[Backport 7.58.x] [ksm] Init a single kubelet reflector for all pod collectors

[agent-platform-auto-pr]

Backport 9610ef9 from #29145.

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What does this PR do?

This is an optimization for the PR that introduced the option to emit KSM pod metrics from the node agent: #28811

In that first version there was a kubelet pod watcher instantiated for each KSM metrics pod collector. By default there are two pod collectors, the standard one and the "pods_extended" one.

This PR changes that so that only one pod watcher is instantiated and used for all the collectors.
I've also simplified the tests a bit.

Describe how to test/QA your changes

Testing #28811 plus the unit tests should be enough.

[agent-platform-auto-pr]

[Fast Unit Tests Report]

On pipeline 43964943 (CI Visibility). The following jobs did not run any unit tests:

Jobs:

• tests_flavor_dogstatsd_deb-x64
• tests_flavor_heroku_deb-x64
• tests_flavor_iot_deb-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-devx-help

[pr-commenter]

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=43964943 --os-family=ubuntu

Note: This applies to commit 3b89b69

[pr-commenter]

Regression Detector

Regression Detector Results

Run ID: bf90264b-315d-4fde-b266-5ae878082148 Metrics dashboard Target profiles

Baseline: e509535
Comparison: 3b89b69

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	trials	links
➖	idle	memory utilization	+0.48	[+0.44, +0.53]	1	Logs
➖	tcp_syslog_to_blackhole	ingress throughput	+0.13	[+0.09, +0.18]	1	Logs
➖	pycheck_lots_of_tags	% cpu utilization	+0.04	[-2.60, +2.67]	1	Logs
➖	uds_dogstatsd_to_api	ingress throughput	+0.00	[-0.00, +0.00]	1	Logs
➖	tcp_dd_logs_filter_exclude	ingress throughput	+0.00	[-0.01, +0.01]	1	Logs
➖	otel_to_otel_logs	ingress throughput	-0.07	[-0.90, +0.76]	1	Logs
➖	file_tree	memory utilization	-0.08	[-0.19, +0.03]	1	Logs
➖	basic_py_check	% cpu utilization	-1.46	[-4.10, +1.18]	1	Logs
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	-1.57	[-2.35, -0.78]	1	Logs

Bounds Checks

perf	experiment	bounds_check_name	replicates_passed
❌	idle	memory_usage	7/10

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".

[davidor]

/merge

[dd-devflow]

🚂 MergeQueue: pull request added to the queue

The median merge time in 7.58.x is 22m.

Use /merge -c to cancel this operation!