CONTINT-4838 - increase test timeout for autoscalerController

[lavigne958]

The test pkg/util/kubernetes/apiserver/controllers.TestAutoscalerController is flaky, on very few occasions it takes 2 tries to complete.

1. try timeous out on the 10s timeout
2. try succeeds in a few ms.

Increase that timeout to a larger value if it fails now... it's real problem.

What does this PR do?

Motivation

Describe how you validated your changes

Additional Notes

[datadog-official]

🎯 Code Coverage (details)
• Patch Coverage: 100.00%
• Overall Coverage: 50.19% (-0.02%)

_{This comment will be updated automatically if new data arrives.
🔗 Commit SHA: e861729 | Docs | Datadog PR Page | Give us feedback!}

[dd-octo-sts]

Files inventory check summary

File checks results against ancestor 8078bf48:

Results for datadog-agent_7.80.0~devel.git.204.e861729.pipeline.109552594-1_amd64.deb:

No change detected

[cit-pr-commenter-54b7da]

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: 58c93301-55f2-477c-892f-f7c1b562af45

Baseline: 8078bf4
Comparison: e861729
Diff

Optimization Goals: ✅ No significant changes detected

Experiments ignored for regressions

Regressions in experiments with settings containing erratic: true are ignored.

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	docker_containers_cpu	% cpu utilization	+2.58	[-0.58, +5.75]	1	Logs

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	docker_containers_cpu	% cpu utilization	+2.58	[-0.58, +5.75]	1	Logs
➖	otlp_ingest_metrics	memory utilization	+0.47	[+0.32, +0.62]	1	Logs
➖	quality_gate_logs	% cpu utilization	+0.42	[-1.22, +2.06]	1	Logs bounds checks dashboard
➖	file_tree	memory utilization	+0.33	[+0.29, +0.38]	1	Logs
➖	uds_dogstatsd_20mb_12k_contexts_20_senders	memory utilization	+0.19	[+0.13, +0.24]	1	Logs
➖	ddot_metrics	memory utilization	+0.16	[-0.04, +0.36]	1	Logs
➖	ddot_logs	memory utilization	+0.16	[+0.09, +0.23]	1	Logs
➖	quality_gate_idle_all_features	memory utilization	+0.15	[+0.11, +0.19]	1	Logs bounds checks dashboard
➖	ddot_metrics_sum_cumulative	memory utilization	+0.07	[-0.09, +0.22]	1	Logs
➖	ddot_metrics_sum_cumulativetodelta_exporter	memory utilization	+0.06	[-0.17, +0.30]	1	Logs
➖	otlp_ingest_logs	memory utilization	+0.04	[-0.06, +0.15]	1	Logs
➖	uds_dogstatsd_to_api_v3	ingress throughput	+0.02	[-0.18, +0.22]	1	Logs
➖	file_to_blackhole_1000ms_latency	egress throughput	+0.01	[-0.44, +0.45]	1	Logs
➖	tcp_dd_logs_filter_exclude	ingress throughput	+0.00	[-0.11, +0.11]	1	Logs
➖	quality_gate_metrics_logs	memory utilization	+0.00	[-0.26, +0.26]	1	Logs bounds checks dashboard
➖	uds_dogstatsd_to_api	ingress throughput	-0.01	[-0.22, +0.20]	1	Logs
➖	file_to_blackhole_100ms_latency	egress throughput	-0.02	[-0.12, +0.09]	1	Logs
➖	file_to_blackhole_0ms_latency	egress throughput	-0.05	[-0.51, +0.42]	1	Logs
➖	file_to_blackhole_500ms_latency	egress throughput	-0.07	[-0.46, +0.32]	1	Logs
➖	quality_gate_idle	memory utilization	-0.11	[-0.16, -0.07]	1	Logs bounds checks dashboard
➖	ddot_metrics_sum_delta	memory utilization	-0.14	[-0.33, +0.05]	1	Logs
➖	docker_containers_memory	memory utilization	-0.59	[-0.69, -0.49]	1	Logs
➖	tcp_syslog_to_blackhole	ingress throughput	-0.88	[-1.04, -0.71]	1	Logs

Bounds Checks: ✅ Passed

perf	experiment	bounds_check_name	replicates_passed	observed_value	links
✅	docker_containers_cpu	simple_check_run	10/10	715 ≥ 26
✅	docker_containers_memory	memory_usage	10/10	238.60MiB ≤ 370MiB
✅	docker_containers_memory	simple_check_run	10/10	681 ≥ 26
✅	file_to_blackhole_0ms_latency	memory_usage	10/10	0.16GiB ≤ 1.20GiB
✅	file_to_blackhole_0ms_latency	missed_bytes	10/10	0B = 0B
✅	file_to_blackhole_1000ms_latency	memory_usage	10/10	0.20GiB ≤ 1.20GiB
✅	file_to_blackhole_1000ms_latency	missed_bytes	10/10	0B = 0B
✅	file_to_blackhole_100ms_latency	memory_usage	10/10	0.17GiB ≤ 1.20GiB
✅	file_to_blackhole_100ms_latency	missed_bytes	10/10	0B = 0B
✅	file_to_blackhole_500ms_latency	memory_usage	10/10	0.18GiB ≤ 1.20GiB
✅	file_to_blackhole_500ms_latency	missed_bytes	10/10	0B = 0B
✅	quality_gate_idle	intake_connections	10/10	3 ≤ 4	bounds checks dashboard
✅	quality_gate_idle	memory_usage	10/10	138.60MiB ≤ 147MiB	bounds checks dashboard
✅	quality_gate_idle_all_features	intake_connections	10/10	3 ≤ 4	bounds checks dashboard
✅	quality_gate_idle_all_features	memory_usage	10/10	463.35MiB ≤ 495MiB	bounds checks dashboard
✅	quality_gate_logs	intake_connections	10/10	4 ≤ 6	bounds checks dashboard
✅	quality_gate_logs	memory_usage	10/10	171.83MiB ≤ 195MiB	bounds checks dashboard
✅	quality_gate_logs	missed_bytes	10/10	0B = 0B	bounds checks dashboard
✅	quality_gate_metrics_logs	cpu_usage	10/10	358.14 ≤ 2000	bounds checks dashboard
✅	quality_gate_metrics_logs	intake_connections	10/10	3 ≤ 6	bounds checks dashboard
✅	quality_gate_metrics_logs	memory_usage	10/10	406.43MiB ≤ 430MiB	bounds checks dashboard
✅	quality_gate_metrics_logs	missed_bytes	10/10	0B = 0B	bounds checks dashboard

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_metrics_logs, bounds check memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_metrics_logs, bounds check intake_connections: 10/10 replicas passed. Gate passed.
• quality_gate_metrics_logs, bounds check cpu_usage: 10/10 replicas passed. Gate passed.
• quality_gate_metrics_logs, bounds check missed_bytes: 10/10 replicas passed. Gate passed.
• quality_gate_idle_all_features, bounds check memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_idle_all_features, bounds check intake_connections: 10/10 replicas passed. Gate passed.
• quality_gate_logs, bounds check memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_logs, bounds check intake_connections: 10/10 replicas passed. Gate passed.
• quality_gate_logs, bounds check missed_bytes: 10/10 replicas passed. Gate passed.
• quality_gate_idle, bounds check intake_connections: 10/10 replicas passed. Gate passed.
• quality_gate_idle, bounds check memory_usage: 10/10 replicas passed. Gate passed.

[L3n41c]

Hi @lavigne958, I dug into CONTINT-4838 and I think bumping the timeout from 10s to 20s won't actually fix the flake. Sharing the analysis in case it's useful.

Telemetry on main (last 30 days)

• 7562 pass, 35 fail (~0.46%)
• avg/p95/p99/max(pass) = 581/636/649/840 ms
• avg(fail) = 10 086 ms (= the 10s timeout exactly)

The distribution is bimodal: the test either passes well under a second, or sits at exactly 10s. There is no "needed 12s but only got 10s" regime, so widening the wall clock just makes each CI failure cost 20s instead of 10s while the flake rate stays the same.

Root cause: race in the client-go fake client between the test's Create() and the reflector's WatchWithContext registration. If Create wins, tracker.add broadcasts the ADDED event to zero watchers and silently drops it. The lister has the object (it lives in tracker.objects), but no AddFunc ever fires — so hpaQueue stays empty, the worker never writes to hctrl.autoscalers, and the select waits the full timeout. All recent failures across Linux x64, Windows x64, macOS arm64 hit hpa_controller_test.go:346 (the first select), which matches.

The sister TestWPAController doesn't flake because it pre-loads the WPA into the fake client before inf.Start, so the reflector's initial List() surfaces it via a delta and AddFunc fires from there — independent of Watch registration timing.

Structural fix: #49900 mirrors that pattern for the HPA test. Verified with 500/500 passes under -race (~633ms each, where ~2-3 failures would be expected pre-fix). Also fixes a latent bug where a single time.NewTimer(10s) was reused across three select blocks — a time.Timer doesn't re-arm, so the second/third selects could pre-expire — and removes a autoscalersListerSynced = func() bool { return true } override that bypassed the cache-sync barrier.

If #49900 looks good, I'd suggest closing this one in favor of it. Happy to discuss if you see something I missed.

[L3n41c]

The timeout is already 12 times the maximum amount of time it takes for the test to pass when it is successful.