Bump github.com/tinylib/msgp from 1.1.8 to 1.1.9

[dependabot[bot]]

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Bumps github.com/tinylib/msgp from 1.1.8 to 1.1.9.

Release notes

Sourced from github.com/tinylib/msgp's releases.

v1.1.9

What's Changed

• Support "allownil" for byte slices by @​klauspost in tinylib/msgp#328
• Added Read/WriteExtensionRaw by @​mhr3 in tinylib/msgp#329
• Optimize WriteExtensionRaw for stack buffers by @​mhr3 in tinylib/msgp#330
• Manage non-[]byte types when type-conversion needed from generated code by @​pilebones in tinylib/msgp#312
• chore: Upgrade dependencies + CI by @​klauspost in tinylib/msgp#335

New Contributors

• @​mhr3 made their first contribution in tinylib/msgp#329
• @​pilebones made their first contribution in tinylib/msgp#312

Full Changelog: https://github.com/tinylib/msgp/compare/v1.1.8...v1.1.9

Commits

• 778f982 chore: Upgrade dependencies + CI (#335)
• 4c45222 gen: fix decoding for non-[]byte types when type-conversion needed
• 6ac204f Turn benchmark into a proper test
• 05c997e Optimize WriteExtensionRaw for stack buffers
• 4e26c5d Add ReportAllocs into the benchmark
• abd1dc1 Added Read/WriteExtensionRaw
• 1627683 Support "allownil" for byte slices
• See full diff 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=30123109 --os-family=ubuntu

[pr-commenter[bot]]

Regression Detector

Regression Detector Results

Run ID: 305b5c4b-cecf-492b-b3b9-41cce441b072 Baseline: b2384042b144a5f880a4d22b22018895101eceea Comparison: 92f048ba635e88d2b4977ab516578228cacd0025

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	-0.59	[-6.90, +5.72]

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI
➖	pycheck_1000_100byte_tags	% cpu utilization	+2.18	[-2.79, +7.15]
➖	tcp_syslog_to_blackhole	ingress throughput	+1.65	[+1.57, +1.73]
➖	basic_py_check	% cpu utilization	+0.78	[-1.54, +3.10]
➖	file_tree	memory utilization	+0.73	[+0.63, +0.82]
➖	process_agent_standard_check_with_stats	memory utilization	+0.35	[+0.30, +0.39]
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	+0.24	[-2.66, +3.15]
➖	tcp_dd_logs_filter_exclude	ingress throughput	+0.02	[-0.01, +0.05]
➖	uds_dogstatsd_to_api	ingress throughput	+0.00	[-0.20, +0.20]
➖	trace_agent_json	ingress throughput	+0.00	[-0.02, +0.03]
➖	trace_agent_msgpack	ingress throughput	-0.02	[-0.02, -0.01]
➖	otel_to_otel_logs	ingress throughput	-0.10	[-0.56, +0.35]
➖	process_agent_standard_check	memory utilization	-0.31	[-0.37, -0.26]
➖	idle	memory utilization	-0.35	[-0.39, -0.31]
➖	process_agent_real_time_mode	memory utilization	-0.48	[-0.51, -0.44]
➖	file_to_blackhole	% cpu utilization	-0.59	[-6.90, +5.72]

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 recreate

[dependabot[bot]]

Looks like github.com/tinylib/msgp is up-to-date now, so this is no longer needed.