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DataDog / saluki

An experimental toolkit for building telemetry data planes in Rust.
Apache License 2.0
12 stars 2 forks source link

build(deps): bump serde from 1.0.208 to 1.0.209 #219

Closed dependabot[bot] closed 2 weeks ago

dependabot[bot] commented 2 weeks ago

Bumps serde from 1.0.208 to 1.0.209.

Release notes

Sourced from serde's releases.

v1.0.209

  • Fix deserialization of empty structs and empty tuples inside of untagged enums (#2805, thanks @​Mingun)
Commits
  • 30752ac Release 1.0.209
  • b84e6ca Improve wording of PR 2805 comments
  • 87a2fb0 Wrap comments from PR 2805 to 80 columns
  • 9eaf7b9 Merge pull request #2805 from Mingun/untagged-tests
  • 7bde100 Replace MapRefDeserializer with value::MapDeserializer
  • da7fc79 Fix deserialization of empty struct variant in untagged enums
  • 4c5fec1 Test special cases that reaches SeqRefDeserializer::deserialize_any len==0 co...
  • 6588b0a Cover Content::Seq case in VariantRefDeserializer::struct_variant
  • 0093f74 Split test newtype_enum into four tests for each variant
  • 171c6da Complete coverage of ContentRefDeserializer::deserialize_newtype_struct
  • Additional commits viewable in compare view


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pr-commenter[bot] commented 2 weeks ago

Regression Detector (DogStatsD)

Regression Detector Results

Run ID: 21308e31-a3d4-4b83-9638-148085075505

Baseline: 7.55.2 Comparison: 7.55.3

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_1mb_50k_contexts | ingress throughput | +0.02 | [-0.01, +0.04] | | | ➖ | dsd_uds_1mb_50k_contexts_memlimit | ingress throughput | +0.02 | [-0.00, +0.04] | | | ➖ | dsd_uds_10mb_3k_contexts | ingress throughput | +0.02 | [-0.02, +0.06] | | | ➖ | dsd_uds_100mb_250k_contexts | ingress throughput | +0.01 | [-0.05, +0.07] | | | ➖ | dsd_uds_500mb_3k_contexts | ingress throughput | +0.00 | [-0.00, +0.00] | | | ➖ | dsd_uds_1mb_3k_contexts | ingress throughput | -0.00 | [-0.05, +0.04] | | | ➖ | dsd_uds_100mb_3k_contexts | ingress throughput | -0.00 | [-0.02, +0.01] | | | ➖ | dsd_uds_512kb_3k_contexts | ingress throughput | -0.02 | [-0.08, +0.04] | | | ➖ | dsd_uds_100mb_3k_contexts_distributions_only | memory utilization | -2.05 | [-2.27, -1.82] | |

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 2 weeks ago

Regression Detector (Saluki)

Regression Detector Results

Run ID: 34f79161-0a7e-45d7-89d0-966aa16c1ebc

Baseline: a5bdd380459d9ed3dd97c4fef6b53e9cb40e1ba8 Comparison: fb11d16be899cad27ec8e35f6cc975e441f46949

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 | +2.68 | [+2.51, +2.84] | | | ➖ | dsd_uds_1mb_50k_contexts_memlimit | ingress throughput | +1.09 | [-2.20, +4.38] | | | ➖ | dsd_uds_500mb_3k_contexts | ingress throughput | +1.02 | [+0.93, +1.11] | | | ➖ | dsd_uds_100mb_250k_contexts | ingress throughput | +0.17 | [-0.11, +0.44] | | | ➖ | dsd_uds_512kb_3k_contexts | ingress throughput | +0.02 | [-0.05, +0.08] | | | ➖ | dsd_uds_1mb_50k_contexts | ingress throughput | +0.02 | [-0.00, +0.04] | | | ➖ | dsd_uds_50mb_10k_contexts_no_inlining_no_allocs | ingress throughput | +0.01 | [-0.04, +0.05] | | | ➖ | dsd_uds_100mb_3k_contexts | ingress throughput | +0.00 | [-0.00, +0.01] | | | ➖ | dsd_uds_50mb_10k_contexts_no_inlining | ingress throughput | +0.00 | [-0.00, +0.00] | | | ➖ | dsd_uds_1mb_3k_contexts | ingress throughput | -0.02 | [-0.05, +0.02] | | | ➖ | dsd_uds_10mb_3k_contexts | ingress throughput | -0.05 | [-0.11, -0.00] | |

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 2 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 2 weeks ago

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