docs: adr 0012 kubernetes execution backend#243
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Four ways panopticon can create and deploy agents into a cluster for long-running, dynamically scalable work (AutoML training loops, batch jobs): a kubectl-driven KubernetesRunner behind the Runner ABC, an in-cluster runner/operator (the M3 press-release shape), DevPod providers as the spawn mechanism, and an agent-facing 'kubernetes' capability that grants a scoped kubeconfig for burst Jobs. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
The callback direction, control-plane lifecycle, and console reach all hinge on where the task service runs, not on which backend option is built; give the nuance its own section. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
…hared cluster Drop the backend survey (KubernetesRunner, operator, DevPod — future ADRs) and commit to the smallest shape: the agent launches Jobs via a scoped kubeconfig. Adds the multi-user isolation design: per-user namespace template (ServiceAccount + Role/RoleBinding, ResourceQuota, LimitRange, default-deny NetworkPolicies), short-lived tokens, and labeling/naming conventions so users' workloads cannot collide. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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