Generate a PR to auto bump windows gitlab runner version on every new RC

[Pythyu]

What does this PR do?

Add a new job generate_windows_gitlab_runner_bump_pr which depends on trigger_auto_staging_release to generate a workflow on buildenv repository to bump windows runner agent version.

Motivation

RFC

Describe how you validated your changes

Possible Drawbacks / Trade-offs

Additional Notes

[Pythyu]

Finishing QA before marking it as ready

[agent-platform-auto-pr]

Gitlab CI Configuration Changes

Added Jobs

generate_windows_gitlab_runner_bump_pr

generate_windows_gitlab_runner_bump_pr:
  image: registry.ddbuild.io/ci/datadog-agent-buildimages/deb_x64$DATADOG_AGENT_BUILDIMAGES_SUFFIX:$DATADOG_AGENT_BUILDIMAGES
  needs:
  - trigger_auto_staging_release
  rules:
  - if: $DDR == "true"
    when: never
  - if: $CI_COMMIT_TAG =~ /^[0-9]+\.[0-9]+\.[0-9]+-v[0-9]+\.[0-9]+\.[0-9]+(-rc\.[0-9]+){0,1}$/
    when: never
  - if: $DEPLOY_AGENT == "true" || $DDR_WORKFLOW_ID != null
  script:
  - "if [[ \"$(( RANDOM % 2 ))\" == \"1\" ]]; then\n  GITHUB_KEY_B64=$($CI_PROJECT_DIR/tools/ci/fetch_secret.sh\
    \ $MACOS_GITHUB_APP_1 key_b64) || exit $?; export GITHUB_KEY_B64\n  GITHUB_APP_ID=$($CI_PROJECT_DIR/tools/ci/fetch_secret.sh\
    \ $MACOS_GITHUB_APP_1 app_id) || exit $?; export GITHUB_APP_ID\n  GITHUB_INSTALLATION_ID=$($CI_PROJECT_DIR/tools/ci/fetch_secret.sh\
    \ $MACOS_GITHUB_APP_1 installation_id) || exit $?; export GITHUB_INSTALLATION_ID\n\
    \  echo \"Using GitHub App instance 1\"\nelse\n  GITHUB_KEY_B64=$($CI_PROJECT_DIR/tools/ci/fetch_secret.sh\
    \ $MACOS_GITHUB_APP_2 key_b64) || exit $?; export GITHUB_KEY_B64\n  GITHUB_APP_ID=$($CI_PROJECT_DIR/tools/ci/fetch_secret.sh\
    \ $MACOS_GITHUB_APP_2 app_id) || exit $?; export GITHUB_APP_ID\n  GITHUB_INSTALLATION_ID=$($CI_PROJECT_DIR/tools/ci/fetch_secret.sh\
    \ $MACOS_GITHUB_APP_2 installation_id) || exit $?; export GITHUB_INSTALLATION_ID\n\
    \  echo \"Using GitHub App instance 2\"\nfi\n"
  - $S3_CP_CMD $S3_ARTIFACTS_URI/agent-version.cache .
  - inv -e github.trigger-buildenv "$CI_COMMIT_REF_NAME"
  stage: trigger_release
  tags:
  - arch:amd64

Changes Summary

Removed	Modified	Added	Renamed
0	0	1	0

ℹ️ Diff available in the job log.

[agent-platform-auto-pr]

[Fast Unit Tests Report]

On pipeline 50862817 (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

[cit-pr-commenter]

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: aac7e68e-2bf7-4046-a3d3-e6cf765be64c

Baseline: d9a4c78
Comparison: bc16146
Diff

Optimization Goals: ✅ No significant changes detected

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	+2.97	[+2.23, +3.71]	1	Logs
➖	file_tree	memory utilization	+1.54	[+1.42, +1.66]	1	Logs
➖	otel_to_otel_logs	ingress throughput	+1.26	[+0.59, +1.93]	1	Logs
➖	file_to_blackhole_1000ms_latency	egress throughput	+0.73	[-0.06, +1.51]	1	Logs
➖	quality_gate_idle_all_features	memory utilization	+0.68	[+0.55, +0.80]	1	Logs bounds checks dashboard
➖	file_to_blackhole_500ms_latency	egress throughput	+0.16	[-0.62, +0.94]	1	Logs
➖	file_to_blackhole_1000ms_latency_linear_load	egress throughput	+0.08	[-0.38, +0.54]	1	Logs
➖	file_to_blackhole_0ms_latency_http2	egress throughput	+0.03	[-0.82, +0.88]	1	Logs
➖	file_to_blackhole_100ms_latency	egress throughput	+0.03	[-0.70, +0.75]	1	Logs
➖	uds_dogstatsd_to_api	ingress throughput	+0.02	[-0.10, +0.13]	1	Logs
➖	tcp_dd_logs_filter_exclude	ingress throughput	+0.00	[-0.01, +0.01]	1	Logs
➖	file_to_blackhole_0ms_latency	egress throughput	-0.01	[-0.81, +0.79]	1	Logs
➖	file_to_blackhole_300ms_latency	egress throughput	-0.04	[-0.67, +0.59]	1	Logs
➖	file_to_blackhole_0ms_latency_http1	egress throughput	-0.05	[-0.88, +0.78]	1	Logs
➖	tcp_syslog_to_blackhole	ingress throughput	-0.14	[-0.21, -0.07]	1	Logs
➖	quality_gate_idle	memory utilization	-0.61	[-0.65, -0.57]	1	Logs bounds checks dashboard
➖	quality_gate_logs	% cpu utilization	-3.42	[-6.33, -0.51]	1	Logs

Bounds Checks: ❌ Failed

perf	experiment	bounds_check_name	replicates_passed	links
❌	file_to_blackhole_100ms_latency	lost_bytes	9/10
❌	file_to_blackhole_500ms_latency	lost_bytes	9/10
✅	file_to_blackhole_0ms_latency	lost_bytes	10/10
✅	file_to_blackhole_0ms_latency	memory_usage	10/10
✅	file_to_blackhole_0ms_latency_http1	lost_bytes	10/10
✅	file_to_blackhole_0ms_latency_http1	memory_usage	10/10
✅	file_to_blackhole_0ms_latency_http2	lost_bytes	10/10
✅	file_to_blackhole_0ms_latency_http2	memory_usage	10/10
✅	file_to_blackhole_1000ms_latency	memory_usage	10/10
✅	file_to_blackhole_1000ms_latency_linear_load	memory_usage	10/10
✅	file_to_blackhole_100ms_latency	memory_usage	10/10
✅	file_to_blackhole_300ms_latency	lost_bytes	10/10
✅	file_to_blackhole_300ms_latency	memory_usage	10/10
✅	file_to_blackhole_500ms_latency	memory_usage	10/10
✅	quality_gate_idle	memory_usage	10/10	bounds checks dashboard
✅	quality_gate_idle_all_features	memory_usage	10/10	bounds checks dashboard
✅	quality_gate_logs	lost_bytes	10/10
✅	quality_gate_logs	memory_usage	10/10

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:

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".

CI Pass/Fail Decision

✅ Passed. All Quality Gates passed.

• quality_gate_idle_all_features, bounds check memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_logs, bounds check lost_bytes: 10/10 replicas passed. Gate passed.
• quality_gate_logs, bounds check memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_idle, bounds check memory_usage: 10/10 replicas passed. Gate passed.