chore: enhance Runner.service for more cases.

[k82cn]

No description provided.

[gemini-code-assist]

Summary of Changes

Hello @k82cn, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request significantly enhances the Runner.service functionality by introducing explicit controls for state persistence and instance autoscaling. It refactors the underlying execution model to improve efficiency by loading execution objects once per session and provides robust support for managing service instances within the scheduler, allowing for more flexible and performant distributed applications.

Highlights

• Enhanced Runner.service API: The Runner.service() method now accepts stateful and autoscale parameters, replacing the previous kind parameter. This decouples state persistence from instance scaling, offering more granular control over service behavior.
• Flexible Instance Scaling: Services can now be configured with autoscale=True for dynamic scaling (min 0, max unlimited instances) or autoscale=False for a single, dedicated instance (min 1, max 1). Sensible defaults are applied based on the execution object type (functions autoscale, classes/instances do not).
• Improved Execution Efficiency: Execution objects are now loaded and, if applicable, instantiated once per session (on_session_enter) rather than per task (on_task_invoke). This significantly reduces overhead for stateful services.
• State Persistence Control: The stateful=True parameter ensures that the execution object's state is persisted back to the cache after each task, allowing stateful services to maintain their state across executions and recover from executor failures.
• Scheduler and Database Integration: The session manager, scheduler, and database schema have been updated to support the new min_instances and max_instances configurations. The FairShare scheduler plugin now respects these limits, guaranteeing minimum allocations and capping maximum instances.

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[gemini-code-assist]

Code Review

The pull request introduces significant enhancements to the Runner service, allowing for more granular control over state persistence and instance scaling. The changes are well-implemented across the Python SDK, RPC definitions, session manager, and scheduler components. The accompanying design document is comprehensive and clearly outlines the motivation, new API, implementation details, and potential limitations. The new test cases adequately cover the added functionality, including default behaviors and error conditions. Overall, this is a robust and well-thought-out feature implementation.