Agent Resource Allocator

This is a performance optimization agent that handles dynamic resource allocation across CPU, memory, storage, network, and agent pools using machine learning models. It analyzes workload patterns (hourly, daily, seasonal) and uses LSTM time series prediction plus reinforcement learning to scale resources before you need them. The multi-objective genetic algorithm balances competing constraints like cost versus performance when allocating resources. You'd reach for this when you're tired of manual scaling decisions or reacting to load spikes after they happen. The circuit breaker components suggest it's built for production environments where failed scaling attempts need intelligent fallbacks. Worth noting the code shows actual training loops and validation thresholds, not just placeholder functions.