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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 serde_json from 1.0.125 to 1.0.127 #220

Closed dependabot[bot] closed 2 weeks ago

dependabot[bot] commented 2 weeks ago

Bumps serde_json from 1.0.125 to 1.0.127.

Release notes

Sourced from serde_json's releases.

1.0.127

1.0.126

  • Improve string parsing on targets that use 32-bit pointers but also have fast 64-bit integer arithmetic, such as aarch64-unknown-linux-gnu_ilp32 and x86_64-unknown-linux-gnux32 (#1182, thanks @​CryZe)
Commits
  • 5ebf65c Release 1.0.127
  • f287a3b Merge pull request 1179 from GREsau/patch-1
  • ec980b0 Release 1.0.126
  • e6282b0 Merge pull request #1184 from serde-rs/fastarithmetic
  • ffc4a43 Improve cfg names for fast arithmetic
  • 4b1048d Merge pull request #1183 from serde-rs/arithmetic
  • f268173 Unify chunk size choice between float and string parsing
  • fec0376 Merge pull request #1182 from CryZe/chunk-64bit
  • 3d837e1 Ensure the SWAR chunks are 64-bit in more cases
  • 11fc61c Add OccupiedEntry::shift_remove() and swap_remove()
  • 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: 1fca7a99-ae0e-44a2-af07-a0bf88820def

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_100mb_3k_contexts_distributions_only | memory utilization | +1.25 | [+1.03, +1.47] | | | ➖ | dsd_uds_512kb_3k_contexts | ingress throughput | +0.04 | [-0.03, +0.11] | | | ➖ | dsd_uds_10mb_3k_contexts | ingress throughput | +0.02 | [-0.00, +0.05] | | | ➖ | dsd_uds_1mb_3k_contexts | ingress throughput | +0.02 | [-0.02, +0.06] | | | ➖ | dsd_uds_100mb_250k_contexts | ingress throughput | +0.01 | [-0.03, +0.05] | | | ➖ | dsd_uds_1mb_50k_contexts_memlimit | ingress throughput | +0.00 | [-0.00, +0.00] | | | ➖ | dsd_uds_500mb_3k_contexts | ingress throughput | +0.00 | [-0.00, +0.00] | | | ➖ | dsd_uds_1mb_50k_contexts | ingress throughput | -0.00 | [-0.05, +0.05] | | | ➖ | dsd_uds_100mb_3k_contexts | ingress throughput | -0.00 | [-0.02, +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 2 weeks ago

Regression Detector (Saluki)

Regression Detector Results

Run ID: a8ea6d9d-6652-4b04-9726-48a2f328c74e

Baseline: a5bdd380459d9ed3dd97c4fef6b53e9cb40e1ba8 Comparison: 7f40fcd4ed626a868e867267d585ad5a15b3bf32

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 | +4.44 | [+4.30, +4.58] | | | ➖ | dsd_uds_1mb_50k_contexts_memlimit | ingress throughput | +0.69 | [-2.60, +3.98] | | | ➖ | dsd_uds_10mb_3k_contexts | ingress throughput | +0.05 | [-0.01, +0.11] | | | ➖ | dsd_uds_1mb_3k_contexts | ingress throughput | +0.04 | [-0.01, +0.08] | | | ➖ | dsd_uds_100mb_250k_contexts | ingress throughput | +0.02 | [-0.25, +0.28] | | | ➖ | dsd_uds_100mb_3k_contexts | ingress throughput | +0.00 | [-0.00, +0.00] | | | ➖ | dsd_uds_1mb_50k_contexts | ingress throughput | +0.00 | [-0.00, +0.00] | | | ➖ | dsd_uds_50mb_10k_contexts_no_inlining | ingress throughput | -0.00 | [-0.00, +0.00] | | | ➖ | dsd_uds_50mb_10k_contexts_no_inlining_no_allocs | ingress throughput | -0.01 | [-0.05, +0.03] | | | ➖ | dsd_uds_512kb_3k_contexts | ingress throughput | -0.07 | [-0.12, -0.01] | | | ➖ | dsd_uds_500mb_3k_contexts | ingress throughput | -0.78 | [-0.88, -0.69] | |

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_json is up-to-date now, so this is no longer needed.