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chore(deps): Bump serde from 1.0.186 to 1.0.187 #18392

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@dependabot dependabot bot commented on behalf of github Aug 25, 2023

Bumps serde from 1.0.186 to 1.0.187.

Release notes

Sourced from serde's releases.

v1.0.187

  • Remove support for Emscripten targets on rustc older than 1.40 (#2600)
Commits
  • 146dc0f Release 1.0.187
  • d26852d Merge pull request #2602 from dtolnay/resolver
  • e1c2724 Adopt new Cargo feature resolver
  • dbbfe7a Merge pull request #2600 from dtolnay/oldemscripten
  • dc24d12 Clean up all usage of serde_if_integer128
  • 4e7533e Remove support for emscripten targets on rustc older than 1.40
  • See full diff in compare view

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Bumps [serde](https://github.com/serde-rs/serde) from 1.0.186 to 1.0.187.
- [Release notes](https://github.com/serde-rs/serde/releases)
- [Commits](serde-rs/serde@v1.0.186...v1.0.187)

---
updated-dependencies:
- dependency-name: serde
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <[email protected]>
@dependabot dependabot bot requested a review from a team August 25, 2023 23:06
@dependabot dependabot bot added the domain: deps Anything related to Vector's dependencies label Aug 25, 2023
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@github-actions github-actions bot added the domain: core Anything related to core crates i.e. vector-core, core-common, etc label Aug 25, 2023
@jszwedko jszwedko enabled auto-merge August 25, 2023 23:10
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Superseded by #18395.

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@dependabot dependabot bot deleted the dependabot/cargo/serde-1.0.187 branch August 26, 2023 03:07
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Regression Detector Results

Run ID: cef4c732-7f39-4691-a86e-0928cad0ffb5
Baseline: 725b9bd
Comparison: 2bf02e9
Total vector CPUs: 7

Explanation

A regression test is an integrated performance test for vector in a repeatable rig, with varying configuration for vector. What follows is a statistical summary of a brief vector run for each configuration across SHAs given above. The goal of these tests are to determine quickly if vector performance is changed and to what degree by a pull request.

Because a target's optimization goal performance in each experiment will vary somewhat each time it is run, we can only estimate mean differences in optimization goal relative to the baseline target. We express these differences as a percentage change relative to the baseline target, denoted "Δ mean %". These estimates are made to a precision that balances accuracy and cost control. We represent this precision as a 90.00% confidence interval denoted "Δ mean % CI": there is a 90.00% chance that the true value of "Δ mean %" is in that interval.

We decide whether a change in performance is a "regression" -- a change worth investigating further -- if both of the following two criteria are true:

  1. The estimated |Δ mean %| ≥ 5.00%. This criterion intends to answer the question "Does the estimated change in mean optimization goal performance have a meaningful impact on your customers?". We assume that when |Δ mean %| < 5.00%, the impact on your customers is not meaningful. We also assume that a performance change in optimization goal is worth investigating whether it is an increase or decrease, so long as the magnitude of the change is sufficiently large.

  2. Zero is not in the 90.00% confidence interval "Δ mean % CI" about "Δ mean %". This statement is equivalent to saying that there is at least a 90.00% chance that the mean difference in optimization goal is not zero. This criterion intends to answer the question, "Is there a statistically significant difference in mean optimization goal performance?". It also means there is no more than a 10.00% chance this criterion reports a statistically significant difference when the true difference in mean optimization goal is zero -- a "false positive". We assume you are willing to accept a 10.00% chance of inaccurately detecting a change in performance when no true difference exists.

The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values of "Δ mean %" mean that baseline is faster, whereas positive values of "Δ mean %" mean that comparison is faster. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed.

No interesting changes in experiment optimization goals with confidence ≥ 90.00% and |Δ mean %| ≥ 5.00%.

Fine details of change detection per experiment.
experiment goal Δ mean % Δ mean % CI confidence
syslog_regex_logs2metric_ddmetrics ingress throughput +4.08 [+3.80, +4.36] 100.00%
socket_to_socket_blackhole ingress throughput +2.27 [+2.24, +2.31] 100.00%
otlp_http_to_blackhole ingress throughput +1.72 [+1.54, +1.91] 100.00%
http_to_http_noack ingress throughput +1.61 [+1.48, +1.73] 100.00%
splunk_hec_route_s3 ingress throughput +1.45 [+1.01, +1.89] 100.00%
syslog_log2metric_humio_metrics ingress throughput +0.57 [+0.46, +0.67] 100.00%
http_to_s3 ingress throughput +0.47 [+0.26, +0.68] 99.60%
fluent_elasticsearch ingress throughput +0.29 [+0.06, +0.53] 88.87%
file_to_blackhole egress throughput +0.28 [-0.57, +1.13] 33.14%
splunk_hec_indexer_ack_blackhole ingress throughput +0.01 [-0.12, +0.14] 8.50%
http_to_http_json ingress throughput -0.00 [-0.04, +0.04] 2.29%
splunk_hec_to_splunk_hec_logs_noack ingress throughput -0.01 [-0.11, +0.10] 5.13%
splunk_hec_to_splunk_hec_logs_acks ingress throughput -0.01 [-0.12, +0.10] 9.24%
http_to_http_acks ingress throughput -0.18 [-0.31, -0.05] 92.06%
datadog_agent_remap_blackhole ingress throughput -0.27 [-0.34, -0.20] 100.00%
otlp_grpc_to_blackhole ingress throughput -0.65 [-0.72, -0.58] 100.00%
http_text_to_http_json ingress throughput -0.66 [-0.75, -0.57] 100.00%
datadog_agent_remap_blackhole_acks ingress throughput -0.71 [-0.79, -0.63] 100.00%
enterprise_http_to_http ingress throughput -0.75 [-0.88, -0.61] 100.00%
syslog_splunk_hec_logs ingress throughput -1.37 [-1.44, -1.30] 100.00%
syslog_log2metric_splunk_hec_metrics ingress throughput -1.46 [-1.58, -1.34] 100.00%
syslog_loki ingress throughput -1.49 [-1.54, -1.45] 100.00%
datadog_agent_remap_datadog_logs_acks ingress throughput -2.41 [-2.51, -2.31] 100.00%
syslog_humio_logs ingress throughput -2.64 [-2.73, -2.54] 100.00%
datadog_agent_remap_datadog_logs ingress throughput -2.67 [-2.80, -2.54] 100.00%

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