Reduce K8s test resource usage with single-node Kind clusters

[nailo2c]

The K8s test Kind clusters have used a control-plane + worker topology since the original Kind migration in 2019 (#5837), and it was never revisited. Nothing uses the second node: workload pods can never schedule on the control-plane (NoSchedule taint), yet kind load copies the ~1.8GB Airflow image and the pinned test images into every node — the control-plane copy is pure overhead. No test depends on the topology.

This switches the cluster to a single control-plane node (Kind's own default), which runs the workloads too — Kind removes the taint on single-node clusters.

Changes

• kind-cluster-conf.yaml: drop the worker node, move extraPortMappings to the control-plane
• get_kubernetes_port_numbers(): the forwarded port was read from the hard-coded nodes[1], which raises IndexError on the new config; it now looks the mapping up by containerPort, so rendered configs of clusters created before this change keep working too
• unit tests for the port extraction (single-node / legacy two-node / missing mapping)
• doc sample outputs and workflow comments updated to match

Local benchmark

Single run, Apple-silicon macOS + Docker Desktop, same image on both sides, KubernetesExecutor, python 3.10 / K8s v1.30.13:

metric	two-node (main)	single-node (this PR)	delta
upload-k8s-image	114.1s	66.4s	−42%
containerd disk, all nodes	15.1 GB	7.8 GB	−48%
memory after deploy, all nodes	~3.39 GiB	~2.65 GiB	−22%
kind create cluster ¹	50.5s	16.8s	−67%
deploy-airflow	97.0s	83.9s	−14%
test results	57 passed / 3 skipped	57 passed / 3 skipped	identical

¹ measured with plain kind create cluster and the node image cached on both sides, isolating the topology effect — the worker join is the expensive part.

Verification

• KubernetesExecutor suite on the single-node cluster: 57 passed / 3 skipped — identical to the two-node baseline
• CeleryExecutor (largest pod count: redis + celery workers): 53 passed / 7 skipped, including the two Celery-specific tests that are skipped under KubernetesExecutor

Every job in the CI K8s matrix (36 K8S System jobs per canary run, ~500 job-minutes) pays the double image load today. I'll post a per-job duration comparison against recent canary runs once CI has run on this PR.

Validation

• uv run --project dev/breeze pytest dev/breeze/tests/test_kubernetes_utils.py -xvs
• prek run --from-ref main --stage pre-commit
• full manual breeze k8s flow (create / configure / upload / deploy / tests / delete) for both executors above

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Was generative AI tooling used to co-author this PR?

• Yes — Claude Code (Fable 5)

Generated-by: Claude Code (Fable 5) following the guidelines