Run Argo Workflows E2E with the Kubernetes Agent backend

[vitkyrka]

What does this PR do?

Runs the Argo Workflows Kind E2E with the Kubernetes Agent backend introduced by #24639. workflow-controller has no backing Service, so the Agent (now running inside the Kind cluster) reaches it directly via the pod's IP address, fetched with kubectl get pods --namespace argo --selector app=workflow-controller --output json. The check now scrapes http://<pod-ip>:9090/metrics, so the external Docker Agent and the kubectl port-forward to workflow-controller are no longer needed.

Validation:

• ddev test -fs argo_workflows
• ddev --no-interactive test argo_workflows (3 passed, 1 E2E skipped)
• ddev env show argo_workflows (py3.13)
• ddev env start --dev argo_workflows py3.13
• ddev env test --dev argo_workflows py3.13 (1 passed, 3 deselected)
• ddev env stop argo_workflows py3.13

Motivation

This PR follows the conversion pattern from #24674 (argo_rollouts), adapted for a target with no Service: the pod IP is fetched directly, mirroring the approach used for Velero's node-agent DaemonSet in #24645. Running the Agent inside the same Kind cluster removes the long-lived host-side port-forward without changing the E2E setup, waits, instance shape, or assertions.

Review checklist (to be filled by reviewers)

• Feature or bugfix MUST have appropriate tests (unit, integration, e2e)
• Add qa/required if this PR needs QA validation, or qa/skip-qa if it does not. Exactly one of the two is required.
• If you need to backport this PR to another branch, you can add the backport/<branch-name> label to the PR and it will automatically open a backport PR once this one is merged

[datadog-prod-us1-3]

🎉 All green!

🧪 All tests passed
❄️ No new flaky tests detected

_{This comment will be updated automatically if new data arrives.
🔗 Commit SHA: a686e38 | Docs | Datadog PR Page | Give us feedback!}

[cit-pr-commenter-54b7da]

evalya-impact-summary

evalya impact analysis

Impact analysis: RUN-ALL — every test task will run
Trigger:         empty diff (default branch, scheduled run, or shallow-clone fallback)
Test tasks:      0 (all selected)
Publish tasks:   1 (always emitted)
Diff:            empty (no diff information)

Learn more about CI impact filtering

[vitkyrka]

@codex review

[chatgpt-codex-connector]

Codex Review: Didn't find any major issues. Breezy!

Reviewed commit: 76e1a88b2d

ℹ️ About Codex in GitHub

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• Open a pull request for review
• Mark a draft as ready
• Comment "@codex review".

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[vitkyrka]

@codex review

[chatgpt-codex-connector]

Codex Review: Didn't find any major issues. Already looking forward to the next diff.

Reviewed commit: 0a45fc3fb4

ℹ️ About Codex in GitHub

Your team has set up Codex to review pull requests in this repo. Reviews are triggered when you

• Open a pull request for review
• Mark a draft as ready
• Comment "@codex review".

If Codex has suggestions, it will comment; otherwise it will react with 👍.

Codex can also answer questions or update the PR. Try commenting "@codex address that feedback".

[dd-octo-sts]

Validation Report

All 21 validations passed.

Show details

Validation	Description	Status
agent-reqs	Verify check versions match the Agent requirements file	✅
ci	Validate CI configuration and code coverage settings	✅
codeowners	Validate every integration has a CODEOWNERS entry	✅
config	Validate default configuration files against spec.yaml	✅
dep	Verify dependency pins are consistent and Agent-compatible	✅
http	Validate integrations use the HTTP wrapper correctly	✅
imports	Validate check imports do not use deprecated modules	✅
integration-style	Validate check code style conventions	✅
jmx-metrics	Validate JMX metrics definition files and config	✅
labeler	Validate PR labeler config matches integration directories	✅
legacy-signature	Validate no integration uses the legacy Agent check signature	✅
license-headers	Validate Python files have proper license headers	✅
licenses	Validate third-party license attribution list	✅
metadata	Validate metadata.csv metric definitions	✅
models	Validate configuration data models match spec.yaml	✅
openmetrics	Validate OpenMetrics integrations disable the metric limit	✅
package	Validate Python package metadata and naming	✅
qa-label	Validate the pull request declares whether it needs QA for the next Agent release	✅
readmes	Validate README files have required sections	✅
saved-views	Validate saved view JSON file structure and fields	✅
version	Validate version consistency between package and changelog	✅

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