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Bump github.com/DataDog/go-libddwaf/v3 from 3.3.0 to 3.4.0
Bumps github.com/DataDog/go-libddwaf/v3 from 3.3.0 to 3.4.0.
Release notes
Sourced from github.com/DataDog/go-libddwaf/v3's releases.
v3.4.0
What's Changed
- feat(lib): use memfd on linux instead of dumping libddwaf.so in /tmp by
@eliottnessin DataDog/go-libddwaf#106- chore: upgrade libddwaf 1.18.0 -> 1.19.1 by
@eliottnessin DataDog/go-libddwaf#108- fix: Don't ignore errors during loading libddwaf shared library by
@keiskuin DataDog/go-libddwaf#107- feat: WAF Run Scope support for RASP Metrics by
@eliottnessin DataDog/go-libddwaf#109New Contributors
@keiskumade their first contribution in DataDog/go-libddwaf#107Full Changelog: https://github.com/DataDog/go-libddwaf/compare/v3.3.0...v3.4.0
Commits
c26efc5feat: WAF Run Scope support for RASP Metrics (#109)8cab7e7Don't ignore errors during loading libddwaf shared library (#107)0ca2830chore: upgrade libddwaf 1.18.0 -> 1.19.1 (#108)5eb76befeat(lib): use memfd on linux instead of dumping libddwaf.so in /tmp (#106)- See full diff in compare view
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Regression Detector
Regression Detector Results
Run ID: 1b90ce64-cc42-413a-a958-f38b863e8b4b Metrics dashboard Target profiles
Baseline: f78e4b2f9772aeadf9fa3197b774dfe6e3d8a345 Comparison: fb597fd427d2a23b3ce283226befb574b6d1d4fb
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
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 | trials | links |
|---|---|---|---|---|---|---|
| ➖ | uds_dogstatsd_to_api_cpu | % cpu utilization | +1.35 | [+0.58, +2.12] | 1 | Logs |
| ➖ | file_tree | memory utilization | +0.67 | [+0.56, +0.78] | 1 | Logs |
| ➖ | otel_to_otel_logs | ingress throughput | +0.64 | [-0.19, +1.47] | 1 | Logs |
| ➖ | idle | memory utilization | +0.20 | [+0.16, +0.25] | 1 | Logs |
| ➖ | uds_dogstatsd_to_api | ingress throughput | +0.00 | [-0.00, +0.00] | 1 | Logs |
| ➖ | tcp_dd_logs_filter_exclude | ingress throughput | -0.00 | [-0.01, +0.01] | 1 | Logs |
| ➖ | pycheck_lots_of_tags | % cpu utilization | -0.22 | [-2.86, +2.42] | 1 | Logs |
| ➖ | basic_py_check | % cpu utilization | -0.44 | [-3.24, +2.35] | 1 | Logs |
| ➖ | tcp_syslog_to_blackhole | ingress throughput | -0.57 | [-0.62, -0.52] | 1 | Logs |
Bounds Checks
| perf | experiment | bounds_check_name | replicates_passed |
|---|---|---|---|
| ✅ | idle | memory_usage | 10/10 |
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:
-
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".
@dependabot recreate
A newer version of github.com/DataDog/go-libddwaf/v3 exists, but since this PR has been edited by someone other than Dependabot I haven't updated it. You'll get a PR for the updated version as normal once this PR is merged.
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