[CONTINT-4412] Switch back to static client and structured types for KSM check

[L3n41c]

What does this PR do?

Switch back to static client and structured types for kubernetes_state_core check.

Motivation

In #30061, we had to migrate the kubernetes_state_core check to use the dynamic client to avoid a panic in the upstream kube-state-metrics module: https://gitlab.ddbuild.io/DataDog/datadog-agent/-/jobs/682846491

panic: interface conversion: interface {} is *v1.Job, not *unstructured.Unstructured [recovered]
        	panic: interface conversion: interface {} is *v1.Job, not *unstructured.Unstructured
        
        goroutine 456 [running]:
        k8s.io/apimachinery/pkg/util/runtime.handleCrash({0x5edd188, 0x9086b80}, {0x4508180, 0xc0012e5b90}, {0x9086b80, 0x0, 0x100000000000000?})
        	/go/pkg/mod/k8s.io/[email protected]/pkg/util/runtime/runtime.go:89 +0xee
        k8s.io/apimachinery/pkg/util/runtime.HandleCrash({0x0, 0x0, 0xc00144be48?})
        	/go/pkg/mod/k8s.io/[email protected]/pkg/util/runtime/runtime.go:59 +0x108
        panic({0x4508180?, 0xc0012e5b90?})
        	/usr/local/go/src/runtime/panic.go:770 +0x132
        k8s.io/kube-state-metrics/v2/pkg/util.GVRFromType({0x4cab54f?, 0xc001938f80?}, {0x4c24440?, 0xc000f74a08?})
        	/go/pkg/mod/k8s.io/kube-state-metrics/[email protected]/pkg/util/utils.go:145 +0x1a6
        k8s.io/kube-state-metrics/v2/internal/store.(*Builder).WithCustomResourceStoreFactories(0xc001939088?, {0xc00071b540, 0x5, 0xc001b10c01?})
        	/go/pkg/mod/k8s.io/kube-state-metrics/[email protected]/internal/store/builder.go:200 +0xb5
        k8s.io/kube-state-metrics/v2/pkg/builder.(*Builder).WithCustomResourceStoreFactories(0xc0007ae510?, {0xc00071b540?, 0xc001a82900?, 0x9?})
        	/go/pkg/mod/k8s.io/kube-state-metrics/[email protected]/pkg/builder/builder.go:130 +0x22
        github.com/DataDog/datadog-agent/pkg/kubestatemetrics/builder.(*Builder).WithCustomResourceStoreFactories(...)
        	/go/src/github.com/DataDog/datadog-agent/pkg/kubestatemetrics/builder/builder.go:129
        github.com/DataDog/datadog-agent/pkg/collector/corechecks/cluster/ksm.(*KSMCheck).Configure(0xc00[1881](https://gitlab.ddbuild.io/DataDog/datadog-agent/-/jobs/682846491#L1881)e60, {0x5edd8f8, 0xc0013d6180}, 0x0?, {0xc001920600, 0x193, 0x200}, {0x0, 0x0, 0x0}, ...)
        	/go/src/github.com/DataDog/datadog-agent/pkg/collector/corechecks/cluster/ksm/kubernetes_state.go:359 +0x119a

kubernetes/kube-state-metrics#2553 aims at addressing this issue so that using dynamic client and unstructured types shouldn’t be needed anymore.
As structured types are more efficient than unstructured ones, it would be better, if possible to switch back to them.

Describe how to test/QA your changes

Validate that kubernetes_state_core checks works fine.

Possible Drawbacks / Trade-offs

Additional Notes

Rely on kubernetes/kube-state-metrics#2553

As this PR partially reverts some of the changes of #30061, it might be smart to compare the code with what we had before with something like:

git diff c86d1e0bb79bf5ace65d9085917024ce52e86729^..lenaic/CONTINT-4412_2 pkg/collector/corechecks/cluster/ksm/customresources

[agent-platform-auto-pr]

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=48599856 --os-family=ubuntu

Note: This applies to commit 040814f

[L3n41c]

This is the commit of kubernetes/kube-state-metrics#2553.

To be updated as soon as this PR is merged.

[cit-pr-commenter]

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: 2ab40d59-3979-4f55-a589-81701178299b

Baseline: c86d1e0
Comparison: 040814f
Diff

Optimization Goals: ✅ No significant changes detected

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	pycheck_lots_of_tags	% cpu utilization	+1.69	[-1.79, +5.17]	1	Logs
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	+0.72	[-0.01, +1.44]	1	Logs
➖	idle_all_features	memory utilization	+0.51	[+0.39, +0.63]	1	Logs bounds checks dashboard
➖	idle	memory utilization	+0.27	[+0.22, +0.33]	1	Logs bounds checks dashboard
➖	file_to_blackhole_0ms_latency	egress throughput	+0.02	[-0.39, +0.43]	1	Logs
➖	file_to_blackhole_100ms_latency	egress throughput	+0.01	[-0.24, +0.27]	1	Logs
➖	uds_dogstatsd_to_api	ingress throughput	+0.01	[-0.08, +0.11]	1	Logs
➖	tcp_dd_logs_filter_exclude	ingress throughput	-0.00	[-0.01, +0.01]	1	Logs
➖	tcp_syslog_to_blackhole	ingress throughput	-0.02	[-0.07, +0.03]	1	Logs
➖	file_to_blackhole_300ms_latency	egress throughput	-0.05	[-0.24, +0.14]	1	Logs
➖	file_to_blackhole_1000ms_latency	egress throughput	-0.12	[-0.60, +0.37]	1	Logs
➖	file_to_blackhole_500ms_latency	egress throughput	-0.16	[-0.40, +0.08]	1	Logs
➖	quality_gate_idle_all_features	memory utilization	-0.20	[-0.35, -0.06]	1	Logs bounds checks dashboard
➖	quality_gate_idle	memory utilization	-0.46	[-0.51, -0.40]	1	Logs bounds checks dashboard
➖	basic_py_check	% cpu utilization	-1.16	[-4.85, +2.52]	1	Logs
➖	file_tree	memory utilization	-1.73	[-1.87, -1.60]	1	Logs

Bounds Checks: ❌ Failed

perf	experiment	bounds_check_name	replicates_passed	links
❌	idle	memory_usage	3/10	bounds checks dashboard
❌	quality_gate_idle_all_features	memory_usage	6/10	bounds checks dashboard
❌	quality_gate_idle	memory_usage	7/10	bounds checks dashboard
❌	file_to_blackhole_100ms_latency	lost_bytes	8/10
❌	idle_all_features	memory_usage	9/10	bounds checks dashboard
✅	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_100ms_latency	memory_usage	10/10
✅	file_to_blackhole_300ms_latency	memory_usage	10/10
✅	file_to_blackhole_500ms_latency	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".

[L3n41c]

/merge

[dd-devflow]

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2024-11-08 21:07:47 UTC ℹ️ MergeQueue: pull request added to the queue

The median merge time in main is 24m.