pkg/clusteragent/autoscaling/cluster/spot: fix the race between pod updates and workload opt-out#49880
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🎯 Code Coverage (details) 🔗 Commit SHA: 8b9fc49 | Docs | Datadog PR Page | Give us feedback! |
Files inventory check summaryFile checks results against ancestor e54068ce: Results for datadog-agent_7.80.0~devel.git.229.8b9fc49.pipeline.109832734-1_amd64.deb:No change detected |
Regression DetectorRegression Detector ResultsMetrics dashboard Baseline: faaf02e Optimization Goals: ✅ No significant changes detected
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| perf | experiment | goal | Δ mean % | Δ mean % CI | trials | links |
|---|---|---|---|---|---|---|
| ➖ | docker_containers_cpu | % cpu utilization | -0.29 | [-3.31, +2.73] | 1 | Logs |
Fine details of change detection per experiment
| perf | experiment | goal | Δ mean % | Δ mean % CI | trials | links |
|---|---|---|---|---|---|---|
| ➖ | ddot_metrics | memory utilization | +0.66 | [+0.47, +0.85] | 1 | Logs |
| ➖ | quality_gate_metrics_logs | memory utilization | +0.62 | [+0.35, +0.89] | 1 | Logs bounds checks dashboard |
| ➖ | otlp_ingest_metrics | memory utilization | +0.48 | [+0.32, +0.64] | 1 | Logs |
| ➖ | tcp_syslog_to_blackhole | ingress throughput | +0.45 | [+0.28, +0.63] | 1 | Logs |
| ➖ | otlp_ingest_logs | memory utilization | +0.37 | [+0.25, +0.48] | 1 | Logs |
| ➖ | ddot_metrics_sum_cumulativetodelta_exporter | memory utilization | +0.22 | [-0.01, +0.46] | 1 | Logs |
| ➖ | file_to_blackhole_0ms_latency | egress throughput | +0.08 | [-0.41, +0.57] | 1 | Logs |
| ➖ | file_to_blackhole_1000ms_latency | egress throughput | +0.02 | [-0.42, +0.45] | 1 | Logs |
| ➖ | file_to_blackhole_100ms_latency | egress throughput | +0.01 | [-0.09, +0.10] | 1 | Logs |
| ➖ | uds_dogstatsd_to_api | ingress throughput | +0.01 | [-0.19, +0.20] | 1 | Logs |
| ➖ | file_to_blackhole_500ms_latency | egress throughput | -0.00 | [-0.40, +0.40] | 1 | Logs |
| ➖ | tcp_dd_logs_filter_exclude | ingress throughput | -0.00 | [-0.11, +0.11] | 1 | Logs |
| ➖ | uds_dogstatsd_to_api_v3 | ingress throughput | -0.00 | [-0.21, +0.20] | 1 | Logs |
| ➖ | uds_dogstatsd_20mb_12k_contexts_20_senders | memory utilization | -0.01 | [-0.06, +0.04] | 1 | Logs |
| ➖ | docker_containers_memory | memory utilization | -0.04 | [-0.15, +0.06] | 1 | Logs |
| ➖ | file_tree | memory utilization | -0.06 | [-0.11, -0.02] | 1 | Logs |
| ➖ | quality_gate_idle_all_features | memory utilization | -0.11 | [-0.14, -0.07] | 1 | Logs bounds checks dashboard |
| ➖ | quality_gate_idle | memory utilization | -0.12 | [-0.16, -0.07] | 1 | Logs bounds checks dashboard |
| ➖ | ddot_metrics_sum_delta | memory utilization | -0.12 | [-0.31, +0.07] | 1 | Logs |
| ➖ | ddot_logs | memory utilization | -0.16 | [-0.23, -0.10] | 1 | Logs |
| ➖ | ddot_metrics_sum_cumulative | memory utilization | -0.28 | [-0.44, -0.12] | 1 | Logs |
| ➖ | docker_containers_cpu | % cpu utilization | -0.29 | [-3.31, +2.73] | 1 | Logs |
| ➖ | quality_gate_logs | % cpu utilization | -1.31 | [-2.92, +0.30] | 1 | Logs bounds checks dashboard |
Bounds Checks: ✅ Passed
| perf | experiment | bounds_check_name | replicates_passed | observed_value | links |
|---|---|---|---|---|---|
| ✅ | docker_containers_cpu | simple_check_run | 10/10 | 553 ≥ 26 | |
| ✅ | docker_containers_memory | memory_usage | 10/10 | 243.05MiB ≤ 370MiB | |
| ✅ | docker_containers_memory | simple_check_run | 10/10 | 718 ≥ 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 | 142.54MiB ≤ 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 | 467.95MiB ≤ 495MiB | bounds checks dashboard |
| ✅ | quality_gate_logs | intake_connections | 10/10 | 3 ≤ 6 | bounds checks dashboard |
| ✅ | quality_gate_logs | memory_usage | 10/10 | 175.96MiB ≤ 195MiB | bounds checks dashboard |
| ✅ | quality_gate_logs | missed_bytes | 10/10 | 0B = 0B | bounds checks dashboard |
| ✅ | quality_gate_metrics_logs | cpu_usage | 10/10 | 347.66 ≤ 2000 | bounds checks dashboard |
| ✅ | quality_gate_metrics_logs | intake_connections | 10/10 | 4 ≤ 6 | bounds checks dashboard |
| ✅ | quality_gate_metrics_logs | memory_usage | 10/10 | 404.51MiB ≤ 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:
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Its estimated |Δ mean %| ≥ 5.00%, indicating the change is big enough to merit a closer look.
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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.
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Its configuration does not mark it "erratic".
CI Pass/Fail Decision
✅ Passed. All Quality Gates passed.
- quality_gate_idle_all_features, bounds check intake_connections: 10/10 replicas passed. Gate passed.
- quality_gate_idle_all_features, bounds check memory_usage: 10/10 replicas passed. Gate passed.
- quality_gate_metrics_logs, bounds check missed_bytes: 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 memory_usage: 10/10 replicas passed. Gate passed.
- quality_gate_metrics_logs, bounds check cpu_usage: 10/10 replicas passed. Gate passed.
- quality_gate_logs, bounds check missed_bytes: 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_idle, bounds check memory_usage: 10/10 replicas passed. Gate passed.
- quality_gate_idle, bounds check intake_connections: 10/10 replicas passed. Gate passed.
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Static quality checks✅ Please find below the results from static quality gates 30 successful checks with minimal change (< 2 KiB)
On-wire sizes (compressed)
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…e race conditions
… before advancing fake clock Test scenarios use fake clock to speed-up on-demand fallback and rebalancing. The rebalancer skips an iteration when there are pending pods or in-flight admissions therefore update tests to step fake clock after workload updates have settled. Also refactor manual pod creation/deletion into fakeDeployment Reconcile and ScaleDown methods. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
…pdates and workload opt-out Refactor podTracker to use up-to-date spot config and untrack workload in case it is not spot eligible anymore (opted-out). Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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What does this PR do?
Refactor podTracker to use up-to-date spot config and untrack workload in case it is not spot eligible anymore (opted-out).
Motivation
This fixes the race between pod and workload updates where pod updates may arrive after workload was opted-out and silently recreate the pod set in the tracker.
Describe how you validated your changes
Reproduced the race in main via:
and verified it does not reproduce with the changes.
Additional Notes
To reproduce the race in tests delay WLM updates.
Test scenarios use fake clock to speed-up on-demand fallback and rebalancing. The rebalancer skips an iteration when there are pending pods or in-flight admissions therefore update tests to step fake clock after workload updates have settled.
Also refactor manual pod creation/deletion into fakeDeployment Reconcile and ScaleDown methods.
Updates https://datadoghq.atlassian.net/browse/CASCL-1274