[CWS] Allow k8s-e2e-cws tests to fail

[YoannGh]

What does this PR do?

These tests can sometimes be flaky.
As we are currently in the process of removing these in favor of #25218, let's allow these to fail so that these do not impact the main branch.

Motivation

Additional Notes

Possible Drawbacks / Trade-offs

Describe how to test/QA your changes

[pr-commenter]

Regression Detector

Regression Detector Results

Run ID: 20bfe657-94f0-4a2d-88c6-546a4b39b6d1
Baseline: 49c10b7
Comparison: 5bf04dc

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.

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI
➖	pycheck_1000_100byte_tags	% cpu utilization	+1.23	[-3.69, +6.15]
➖	basic_py_check	% cpu utilization	+1.05	[-1.48, +3.58]
➖	idle	memory utilization	+0.13	[+0.09, +0.18]
➖	uds_dogstatsd_to_api	ingress throughput	+0.01	[-0.19, +0.22]
➖	trace_agent_json	ingress throughput	+0.00	[-0.01, +0.01]
➖	trace_agent_msgpack	ingress throughput	-0.02	[-0.02, -0.01]
➖	tcp_dd_logs_filter_exclude	ingress throughput	-0.02	[-0.05, +0.02]
➖	otel_to_otel_logs	ingress throughput	-0.08	[-0.44, +0.28]
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	-0.53	[-3.46, +2.39]
➖	file_tree	memory utilization	-0.63	[-0.74, -0.51]
➖	tcp_syslog_to_blackhole	ingress throughput	-11.59	[-31.71, +8.53]

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".

[paulcacheux]

/merge

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