[task-run-ci-external-contributor] Add task to run CI from external contributor
What does this PR do?
Adds a task pipeline.trigger-external to trigger the gitlab / circle CI from an external contributor by creating and pushing a branch to this repo (following https://datadoghq.atlassian.net/browse/APL-1995)
Example
inv pipeline.trigger-external Dog/my-feature
Will push the branch my-feature of Dog/datadog-agent to a new branch dog/my-feature in this repo.
Note that we can add --no-verify to add this flag to the push.
Motivation
Additional Notes
Possible Drawbacks / Trade-offs
Describe how to test/QA your changes
Bloop Bleep... Dogbot Here
Regression Detector Results
Run ID: 14f39ae5-cd2e-42b4-93e2-bd864d66d9cb Baseline: 9387a5c1f0cda4bec2f4267477351a6ccd048e8c Comparison: aafb6f757db05535a4856ecf8641334da96fc4b7
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.
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 | -30.00 | [-35.38, -24.61] |
Fine details of change detection per experiment
| perf | experiment | goal | Δ mean % | Δ mean % CI |
|---|---|---|---|---|
| ➖ | pycheck_1000_100byte_tags | % cpu utilization | +3.11 | [-2.22, +8.44] |
| ➖ | basic_py_check | % cpu utilization | +2.71 | [+0.29, +5.12] |
| ➖ | file_tree | memory utilization | +1.23 | [+1.14, +1.31] |
| ➖ | idle | memory utilization | +0.25 | [+0.22, +0.28] |
| ➖ | otel_to_otel_logs | ingress throughput | +0.13 | [-0.31, +0.56] |
| ➖ | uds_dogstatsd_to_api | ingress throughput | +0.02 | [-0.19, +0.22] |
| ➖ | tcp_dd_logs_filter_exclude | ingress throughput | +0.01 | [+0.00, +0.01] |
| ➖ | trace_agent_json | ingress throughput | +0.00 | [-0.03, +0.03] |
| ➖ | trace_agent_msgpack | ingress throughput | +0.00 | [-0.00, +0.01] |
| ➖ | process_agent_real_time_mode | memory utilization | -0.05 | [-0.10, -0.01] |
| ➖ | uds_dogstatsd_to_api_cpu | % cpu utilization | -0.15 | [-3.12, +2.82] |
| ➖ | process_agent_standard_check | memory utilization | -0.39 | [-0.43, -0.35] |
| ➖ | tcp_syslog_to_blackhole | ingress throughput | -0.93 | [-1.03, -0.83] |
| ➖ | process_agent_standard_check_with_stats | memory utilization | -1.04 | [-1.08, -1.00] |
| ✅ | file_to_blackhole | % cpu utilization | -30.00 | [-35.38, -24.61] |
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".
Can't wait for this PR to be merged, doing it manually is super annoying 😄
/merge
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