AI-Powered Load Balancing Intermediate

class AILoadBalancer:
    def select_backend(self, request, backends):
        """Select optimal backend based on ML prediction"""
        scores = []
        for backend in backends:
            predicted_latency = self.latency_model.predict({
                "request_type": request.type,
                "request_size": request.content_length,
                "backend_cpu": backend.cpu_utilization,
                "backend_memory": backend.memory_utilization,
                "active_connections": backend.active_conns,
                "avg_response_time_1m": backend.avg_rt_1m,
                "error_rate_1m": backend.error_rate_1m
            })
            scores.append((backend, predicted_latency))
        # Select backend with lowest predicted latency
        return min(scores, key=lambda x: x[1])[0]