Using Reinforcement Learning to Control Auto-Scaling of Distributed Applications
Gabriele Russo Russo · 2023
Modern distributed systems can benefit from the availability of large-scale and heterogeneous computing infrastructures. However, the complexity and dynamic nature of these environments also call for self-adaptation abilities, as guaranteeing efficient resource usage and acceptable service levels through static configurations is very difficult.