082 Baseline: c6b52ff2d46479df800861fe1d2991affc430d1a Comparison: 55079fe3bc8ea9bb17b3e42ceb83bd15dcff5545

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

No significant changes in experiment optimization goals

Confidence level: 90.00% Effect size tolerance: |Δ mean %| ≥ 5.00%

There were no significant changes in experiment optimization goals at this confidence level and effect size tolerance.

Experiments ignored for regressions

Regressions in experiments with settings containing erratic: true are ignored.

perf	experiment	goal	Δ mean %	Δ mean % CI
➖	file_to_blackhole	% cpu utilization	-5.44	[-11.98, +1.11]

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI
➖	pycheck_1000_100byte_tags	% cpu utilization	+2.80	[-2.54, +8.14]
➖	basic_py_check	% cpu utilization	+2.25	[-0.12, +4.62]
➖	file_tree	memory utilization	+1.78	[+1.68, +1.89]
➖	process_agent_real_time_mode	memory utilization	+0.21	[+0.16, +0.26]
➖	process_agent_standard_check_with_stats	memory utilization	+0.16	[+0.12, +0.20]
➖	process_agent_standard_check	memory utilization	+0.08	[+0.04, +0.11]
➖	trace_agent_json	ingress throughput	+0.02	[-0.02, +0.05]
➖	tcp_dd_logs_filter_exclude	ingress throughput	-0.00	[-0.00, +0.00]
➖	uds_dogstatsd_to_api	ingress throughput	-0.00	[-0.20, +0.20]
➖	trace_agent_msgpack	ingress throughput	-0.01	[-0.01, -0.00]
➖	otel_to_otel_logs	ingress throughput	-0.20	[-0.64, +0.23]
➖	tcp_syslog_to_blackhole	ingress throughput	-0.25	[-0.35, -0.15]
➖	idle	memory utilization	-0.47	[-0.51, -0.43]
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	-0.88	[-3.87, +2.10]
➖	file_to_blackhole	% cpu utilization	-5.44	[-11.98, +1.11]

Explanation

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".

[pr-commenter[bot]]

Test changes on VM

Use this command from test-infra-definitions to manually test this PR changes on a VM:

inv create-vm --pipeline-id=30285046 --os-family=ubuntu

[pr-commenter[bot]]

Regression Detector

Regression Detector Results

Run ID: 97512128-ae20-4b0b-8764-eb3576119813 Baseline: c076b511a285f6bf0bf7e3e7d599e75dcc4c5552 Comparison: f87e2f59286a131b092c2327fe94c50aa88057d3

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

No significant changes in experiment optimization goals

Confidence level: 90.00% Effect size tolerance: |Δ mean %| ≥ 5.00%

There were no significant changes in experiment optimization goals at this confidence level and effect size tolerance.

Experiments ignored for regressions

Regressions in experiments with settings containing erratic: true are ignored.

perf	experiment	goal	Δ mean %	Δ mean % CI
➖	file_to_blackhole	% cpu utilization	-3.60	[-9.84, +2.64]

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	+1.18	[-1.57, +3.94]
➖	pycheck_1000_100byte_tags	% cpu utilization	+0.61	[-4.28, +5.50]
➖	process_agent_standard_check	memory utilization	+0.37	[+0.33, +0.40]
➖	tcp_syslog_to_blackhole	ingress throughput	+0.21	[+0.12, +0.30]
➖	otel_to_otel_logs	ingress throughput	+0.17	[-0.26, +0.60]
➖	idle	memory utilization	+0.15	[+0.12, +0.18]
➖	file_tree	memory utilization	+0.08	[-0.01, +0.17]
➖	trace_agent_json	ingress throughput	+0.05	[+0.01, +0.08]
➖	tcp_dd_logs_filter_exclude	ingress throughput	+0.03	[+0.01, +0.05]
➖	uds_dogstatsd_to_api	ingress throughput	+0.02	[-0.19, +0.22]
➖	process_agent_standard_check_with_stats	memory utilization	+0.01	[-0.02, +0.04]
➖	trace_agent_msgpack	ingress throughput	-0.00	[-0.01, +0.01]
➖	process_agent_real_time_mode	memory utilization	-0.27	[-0.30, -0.23]
➖	basic_py_check	% cpu utilization	-1.72	[-4.28, +0.83]
➖	file_to_blackhole	% cpu utilization	-3.60	[-9.84, +2.64]

Explanation

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".

[agent-platform-auto-pr[bot]]

[Fast Unit Tests Report]

Warning: On pipeline 30285046. The following jobs did not run any unit tests:

• tests_deb-arm64-py3
• tests_deb-x64-py3
• tests_flavor_dogstatsd_deb-x64
• tests_flavor_heroku_deb-x64
• tests_flavor_iot_deb-x64
• tests_rpm-arm64-py3
• tests_rpm-x64-py3
• tests_windows-x64

If you modified Go files and expected unit tests to run in these jobs, please double check the job logs. If you think tests should have been executed reach out to #agent-developer-experience

[nplanel]

new-e2e-npm https://gitlab.ddbuild.io/DataDog/datadog-agent/-/jobs/462363857

[nplanel]

/merge

[dd-devflow[bot]]

:steam_locomotive: MergeQueue

Pull request added to the queue.

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Use /merge -c to cancel this operation!