How would you approach building a scalable and robust logging system for ML models?
Instruction: Describe the architecture and technologies you would use to implement a logging system that scales with the deployment of numerous ML models.
Context: This question tests the candidate's ability to design a logging system that is both scalable and capable of handling the complex data generated by ML models, crucial for monitoring and debugging.
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I would design the logging system around queryability, privacy boundaries, and high-cardinality production reality...