Evaluate the challenges and propose solutions for implementing distributed machine learning models across global data centers in an MLOps context.

Instruction: Discuss the primary challenges of deploying and managing distributed ML models in a global infrastructure. Provide detailed solutions for each identified challenge, focusing on synchronization, latency, data localization, and compliance with data protection regulations.

Context: This question assesses the candidate's understanding of the complexities involved in deploying distributed machine learning models in an MLOps framework, especially in a global context. It tests their knowledge of network and data challenges, including latency, data localization, and legal compliance. The question also evaluates the candidate's ability to propose practical and effective solutions for these challenges, demonstrating a deep understanding of both MLOps principles and global IT infrastructure requirements.