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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 1.0.207 to 1.0.208 #200

Closed dependabot[bot] closed 3 weeks ago

dependabot[bot] commented 3 weeks ago

Bumps serde from 1.0.207 to 1.0.208.

Release notes

Sourced from serde's releases.

v1.0.208

  • Support serializing and deserializing unit structs in a flatten field (#2802, thanks @​jonhoo)
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pr-commenter[bot] commented 3 weeks ago

Regression Detector (Saluki)

Regression Detector Results

Run ID: 389e5379-2a5e-41e9-9c50-18ffe0089c04

Baseline: f0a8b4c7b06e49a9f97f4067cf2a94cabd1cfbed Comparison: 118baabdff9998bcc7f7d11bee4b36eb33561e04

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_memlimit | ingress throughput | +1.33 | [-1.97, +4.62] | | | ➖ | dsd_uds_500mb_3k_contexts | ingress throughput | +0.70 | [+0.61, +0.79] | | | ➖ | dsd_uds_100mb_250k_contexts | ingress throughput | +0.09 | [-0.19, +0.37] | | | ➖ | dsd_uds_10mb_3k_contexts | ingress throughput | +0.07 | [-0.04, +0.18] | | | ➖ | dsd_uds_512kb_3k_contexts | ingress throughput | +0.05 | [-0.08, +0.18] | | | ➖ | dsd_uds_1mb_3k_contexts | ingress throughput | +0.01 | [-0.14, +0.16] | | | ➖ | dsd_uds_50mb_10k_contexts_no_inlining_no_allocs | ingress throughput | +0.00 | [-0.02, +0.02] | | | ➖ | dsd_uds_50mb_10k_contexts_no_inlining | ingress throughput | +0.00 | [-0.00, +0.00] | | | ➖ | dsd_uds_100mb_3k_contexts | ingress throughput | -0.00 | [-0.01, +0.01] | | | ➖ | dsd_uds_1mb_50k_contexts | ingress throughput | -0.01 | [-0.06, +0.04] | | | ➖ | dsd_uds_100mb_3k_contexts_distributions_only | memory utilization | -0.62 | [-0.76, -0.48] | |

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 (DogStatsD)

Regression Detector Results

Run ID: 0f5e03e3-1f11-484e-92f4-cf5ece410818

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 | +0.04 | [-0.17, +0.26] | | | ➖ | dsd_uds_1mb_50k_contexts | ingress throughput | +0.03 | [+0.00, +0.07] | | | ➖ | dsd_uds_10mb_3k_contexts | ingress throughput | +0.02 | [-0.01, +0.05] | | | ➖ | dsd_uds_512kb_3k_contexts | ingress throughput | +0.02 | [-0.05, +0.08] | | | ➖ | dsd_uds_100mb_250k_contexts | ingress throughput | +0.01 | [-0.06, +0.08] | | | ➖ | dsd_uds_100mb_3k_contexts | ingress throughput | +0.00 | [-0.01, +0.02] | | | ➖ | dsd_uds_500mb_3k_contexts | ingress throughput | +0.00 | [-0.00, +0.00] | | | ➖ | dsd_uds_1mb_3k_contexts | ingress throughput | -0.02 | [-0.08, +0.04] | | | ➖ | dsd_uds_1mb_50k_contexts_memlimit | ingress throughput | -0.02 | [-0.03, +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 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 serde is up-to-date now, so this is no longer needed.