Taming the Beast: How ScyllaDB Leverages Control Theory to Keep Compactions Under Control

ScyllaDB employs control theory to manage database compactions by automating resource allocation, thus maintaining system performance without user intervention. This approach addresses the challenges of balancing foreground requests and background processes, such as compactions, which are crucial for databases using Log Structured Merge trees. By leveraging control systems, ScyllaDB ensures that compaction bandwidth is dynamically adjusted to maintain a predictable system response, reducing the operational burden on users and adapting to workload changes autonomously. This method allows ScyllaDB to achieve equilibrium in resource usage, ensuring stable latency and throughput even as workloads fluctuate. The database's control system uses schedulers similar to industrial controllers, adjusting resource shares to manage the compaction backlog effectively, ultimately providing a resilient and efficient database environment.