An Observation-based Approach Towards Selfmanaging Web Servers
The web server architectures that provide performance isolation, service differentiation, and QoS guarantees rely on external administrators to set the right parameter values for the desired performance. Due to the complexity of handling varying workloads and bottleneck resources, configuring such parameters optimally becomes a challenge. In this paper the authors describe an observation-based approach for self-managing web servers that can adapt to changing workloads while maintaining the QoS requirements of different classes. In this approach, the system state is monitored continuously and parameter values of various system resources primarily the accept queue and the CPU are adjusted to maintain the system-wide QoS goals.