[Orchestrator] update code structure

[kangyili]

What does this PR do?

Update code structure for orchestrator check, this PR is required by #22060

Motivation

Additional Notes

Possible Drawbacks / Trade-offs

Describe how to test/QA your changes

[cit-pr-commenter]

Go Package Import Differences

Baseline: 75a3f61
Comparison: 52fb6a1

binary	os	arch	change
agent	linux	amd64	+1, -0 +github.com/DataDog/datadog-agent/pkg/collector/corechecks/cluster/orchestrator/processors/common
agent	linux	arm64	+1, -0 +github.com/DataDog/datadog-agent/pkg/collector/corechecks/cluster/orchestrator/processors/common
agent	windows	amd64	+1, -0 +github.com/DataDog/datadog-agent/pkg/collector/corechecks/cluster/orchestrator/processors/common
agent	darwin	amd64	+1, -0 +github.com/DataDog/datadog-agent/pkg/collector/corechecks/cluster/orchestrator/processors/common
agent	darwin	arm64	+1, -0 +github.com/DataDog/datadog-agent/pkg/collector/corechecks/cluster/orchestrator/processors/common
cluster-agent	linux	amd64	+1, -0 +github.com/DataDog/datadog-agent/pkg/collector/corechecks/cluster/orchestrator/processors/common
cluster-agent	linux	arm64	+1, -0 +github.com/DataDog/datadog-agent/pkg/collector/corechecks/cluster/orchestrator/processors/common

[pr-commenter]

Bloop Bleep... Dogbot Here

Regression Detector Results

Run ID: 3fc3594c-c28a-48cf-b3f0-15fced2c6c55
Baseline: b4f0a17
Comparison: e9f189ec43fbdcb677f0d8e10dcf64a0a5f52fe6

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	+0.55	[-5.79, +6.90]

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI
➖	otel_to_otel_logs	ingress throughput	+1.86	[+1.20, +2.51]
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	+1.44	[-1.31, +4.18]
➖	basic_py_check	% cpu utilization	+1.20	[-1.23, +3.64]
➖	file_to_blackhole	% cpu utilization	+0.55	[-5.79, +6.90]
➖	tcp_dd_logs_filter_exclude	ingress throughput	+0.03	[-0.03, +0.09]
➖	trace_agent_msgpack	ingress throughput	+0.00	[-0.00, +0.01]
➖	uds_dogstatsd_to_api	ingress throughput	+0.00	[-0.06, +0.06]
➖	trace_agent_json	ingress throughput	+0.00	[-0.01, +0.01]
➖	process_agent_standard_check	memory utilization	-0.32	[-0.35, -0.28]
➖	pycheck_1000_100byte_tags	% cpu utilization	-0.41	[-5.37, +4.55]
➖	idle	memory utilization	-0.43	[-0.46, -0.39]
➖	process_agent_real_time_mode	memory utilization	-0.50	[-0.54, -0.47]
➖	file_tree	memory utilization	-0.75	[-0.84, -0.67]
➖	process_agent_standard_check_with_stats	memory utilization	-0.81	[-0.84, -0.78]
➖	tcp_syslog_to_blackhole	ingress throughput	-0.90	[-0.98, -0.82]

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".

[fisherevans]

looks cleaner. only concern is this pattern:

func (h *StatefulSetHandlers) BuildMessageBody(ctx processors.ProcessorContext, resourceModels []interface{}, groupSize int) model.MessageBody {
	pctx := ctx.(*processors.K8sProcessorContext)

this conversion would panic if someone wired up the dependencies wrong - ideally we'd use either generics or at least type checking to confirm the type. But this is a pattern used elsewhere, so not a blocker for me.

[kangyili]

Sorry about the noise. I rebased my branch and it triggered review requests automatically

[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=30348729 --os-family=ubuntu

[pr-commenter]

Regression Detector

Regression Detector Results

Run ID: e6efea28-29c6-49b2-8a80-bb3828c5e7da
Baseline: 75a3f61
Comparison: 52fb6a1

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	+1.87	[-4.56, +8.30]

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI
➖	file_to_blackhole	% cpu utilization	+1.87	[-4.56, +8.30]
➖	process_agent_standard_check	memory utilization	+0.37	[+0.34, +0.40]
➖	idle	memory utilization	+0.29	[+0.26, +0.32]
➖	process_agent_real_time_mode	memory utilization	+0.18	[+0.15, +0.21]
➖	process_agent_standard_check_with_stats	memory utilization	+0.05	[+0.02, +0.09]
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	+0.03	[-2.72, +2.78]
➖	trace_agent_json	ingress throughput	+0.01	[-0.03, +0.05]
➖	uds_dogstatsd_to_api	ingress throughput	+0.00	[-0.20, +0.21]
➖	tcp_dd_logs_filter_exclude	ingress throughput	-0.00	[-0.03, +0.02]
➖	trace_agent_msgpack	ingress throughput	-0.02	[-0.03, -0.01]
➖	otel_to_otel_logs	ingress throughput	-0.05	[-0.48, +0.39]
➖	file_tree	memory utilization	-0.17	[-0.26, -0.08]
➖	tcp_syslog_to_blackhole	ingress throughput	-0.42	[-0.50, -0.33]
➖	pycheck_1000_100byte_tags	% cpu utilization	-0.55	[-5.44, +4.34]
➖	basic_py_check	% cpu utilization	-1.43	[-3.94, +1.08]

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".

[kangyili]

/merge

[dd-devflow]

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