datadog-agent
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refactor(gitlab): put gitlab yaml files under stages folders
What does this PR do?
Rework slightly gitlab yaml files so that they belong to a folder aligned to their gitlab stage.
Motivation
Improve apprehension of gitlab.yml files within the repository
Additional Notes
Possible Drawbacks / Trade-offs
Describe how to test/QA your changes
Reviewer's Checklist
- [ ] If known, an appropriate milestone has been selected; otherwise the
Triage
milestone is set. - [ ] Use the
major_change
label if your change either has a major impact on the code base, is impacting multiple teams or is changing important well-established internals of the Agent. This label will be use during QA to make sure each team pay extra attention to the changed behavior. For any customer facing change use a releasenote. - [ ] A release note has been added or the
changelog/no-changelog
label has been applied. - [ ] Changed code has automated tests for its functionality.
- [ ] Adequate QA/testing plan information is provided. Except if the
qa/skip-qa
label, with required eitherqa/done
orqa/no-code-change
labels, are applied. - [ ] At least one
team/..
label has been applied, indicating the team(s) that should QA this change. - [ ] If applicable, docs team has been notified or an issue has been opened on the documentation repo.
- [ ] If applicable, the
need-change/operator
andneed-change/helm
labels have been applied. - [ ] If applicable, the
k8s/<min-version>
label, indicating the lowest Kubernetes version compatible with this feature. - [ ] If applicable, the config template has been updated.
Bloop Bleep... Dogbot Here
Regression Detector Results
Run ID: 31cac016-48ac-4ab8-b41e-589d64863de9 Baseline: c41a6779b0d6fa1474fe1a37d1f6be2c31910030 Comparison: fd5287f9e4ac86a8d9bf275c4ade3df31108e7cd Total CPUs: 7
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
Experiments with missing or malformed data
- basic_py_check
Usually, this warning means that there is no usable optimization goal data for that experiment, which could be a result of misconfiguration.
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.
Experiments ignored for regressions
Regressions in experiments with settings containing erratic: true
are ignored.
perf | experiment | goal | Δ mean % | Δ mean % CI |
---|---|---|---|---|
➖ | file_to_blackhole | % cpu utilization | -0.45 | [-6.99, +6.10] |
Fine details of change detection per experiment
perf | experiment | goal | Δ mean % | Δ mean % CI |
---|---|---|---|---|
➖ | file_tree | memory utilization | +1.03 | [+0.95, +1.12] |
➖ | otel_to_otel_logs | ingress throughput | +0.67 | [+0.03, +1.32] |
➖ | process_agent_standard_check | memory utilization | +0.25 | [+0.21, +0.28] |
➖ | tcp_dd_logs_filter_exclude | ingress throughput | +0.00 | [-0.00, +0.00] |
➖ | uds_dogstatsd_to_api | ingress throughput | +0.00 | [-0.00, +0.00] |
➖ | trace_agent_msgpack | ingress throughput | -0.02 | [-0.03, -0.01] |
➖ | trace_agent_json | ingress throughput | -0.03 | [-0.06, +0.01] |
➖ | tcp_syslog_to_blackhole | ingress throughput | -0.10 | [-0.16, -0.04] |
➖ | process_agent_real_time_mode | memory utilization | -0.12 | [-0.15, -0.09] |
➖ | process_agent_standard_check_with_stats | memory utilization | -0.19 | [-0.22, -0.16] |
➖ | idle | memory utilization | -0.23 | [-0.27, -0.20] |
➖ | file_to_blackhole | % cpu utilization | -0.45 | [-6.99, +6.10] |
➖ | uds_dogstatsd_to_api_cpu | % cpu utilization | -0.71 | [-2.11, +0.70] |
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".
hi @chouetz
I added two small comments for @DataDog/container-integrations files
Updated, thanks for your review
/trigger-ci --variable RUN_ALL_BUILDS=true --variable RUN_KITCHEN_TESTS=true --variable RUN_E2E_TESTS=auto
/merge
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/merge
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