Bump github.com/vmihailenco/msgpack/v5 from 5.3.5 to 5.4.1

[dependabot[bot]]

trafficstars

Bumps github.com/vmihailenco/msgpack/v5 from 5.3.5 to 5.4.1.

Release notes

Sourced from github.com/vmihailenco/msgpack/v5's releases.

v5.4.1

Please refer to CHANGELOG.md for details

v5.4.0

Please refer to CHANGELOG.md for details

v5.3.6

Please refer to CHANGELOG.md for details

Changelog

Sourced from github.com/vmihailenco/msgpack/v5's changelog.

5.4.1 (2023-10-26)

Bug Fixes

• reflect: not assignable to type (edeaedd)

5.4.0 (2023-10-01)

5.3.6 (2023-10-01)

Features

• allow overwriting time.Time parsing from extID 13 (for NodeJS Date) (9a6b73b)
• apply omitEmptyFlag to empty structs (e5f8d03)
• support sorted keys for map[string]bool (690c1fa)

Commits

• 19c91df Merge pull request #360 from vmihailenco/release/v5.4.1
• 781a0da chore: release v5.4.1 (release.sh)
• e5d47a2 chore: cleanup
• 6eedee3 Merge pull request #359 from choyri/bugfix/reflect-set
• edeaedd fix(reflect): not assignable to type
• 3f7bd80 Merge pull request #357 from Jille/tests-fix
• 1f7263d msgpack_test: Actually run the test suite
• ecf8fa7 Merge pull request #356 from vmihailenco/release/v5.4.0
• 1b6c01f chore: release v5.4.0 (release.sh)
• a9ef130 chore: update Go
• Additional commits viewable in compare view

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[pr-commenter[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=30049906 --os-family=ubuntu

[pr-commenter[bot]]

Regression Detector

Regression Detector Results

Run ID: 231749be-195e-4c0f-8aa8-b4544195cbe4 Baseline: 30f826b9b34caecaa3995e5f0fdcfc28c7e4dadd Comparison: 1be22786f1970a9cc87836432b1c70adf9483f22

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	+0.29	[-6.26, +6.85]

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	+1.38	[-1.50, +4.26]
➖	pycheck_1000_100byte_tags	% cpu utilization	+1.34	[-3.92, +6.61]
➖	file_to_blackhole	% cpu utilization	+0.29	[-6.26, +6.85]
➖	process_agent_standard_check	memory utilization	+0.16	[+0.12, +0.20]
➖	file_tree	memory utilization	+0.13	[+0.06, +0.19]
➖	tcp_syslog_to_blackhole	ingress throughput	+0.07	[-0.03, +0.16]
➖	process_agent_standard_check_with_stats	memory utilization	+0.04	[+0.00, +0.08]
➖	trace_agent_json	ingress throughput	+0.02	[+0.00, +0.04]
➖	tcp_dd_logs_filter_exclude	ingress throughput	+0.00	[-0.00, +0.00]
➖	uds_dogstatsd_to_api	ingress throughput	-0.00	[-0.20, +0.20]
➖	trace_agent_msgpack	ingress throughput	-0.01	[-0.03, -0.00]
➖	otel_to_otel_logs	ingress throughput	-0.19	[-0.63, +0.24]
➖	idle	memory utilization	-0.35	[-0.39, -0.31]
➖	process_agent_real_time_mode	memory utilization	-0.47	[-0.51, -0.43]
➖	basic_py_check	% cpu utilization	-2.52	[-4.81, -0.22]

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".

[paulcacheux]

@dependabot rebase

[paulcacheux]

/merge

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