Handle multiple releases in the create_rc_pr workflow

[FlorentClarret]

What does this PR do?

Handle multiple releases in the create_rc_pr workflow.

The idea is to:

1. Get all the release branches that are not released yet (currently: 7.56 and 7.57)
2. For each of them, run a sub workflow that will look for changes and create a PR if needed

Motivation

The current version of the workflow does not work when we have two releases at the same time, in our current case:

• 7.56 is not released yet
• But the process for 7.57 started

The new version of this workflow will look for all the versions not released yet and trigger a job for each of them

Additional Notes

Workflow example with no new commits on 7.56 and new commits on 7.57: https://github.com/DataDog/datadog-agent/actions/runs/10466407557/job/28983252441?pr=28539

Which created this PR: #28569

Possible Drawbacks / Trade-offs

Describe how to test/QA your changes

[agent-platform-auto-pr]

[Fast Unit Tests Report]

On pipeline 42246386 (CI Visibility). The following jobs did not run any unit tests:

Jobs:

• tests_deb-arm64-py3
• tests_deb-x64-py3
• tests_flavor_dogstatsd_deb-x64
• tests_flavor_heroku_deb-x64
• tests_flavor_iot_deb-x64
• tests_rpm-arm64-py3
• tests_rpm-x64-py3
• tests_windows-x64

If you modified Go files and expected unit tests to run in these jobs, please double check the job logs. If you think tests should have been executed reach out to #agent-devx-help

[pr-commenter]

Regression Detector

Regression Detector Results

Run ID: c4954816-865f-4bbb-830d-57d8675bf3de Metrics dashboard Target profiles

Baseline: 7f068e9
Comparison: 5c39f2c

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	links
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	+0.43	[-0.46, +1.31]	Logs
➖	idle	memory utilization	+0.25	[+0.22, +0.28]	Logs
➖	tcp_dd_logs_filter_exclude	ingress throughput	+0.00	[-0.01, +0.01]	Logs
➖	uds_dogstatsd_to_api	ingress throughput	-0.00	[-0.00, +0.00]	Logs
➖	file_tree	memory utilization	-0.26	[-0.33, -0.20]	Logs
➖	otel_to_otel_logs	ingress throughput	-0.37	[-1.18, +0.44]	Logs
➖	basic_py_check	% cpu utilization	-0.56	[-3.30, +2.18]	Logs
➖	pycheck_1000_100byte_tags	% cpu utilization	-1.04	[-5.83, +3.74]	Logs
➖	tcp_syslog_to_blackhole	ingress throughput	-1.38	[-14.11, +11.35]	Logs

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".

[FlorentClarret]

/merge

[dd-devflow]

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[dd-devflow]

🚂 MergeQueue: pull request added to the queue

The median merge time in main is 23m.

Use /merge -c to cancel this operation!