CWS: sync BTFHub constants

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What does this PR do?

This PR syncs the BTFHub constants used by CWS
This PR was autogenerated

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On pipeline 34021805 (CI Visibility). The following jobs did not run any unit tests:

Jobs:

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

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/merge

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Regression Detector

Regression Detector Results

Run ID: f20c8017-6f41-4aa1-b2b4-13d201266ef8
Baseline: 3e03e40
Comparison: 99ca471

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	+8.92	[+7.65, +10.19]

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI
❌	file_to_blackhole	% cpu utilization	+8.92	[+7.65, +10.19]
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	+2.82	[-0.07, +5.70]
➖	basic_py_check	% cpu utilization	+1.81	[-0.69, +4.30]
➖	otel_to_otel_logs	ingress throughput	+0.21	[-0.18, +0.60]
➖	idle	memory utilization	+0.14	[+0.10, +0.18]
➖	uds_dogstatsd_to_api	ingress throughput	+0.02	[-0.19, +0.22]
➖	trace_agent_msgpack	ingress throughput	+0.00	[-0.00, +0.00]
➖	trace_agent_json	ingress throughput	+0.00	[-0.01, +0.01]
➖	tcp_dd_logs_filter_exclude	ingress throughput	-0.01	[-0.05, +0.02]
➖	file_tree	memory utilization	-0.48	[-0.58, -0.38]
➖	pycheck_1000_100byte_tags	% cpu utilization	-0.79	[-5.49, +3.91]
➖	tcp_syslog_to_blackhole	ingress throughput	-7.23	[-27.42, +12.96]

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".