Ability to stop pipelines early

[bcdurak]

This PR introduces comprehensive pipeline stopping functionality to ZenML, with particular focus on the Kubernetes orchestrator implementation. The feature enables users to gracefully or forcefully terminate running pipeline executions through both CLI and programmatic interfaces.

Core Changes

Pipeline Run Stop Interface

• Added stop_run() method to PipelineRunResponse model that delegates to the orchestrator's stop implementation
• Extended ExecutionStatus enum with STOPPING and STOPPED states to track termination lifecycle
• Implemented server-side REST API endpoint /runs/{run_id}/stop with graceful termination option
• Added CLI command zenml pipeline runs stop <run_name_or_id> with --graceful flag (defaults to force stop)

Base Orchestrator Framework

• Extended BaseOrchestrator with supports_cancellation property and abstract stop_run() method
• Implemented status validation to prevent stopping finished or already-stopping pipelines
• Added automatic status transition to STOPPING before calling concrete orchestrator implementations
• Integrated keyboard interrupt handling for synchronous orchestrators

Kubernetes Orchestrator Implementation

Stop Mechanism

The Kubernetes orchestrator implements two stop modes:

1. Force Stop (default): Actively terminates all running step pods associated with the pipeline run
2. Graceful Stop (--graceful flag): Allows the orchestrator pod and running steps to complete naturally without intervention

Technical Implementation

• Leverages Kubernetes label selectors (zenml-orchestrator-run-id) to identify related step pods
• Implements pod discovery and termination with configurable grace periods (30 seconds)

Pipeline Cancellation Detection

• Added check_pipeline_cancellation() function in the Kubernetes orchestrator entrypoint
• Integrated cancellation checks into the ThreadedDagRunner via the check_fn parameter

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