DOG-6508: Fix metrics pickling issue in multiprocessing runtime

[Hmnt39]

This PR reesolves metrics serialization errors when passing BaseMetrics instances through multiprocessing by changing the runtime to pass the metrics class instead of an instance. The extractor now initializes metrics internally using a singleton pattern to avoid Prometheus registry conflicts.

Added comprehensive tests to verify metrics work correctly across process boundaries.

[gemini-code-assist]

Summary of Changes

Hello @Hmnt39, 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 addresses a critical issue where metrics instances failed to serialize correctly when passed between processes in a multiprocessing runtime, leading to errors and unreliable metrics collection. The solution refactors the metrics handling mechanism to pass the metrics class itself, allowing each process to initialize its own metrics instance using a controlled singleton pattern. This ensures proper metrics collection, avoids conflicts with the Prometheus registry, and enhances the robustness of the metrics system in distributed environments.

Highlights

• Metrics Serialization Fix: Resolved metrics serialization errors that occurred when passing BaseMetrics instances through multiprocessing by changing the runtime to pass the metrics class instead of an instance.
• Singleton Metrics Initialization: The extractor now initializes metrics internally using a singleton pattern, which effectively avoids Prometheus registry conflicts across different processes.
• Improved Test Coverage: Comprehensive tests have been added to thoroughly verify that metrics function correctly and are properly incremented across process boundaries in a multiprocessing environment.
• API Changes: The Extractor and Runtime classes have been updated to accept a metrics class type instead of a metrics instance, simplifying the API and enabling the new singleton pattern.

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[gemini-code-assist]

Code Review

This pull request effectively addresses the metrics serialization issue in a multiprocessing environment by shifting from passing metric instances to passing metric classes. The introduction of a singleton pattern for metrics initialization within the extractor is a solid approach to prevent Prometheus registry conflicts. The changes are well-structured and the addition of a comprehensive integration test in test_runtime.py is excellent for verifying the fix. I've found one critical issue in the implementation of the metrics loading logic that could lead to runtime errors and inconsistencies. My feedback focuses on making this implementation more robust and consistent.

[gemini-code-assist]

This logic for creating the metrics instance has two issues:

1. The call to safe_get(metrics_class) assumes a no-argument constructor, which contradicts the BaseMetrics constructor and the MyMetrics example in the docstring. This will lead to a TypeError.
2. The else block instantiates BaseMetrics directly, bypassing safe_get. This breaks the singleton pattern and can cause Prometheus registry conflicts if BaseMetrics is instantiated via safe_get elsewhere.

A more robust implementation would be to always use safe_get and pass the required extractor_name and extractor_version arguments. This will require updating any custom metric classes in tests (like TestMetrics) to accept these arguments in their __init__ method.

        cls_to_use = metrics_class or BaseMetrics
        metrics_instance = safe_get(cls_to_use, extractor_name=self.EXTERNAL_ID, extractor_version=self.VERSION)