Implement Adaptive Rate Limiting with Machine Learning

Design a sophisticated rate limiting strategy for a high-traffic API that dynamically adjusts throttling thresholds using machine learning algorithms. Create a comprehensive architecture that can predict traffic spikes, automatically scale rate limits based on historical usage patterns, and prevent both over-throttling and potential DDoS vulnerabilities. Include pseudocode demonstrating how the adaptive rate limiting would integrate with existing API infrastructure, with specific considerations for distributed systems and microservices environments.