8000 Bump k8s.io/cri-api from 0.31.2 to 0.33.1 by dependabot[bot] · Pull Request #37784 · DataDog/datadog-agent · GitHub
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Bump k8s.io/cri-api from 0.31.2 to 0.33.1 #37784

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Bump k8s.io/cri-api from 0.31.2 to 0.33.1 #37784

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Bumps k8s.io/cri-api from 0.31.2 to 0.33.1.

Commits
  • 15d0889 bump etcd 3.5.21 sdk
  • 87ee4e1 Merge pull request #130556 from sreeram-venkitesh/kep-4960-container-stop-sig...
  • 8c42f50 Generated files
  • ea06df2 CRI API changes
  • 74299ef Merge pull request #130701 from roycaihw/psi-metrics
  • f27583b generated
  • 26564a8 Extend CRI API to support PSI
  • 1b6a6cd Merge pull request #130250 from marosset/withdraw-windows-hostnetwork
  • 475a741 update cri-api comments for Windows HostProcess withdrawal
  • 0df2b7e Merge pull request #128123 from felipeagger/feat/add-updatepodsandbox-cri-method
  • Additional commits viewable in compare view

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@dependabot dependabot bot added changelog/no-changelog dependencies PRs that bump a dependency dependencies-go PRs that bump a go dependency team/triage labels Jun 9, 2025
@github-actions github-actions bot added the short review PR is simple enough to be reviewed quickly label Jun 9, 2025
@dependabot
Bump k8s.io/cri-api from 0.31.2 to 0.33.1
1ff5467 
Bumps [k8s.io/cri-api](https://github.com/kubernetes/cri-api) from 0.31.2 to 0.33.1.
- [Commits](kubernetes/cri-api@v0.31.2...v0.33.1)

---
updated-dependencies:
- dependency-name: k8s.io/cri-api
  dependency-version: 0.33.1
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <support@github.com>
@dependabot dependabot bot force-pushed the dependabot/go_modules/k8s.io/cri-api-0.33.1 branch from 20c5b73 to 1ff5467 Compare June 17, 2025 15:53
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Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: 2e692591-5234-47c8-bb9c-716049341814

Baseline: 1680c19
Comparison: 1ff5467
Diff

Optimization Goals: ✅ No significant changes detected

Fine details of change detection per experiment

perf experiment goal Δ mean % Δ mean % CI trials links
➖ tcp_syslog_to_blackhole ingress throughput +1.28 [+1.23, +1.34] 1 Logs
➖ quality_gate_logs % cpu utilization +1.15 [-1.63, +3.93] 1 Logs bounds checks dashboard
➖ quality_gate_idle_all_features memory utilization +0.66 [+0.58, +0.74] 1 Logs bounds checks dashboard
➖ quality_gate_idle memory utilization +0.51 [+0.45, +0.57] 1 Logs bounds checks dashboard
➖ file_tree memory utilization +0.36 [+0.22, +0.51] 1 Logs
➖ uds_dogstatsd_to_api_cpu % cpu utilization +0.26 [-0.59, +1.11] 1 Logs
➖ ddot_logs memory utilization +0.26 [+0.14, +0.38] 1 Logs
➖ otlp_ingest_logs memory utilization +0.09 [-0.04, +0.22] 1 Logs
➖ file_to_blackhole_1000ms_latency egress throughput +0.09 [-0.53, +0.70] 1 Logs
➖ uds_dogstatsd_to_api ingress throughput +0.01 [-0.26, +0.28] 1 Logs
➖ tcp_dd_logs_filter_exclude ingress throughput +0.00 [-0.02, +0.03] 1 Logs
➖ file_to_blackhole_1000ms_latency_linear_load egress throughput -0.04 [-0.27, +0.20] 1 Logs
➖ file_to_blackhole_0ms_latency_http2 egress throughput -0.07 [-0.66, +0.52] 1 Logs
➖ file_to_blackhole_300ms_latency egress throughput -0.07 [-0.68, +0.54] 1 Logs
➖ file_to_blackhole_500ms_latency egress throughput -0.08 [-0.74, +0.58] 1 Logs
➖ file_to_blackhole_0ms_latency_http1 egress throughput -0.09 [-0.64, +0.47] 1 Logs
➖ file_to_blackhole_0ms_latency egress throughput -0.09 [-0.71, +0.53] 1 Logs
➖ docker_containers_memory memory utilization -0.09 [-0.17, -0.02] 1 Logs
➖ file_to_blackhole_100ms_latency egress throughput -0.14 [-0.76, +0.48] 1 Logs
➖ otlp_ingest_metrics memory utilization -0.16 [-0.32, -0.00] 1 Logs
➖ ddot_metrics memory utilization -0.30 [-0.42, -0.18] 1 Logs
➖ uds_dogstatsd_20mb_12k_contexts_20_senders memory utilization -0.34 [-0.39, -0.29] 1 Logs
➖ docker_containers_cpu % cpu utilization -3.44 [-6.45, -0.43] 1 Logs

Bounds Checks: ✅ Passed

perf experiment bounds_check_name replicates_passed links
✅ docker_containers_cpu simple_check_run 10/10
✅ docker_containers_memory memory_usage 10/10
✅ docker_containers_memory simple_check_run 10/10
✅ file_to_blackhole_0ms_latency lost_bytes 10/10
✅ 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 lost_bytes 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 intake_connections 10/10 bounds checks dashboard
✅ quality_gate_idle memory_usage 10/10 bounds checks dashboard
✅ quality_gate_idle_all_features intake_connections 10/10 bounds checks dashboard
✅ quality_gate_idle_all_features memory_usage 10/10 bounds checks dashboard
✅ quality_gate_logs intake_connections 10/10 bounds checks dashboard
✅ quality_gate_logs lost_bytes 10/10 bounds checks dashboard
✅ quality_gate_logs memory_usage 10/10 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_idle, 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_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 lost_bytes: 10/10 replicas passed. Gate 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.

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