[CONTP-60] Improved telemetry on cluster check configs dangling

[gabedos]

What does this PR do?

Adds a new telemetry metric to keep track of cluster check configs that have gone an extended period of time without being scheduled.

Motivation

We would like to monitor the state of the cluster-check scheduling in order to be sure we detect issues before applications get paged for missing metrics.

Describe how you validated your changes

Existing unit tests cover dispatching logic. Only added a wrapper to count number of reschedule attempts and this has been tested by a new unit test.

Possible Drawbacks / Trade-offs

N/A

Additional Notes

Previously, on each rescheduling attempt, all the dangling configs were deleted from the dangling store initially. If they failed to be rescheduled, then they would be readded the dangling config store.

This PR changes this behavior because we want to track how long the config exists in the dangling state. Hence, we only remove the config from the dangling store once it's confirmed to be scheduled.

[cit-pr-commenter]

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: 5a5dff13-2911-4155-b36e-d3d01c8d81c7

Baseline: 5bd602d
Comparison: e7b7ccb
Diff

Optimization Goals: ✅ No significant changes detected

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	quality_gate_logs	% cpu utilization	+3.46	[+0.21, +6.70]	1	Logs
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	+1.05	[+0.36, +1.74]	1	Logs
➖	tcp_syslog_to_blackhole	ingress throughput	+0.53	[+0.48, +0.59]	1	Logs
➖	file_to_blackhole_500ms_latency	egress throughput	+0.37	[-0.39, +1.14]	1	Logs
➖	file_to_blackhole_1000ms_latency_linear_load	egress throughput	+0.21	[-0.27, +0.68]	1	Logs
➖	file_tree	memory utilization	+0.17	[+0.04, +0.29]	1	Logs
➖	file_to_blackhole_0ms_latency	egress throughput	+0.08	[-0.76, +0.93]	1	Logs
➖	file_to_blackhole_0ms_latency_http2	egress throughput	+0.08	[-0.83, +0.98]	1	Logs
➖	file_to_blackhole_300ms_latency	egress throughput	+0.02	[-0.62, +0.66]	1	Logs
➖	file_to_blackhole_0ms_latency_http1	egress throughput	+0.01	[-0.80, +0.82]	1	Logs
➖	uds_dogstatsd_to_api	ingress throughput	+0.01	[-0.11, +0.12]	1	Logs
➖	tcp_dd_logs_filter_exclude	ingress throughput	+0.00	[-0.01, +0.01]	1	Logs
➖	file_to_blackhole_100ms_latency	egress throughput	-0.03	[-0.75, +0.70]	1	Logs
➖	quality_gate_idle	memory utilization	-0.04	[-0.07, +0.00]	1	Logs bounds checks dashboard
➖	quality_gate_idle_all_features	memory utilization	-0.12	[-0.20, -0.04]	1	Logs bounds checks dashboard
➖	file_to_blackhole_1000ms_latency	egress throughput	-0.34	[-1.14, +0.46]	1	Logs
➖	otel_to_otel_logs	ingress throughput	-0.54	[-1.20, +0.13]	1	Logs

Bounds Checks: ❌ Failed

perf	experiment	bounds_check_name	replicates_passed	links
❌	file_to_blackhole_0ms_latency	lost_bytes	9/10
❌	file_to_blackhole_0ms_latency_http2	lost_bytes	9/10
✅	file_to_blackhole_0ms_latency	memory_usage	10/10
✅	file_to_blackhole_0ms_latency_http1	lost_bytes	10/10
✅	file_to_blackhole_0ms_latency_http1	memory_usage	10/10
✅	file_to_blackhole_0ms_latency_http2	memory_usage	10/10
✅	file_to_blackhole_1000ms_latency	memory_usage	10/10
✅	file_to_blackhole_1000ms_latency_linear_load	memory_usage	10/10
✅	file_to_blackhole_100ms_latency	lost_bytes	10/10
✅	file_to_blackhole_100ms_latency	memory_usage	10/10
✅	file_to_blackhole_300ms_latency	lost_bytes	10/10
✅	file_to_blackhole_300ms_latency	memory_usage	10/10
✅	file_to_blackhole_500ms_latency	lost_bytes	10/10
✅	file_to_blackhole_500ms_latency	memory_usage	10/10
✅	quality_gate_idle	memory_usage	10/10	bounds checks dashboard
✅	quality_gate_idle_all_features	memory_usage	10/10	bounds checks dashboard
✅	quality_gate_logs	lost_bytes	10/10
✅	quality_gate_logs	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".

CI Pass/Fail Decision

✅ Passed. All Quality Gates passed.

• quality_gate_idle, bounds check memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_idle_all_features, bounds check memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_logs, bounds check memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_logs, bounds check lost_bytes: 10/10 replicas passed. Gate passed.