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Bump github.com/cri-o/ocicni from 0.4.0 to 0.4.1

Open dependabot[bot] opened this issue 1 year ago • 2 comments
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Bumps github.com/cri-o/ocicni from 0.4.0 to 0.4.1.

Release notes

Sourced from github.com/cri-o/ocicni's releases.

v0.4.1

What's Changed

New Contributors

Full Changelog: https://github.com/cri-o/ocicni/compare/v0.4.0...v0.4.1

Commits
  • 00ce879 Merge pull request #172 from cri-o/dependabot/go_modules/golang.org/x/net-0.17.0
  • 191f911 build(deps): bump golang.org/x/net from 0.14.0 to 0.17.0
  • 7c84931 Merge pull request #171 from cri-o/dependabot/go_modules/github.com/onsi/gink...
  • bc11739 build(deps): bump github.com/onsi/ginkgo/v2 from 2.12.1 to 2.13.0
  • 4e37d50 Merge pull request #170 from cri-o/dependabot/go_modules/github.com/onsi/gome...
  • a915a71 build(deps): bump github.com/onsi/gomega from 1.27.10 to 1.28.0
  • bbe988a Merge pull request #169 from cri-o/dependabot/go_modules/github.com/onsi/gink...
  • 4ff5a3a build(deps): bump github.com/onsi/ginkgo/v2 from 2.12.0 to 2.12.1
  • ccf337d Merge pull request #135 from dfr/freebsd
  • a8b0309 Merge pull request #168 from cri-o/dependabot/go_modules/github.com/onsi/gink...
  • Additional commits viewable in compare view

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dependabot[bot] avatar Mar 13 '24 18:03 dependabot[bot]

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=30049980 --os-family=ubuntu

pr-commenter[bot] avatar Mar 13 '24 19:03 pr-commenter[bot]

Regression Detector

Regression Detector Results

Run ID: e3ec1729-0dfa-481c-b094-6ca88c3f174c Baseline: 30f826b9b34caecaa3995e5f0fdcfc28c7e4dadd Comparison: 28f2d524c44a7304b75c1b4f4e1724f07a5af6f0

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 +15.40 [+8.11, +22.69]

Fine details of change detection per experiment

perf experiment goal Δ mean % Δ mean % CI
file_to_blackhole % cpu utilization +15.40 [+8.11, +22.69]
file_tree memory utilization +1.19 [+1.08, +1.30]
pycheck_1000_100byte_tags % cpu utilization +1.13 [-4.09, +6.35]
tcp_syslog_to_blackhole ingress throughput +0.93 [+0.82, +1.05]
process_agent_real_time_mode memory utilization +0.68 [+0.63, +0.72]
process_agent_standard_check_with_stats memory utilization +0.54 [+0.50, +0.58]
process_agent_standard_check memory utilization +0.14 [+0.10, +0.18]
otel_to_otel_logs ingress throughput +0.12 [-0.30, +0.54]
trace_agent_msgpack ingress throughput +0.02 [+0.01, +0.03]
trace_agent_json ingress throughput +0.01 [-0.02, +0.04]
tcp_dd_logs_filter_exclude ingress throughput +0.00 [+0.00, +0.01]
uds_dogstatsd_to_api ingress throughput -0.00 [-0.20, +0.20]
uds_dogstatsd_to_api_cpu % cpu utilization -0.35 [-3.20, +2.50]
idle memory utilization -0.40 [-0.44, -0.36]
basic_py_check % cpu utilization -1.32 [-3.62, +0.97]

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".

pr-commenter[bot] avatar Mar 13 '24 19:03 pr-commenter[bot]

Superseded by #23854.

dependabot[bot] avatar Mar 18 '24 21:03 dependabot[bot]