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DataDog / saluki

An experimental toolkit for building telemetry data planes in Rust.
Apache License 2.0
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build(deps): bump libc from 0.2.155 to 0.2.158 #204

Closed dependabot[bot] closed 3 weeks ago

dependabot[bot] commented 3 weeks ago

Bumps libc from 0.2.155 to 0.2.158.

Release notes

Sourced from libc's releases.

0.2.158

Other

0.2.157

Added

Fixed

Changed

0.2.156

Added

Fixed

Changed

Removed

Other

  • Update or remove CI tests that have been failing
Changelog

Sourced from libc's changelog.

0.2.158 - 2024-08-19

Other

0.2.157 - 2024-08-17

Added

Fixed

Changed

0.2.156 - 2024-08-15

Added

Fixed

Changed

Removed

... (truncated)

Commits
  • c809c58 Merge pull request #3857 from rust-lang/release-plz-2024-08-19T05-21-04Z
  • 0d28de5 Update CHANGELOG.md
  • 284bd9e chore: release
  • 2682681 Merge pull request #3856 from tgross35/backport-wasi-fix
  • 71440ab [wasi] Add use core::iter::Iterator;
  • 6637dbe Merge pull request #3830 from rust-lang/release-plz-2024-08-15T20-50-10Z
  • 51d81e3 Update CHANGELOG.md
  • 217b2ab chore: release
  • 6d2b8a0 Merge pull request #3852 from tgross35/backport-onion
  • 64ee9df Merge pull request #3851 from tgross35/backport-romaine
  • Additional commits viewable in compare view


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pr-commenter[bot] commented 3 weeks ago

Regression Detector (DogStatsD)

Regression Detector Results

Run ID: dda01cb2-f7f1-49c2-a53c-7406bbaab16b

Baseline: 7.52.0 Comparison: 7.52.1

Performance changes are noted in the perf column of each table:

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 | links | |------|----------------------------------------------|--------------------|----------|----------------|-------| | ➖ | dsd_uds_100mb_3k_contexts_distributions_only | memory utilization | +0.05 | [-0.16, +0.25] | | | ➖ | dsd_uds_1mb_50k_contexts | ingress throughput | +0.03 | [-0.01, +0.08] | | | ➖ | dsd_uds_500mb_3k_contexts | ingress throughput | +0.00 | [-0.00, +0.01] | | | ➖ | dsd_uds_1mb_50k_contexts_memlimit | ingress throughput | +0.00 | [-0.04, +0.04] | | | ➖ | dsd_uds_100mb_250k_contexts | ingress throughput | +0.00 | [-0.00, +0.00] | | | ➖ | dsd_uds_100mb_3k_contexts | ingress throughput | -0.01 | [-0.03, +0.00] | | | ➖ | dsd_uds_10mb_3k_contexts | ingress throughput | -0.02 | [-0.07, +0.02] | | | ➖ | dsd_uds_1mb_3k_contexts | ingress throughput | -0.03 | [-0.11, +0.04] | | | ➖ | dsd_uds_512kb_3k_contexts | ingress throughput | -0.10 | [-0.19, -0.01] | |

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] commented 3 weeks ago

Regression Detector (Saluki)

Regression Detector Results

Run ID: c662250b-121f-4740-9568-84bd9601e540

Baseline: f0a8b4c7b06e49a9f97f4067cf2a94cabd1cfbed Comparison: bd08fcd15f8eef3c6736559f92e60044024a714e

Performance changes are noted in the perf column of each table:

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 | links | |------|-------------------------------------------------|--------------------|----------|----------------|-------| | ➖ | dsd_uds_100mb_3k_contexts_distributions_only | memory utilization | +0.46 | [+0.29, +0.62] | | | ➖ | dsd_uds_500mb_3k_contexts | ingress throughput | +0.34 | [+0.25, +0.43] | | | ➖ | dsd_uds_100mb_250k_contexts | ingress throughput | +0.14 | [-0.13, +0.42] | | | ➖ | dsd_uds_1mb_50k_contexts | ingress throughput | +0.02 | [-0.05, +0.08] | | | ➖ | dsd_uds_50mb_10k_contexts_no_inlining | ingress throughput | +0.00 | [-0.02, +0.02] | | | ➖ | dsd_uds_1mb_3k_contexts | ingress throughput | -0.00 | [-0.16, +0.16] | | | ➖ | dsd_uds_50mb_10k_contexts_no_inlining_no_allocs | ingress throughput | -0.01 | [-0.04, +0.03] | | | ➖ | dsd_uds_100mb_3k_contexts | ingress throughput | -0.01 | [-0.02, +0.01] | | | ➖ | dsd_uds_10mb_3k_contexts | ingress throughput | -0.02 | [-0.24, +0.21] | | | ➖ | dsd_uds_512kb_3k_contexts | ingress throughput | -0.03 | [-0.17, +0.10] | | | ➖ | dsd_uds_1mb_50k_contexts_memlimit | ingress throughput | -0.27 | [-3.57, +3.04] | |

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] commented 3 weeks ago

Regression Detector Links

Experiment Result Links

experiment link(s)
dsd_uds_100mb_250k_contexts [Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_100mb_3k_contexts [Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_100mb_3k_contexts_distributions_only [Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_10mb_3k_contexts [Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_1mb_3k_contexts [Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_1mb_50k_contexts [Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_1mb_50k_contexts_memlimit [Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_500mb_3k_contexts [Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_512kb_3k_contexts [Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_50mb_10k_contexts_no_inlining (ADP only) [Profiling (ADP)] [SMP Dashboard]
dsd_uds_50mb_10k_contexts_no_inlining_no_allocs (ADP only) [Profiling (ADP)] [SMP Dashboard]
dependabot[bot] commented 3 weeks ago

Looks like libc is up-to-date now, so this is no longer needed.