chore(deps): Bump quote from 1.0.35 to 1.0.36

[dependabot]

Bumps quote from 1.0.35 to 1.0.36.

Release notes

Sourced from quote's releases.

1.0.36

• Documentation improvements

Commits

• 5d4880c Release 1.0.36
• 1dd7ce7 Merge pull request #273 from dtolnay/doc
• 0bc5d12 Apply doc comment to cfg(not(doc)) macros too
• c295f5c Revert "Temporarily disable miri on doctests"
• 435bd1b Update ui test suite to nightly-2024-03-31
• cc3847d Explicitly install a Rust toolchain for cargo-outdated job
• 6259d49 Temporarily disable miri on doctests
• bdb4b59 Update ui test suite to nightly-2024-02-08
• c2aeca9 Update ui test suite to nightly-2024-01-31
• 376a061 Merge pull request #270 from dtolnay/bench
• Additional commits viewable in compare view

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[github-actions]

Regression Detector Results

Run ID: b2c418d5-a9c4-4332-a5cb-5ee56f0c8471
Baseline: 177cd0e
Comparison: eaacd2f
Total CPUs: 7

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.

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI
➖	socket_to_socket_blackhole	ingress throughput	+2.47	[+2.37, +2.56]
➖	syslog_humio_logs	ingress throughput	+1.74	[+1.62, +1.87]
➖	http_to_http_acks	ingress throughput	+1.68	[+0.30, +3.05]
➖	datadog_agent_remap_blackhole	ingress throughput	+1.67	[+1.57, +1.77]
➖	otlp_http_to_blackhole	ingress throughput	+1.63	[+1.48, +1.77]
➖	syslog_regex_logs2metric_ddmetrics	ingress throughput	+1.50	[+1.29, +1.70]
➖	syslog_splunk_hec_logs	ingress throughput	+1.34	[+1.25, +1.43]
➖	splunk_hec_route_s3	ingress throughput	+1.15	[+0.68, +1.63]
➖	syslog_loki	ingress throughput	+0.78	[+0.70, +0.86]
➖	syslog_log2metric_tag_cardinality_limit_blackhole	ingress throughput	+0.48	[+0.34, +0.62]
➖	fluent_elasticsearch	ingress throughput	+0.46	[-0.02, +0.93]
➖	http_elasticsearch	ingress throughput	+0.34	[+0.26, +0.41]
➖	http_to_http_noack	ingress throughput	+0.20	[+0.10, +0.30]
➖	http_to_http_json	ingress throughput	+0.04	[-0.03, +0.12]
➖	http_to_s3	ingress throughput	+0.02	[-0.26, +0.30]
➖	splunk_hec_indexer_ack_blackhole	ingress throughput	+0.00	[-0.14, +0.15]
➖	splunk_hec_to_splunk_hec_logs_acks	ingress throughput	-0.01	[-0.15, +0.14]
➖	enterprise_http_to_http	ingress throughput	-0.05	[-0.14, +0.04]
➖	splunk_hec_to_splunk_hec_logs_noack	ingress throughput	-0.05	[-0.16, +0.06]
➖	datadog_agent_remap_datadog_logs_acks	ingress throughput	-0.10	[-0.19, -0.01]
➖	http_text_to_http_json	ingress throughput	-0.51	[-0.64, -0.38]
➖	syslog_log2metric_humio_metrics	ingress throughput	-0.51	[-0.62, -0.40]
➖	file_to_blackhole	egress throughput	-0.54	[-3.09, +2.01]
➖	datadog_agent_remap_blackhole_acks	ingress throughput	-0.54	[-0.65, -0.43]
➖	datadog_agent_remap_datadog_logs	ingress throughput	-0.59	[-0.70, -0.48]
➖	otlp_grpc_to_blackhole	ingress throughput	-0.61	[-0.69, -0.52]
➖	syslog_log2metric_splunk_hec_metrics	ingress throughput	-0.91	[-1.10, -0.72]

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".