[APR-248] chore: bundle licenses of dependencies into ADP container image #313
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Regression Detector (DogStatsD)Regression Detector ResultsRun ID: 7f45744c-4af6-4638-99b4-eab55620bc71 Baseline: 7.58.0 Optimization Goals: ✅ No significant changes detected
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| perf | experiment | goal | Δ mean % | Δ mean % CI | trials | links |
|---|---|---|---|---|---|---|
| ➖ | dsd_uds_100mb_3k_contexts_distributions_only | memory utilization | +2.20 | [+2.03, +2.37] | 1 | |
| ➖ | dsd_uds_100mb_250k_contexts | ingress throughput | -0.00 | [-0.00, +0.00] | 1 | |
| ➖ | dsd_uds_1mb_3k_contexts | ingress throughput | -0.00 | [-0.00, +0.00] | 1 | |
| ➖ | dsd_uds_512kb_3k_contexts | ingress throughput | -0.00 | [-0.01, +0.01] | 1 | |
| ➖ | dsd_uds_1mb_50k_contexts_memlimit | ingress throughput | -0.00 | [-0.00, +0.00] | 1 | |
| ➖ | dsd_uds_10mb_3k_contexts | ingress throughput | -0.00 | [-0.02, +0.02] | 1 | |
| ➖ | dsd_uds_100mb_3k_contexts | ingress throughput | -0.00 | [-0.04, +0.04] | 1 | |
| ➖ | dsd_uds_500mb_3k_contexts | ingress throughput | -0.00 | [-0.01, +0.01] | 1 | |
| ➖ | dsd_uds_1mb_50k_contexts | ingress throughput | -0.00 | [-0.01, +0.00] | 1 |
Explanation
Confidence level: 90.00%
Effect size tolerance: |Δ mean %| ≥ 5.00%
Performance changes are noted in the perf column of each table:
- ✅ = significantly better comparison variant performance
- ❌ = significantly worse comparison variant performance
- ➖ = no significant change in performance
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:
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Its estimated |Δ mean %| ≥ 5.00%, indicating the change is big enough to merit a closer look.
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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.
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Its configuration does not mark it "erratic".
Regression Detector (Saluki)Regression Detector ResultsRun ID: 48a812a8-d2d4-4dfe-a36a-29f77d897db2 Baseline: ecd7a30 Optimization Goals: ✅ No significant changes detected
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| perf | experiment | goal | Δ mean % | Δ mean % CI | trials | links |
|---|---|---|---|---|---|---|
| ➖ | dsd_uds_100mb_3k_contexts_distributions_only | memory utilization | +2.84 | [+2.69, +2.98] | 1 | |
| ➖ | dsd_uds_10mb_3k_contexts | ingress throughput | +0.02 | [-0.01, +0.05] | 1 | |
| ➖ | dsd_uds_512kb_3k_contexts | ingress throughput | +0.01 | [-0.03, +0.04] | 1 | |
| ➖ | dsd_uds_100mb_3k_contexts | ingress throughput | +0.01 | [-0.01, +0.02] | 1 | |
| ➖ | dsd_uds_1mb_3k_contexts | ingress throughput | +0.01 | [-0.01, +0.02] | 1 | |
| ➖ | dsd_uds_50mb_10k_contexts_no_inlining | ingress throughput | +0.00 | [-0.00, +0.00] | 1 | |
| ➖ | dsd_uds_1mb_50k_contexts | ingress throughput | -0.00 | [-0.00, +0.00] | 1 | |
| ➖ | dsd_uds_50mb_10k_contexts_no_inlining_no_allocs | ingress throughput | -0.00 | [-0.02, +0.01] | 1 | |
| ➖ | dsd_uds_100mb_250k_contexts | ingress throughput | -0.01 | [-0.03, +0.01] | 1 | |
| ➖ | dsd_uds_500mb_3k_contexts | ingress throughput | -0.04 | [-0.13, +0.05] | 1 | |
| ➖ | dsd_uds_1mb_50k_contexts_memlimit | ingress throughput | -0.28 | [-4.18, +3.61] | 1 |
Explanation
Confidence level: 90.00%
Effect size tolerance: |Δ mean %| ≥ 5.00%
Performance changes are noted in the perf column of each table:
- ✅ = significantly better comparison variant performance
- ❌ = significantly worse comparison variant performance
- ➖ = no significant change in performance
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:
-
Its estimated |Δ mean %| ≥ 5.00%, indicating the change is big enough to merit a closer look.
-
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.
-
Its configuration does not mark it "erratic".
Regression Detector LinksExperiment Result Links
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tobz
changed the title
Context
As part of our obligations when building public artifacts, we must document the license of not only our own software, but the licenses of any dependencies we utilize. While we currently document the licenses used through
LICENSE-3rdparty.csv, we don't include a copy of those licenses alongside the relevant binary artifacts which means that it's both more difficult to look up the contents of those licenses, as well it not knowing which version of the license a given release refers to.Solution
This PR introduces some small changes to our Dockerfiles in order to, based on
LICENSE-3rdparty.csv, determine which licenses are in use and then copy the relevant licenses into the resulting container image. We do this by parsingLICENSE-3rdparty.csvand then utilize SPDX's helpful "License List Data" repository which holds multiple file formats of all of the licenses that it has registered identifiers for. This repository is, by virtue of being under source control, versioned and auditable.Closes #308.