We present a tool, PerfCenter, that takes as input the deployment, configuration, message flow and workload details of the hardware and software servers in an application hosting center, and predicts the performance of the applications. We allow for a hierarchical specification of the data center, where software is deployed on machines, machines consist of hardware devices and are deployed on LANs. We also explicitly model network links between LANs and model the contention at those links due to messages exchanged between servers. While tools and methodologies for such analysis have been proposed earlier, our approach allows for the most natural specification of a "data center" architecture, and is best suited for aiding in design decisions regarding deployment and configuration of software on various hardware architecture scenarios. The tool takes this high level input and generates the underlying queueing network, which is then solved analytically. Since we allow for synchronous method calls, and model contention at software as well as hardware resources, the generated queueing network is solved using approximate methods. We validate the solution against results obtained from a measurement testbed, and found that the predicted values were reasonably accurate.

We present a methodology and tool for performance analysis of distributed server systems, which allows high-level specification of the system, and generates and solves the underlying queueing network model. Our approach is different from the existing ones in that the specification captures the natural manner in which application servers are deployed on machines and machines are deployed on networks. The model does not impose any strict tiers on the server system. Multiple use case scenarios can be specified, and the tool computes measures such as end-to-end response times for each scenario while taking into account queueing delays at the hardware device, software threads and at the network. The development of the tool is ongoing, and will include detailed network protocol models as well as more flexible distributed system behavior, in the future.