Performance and Scalability Factors

The good news is that StarTeam is a rich application that can be used in a variety of ways. The bad news is that this flexibility makes it difficult to predict exactly what hardware configuration is perfect for your organization. Here are the major factors that affect the performance and scalability of a StarTeam configuration:

Repository Size
The number of views and items affect the StarTeam Server process’s memory usage, database query traffic, and other resource factors more than any other type of data. Other kinds of data such as users, groups, queries, and filters have a lesser effect on resource demand. Simply put, as the repository gets bigger, more demand is placed on server caching and database queries.
Concurrent Users
The number of concurrent users during peak periods has a significant affect on a server. Each concurrent user requires a session, which maintains state, generates commands that utilize worker threads, incurs locking, and so forth. The number of defined users is not nearly as important as the number concurrent users during peak periods. If you use a single metric for capacity planning, use concurrent users.
It boosts server scalability, so whether or not you deploy it and whether or not clients enable it will affect scalability. MPX Cache Agents not only significantly boost check-out performance for remote users, but they also remove significant traffic from the server. In short, deploying will bolster your configuration’s scalability.
Bulk Applications
On-line users that utilize a graphical client typically incur low demand on the server. In contrast, bulk applications such as “extractors” for Datamart or Search and “synchronizers” for integrations such as Caliber or StarTeam Quality Center Synchronizer tend to send continuous streams of commands for long durations. A single bulk application can generate demand comparable to 10-20 on-line users.
Application Complexity
Due to its customizability, StarTeam allows you to build sophisticated custom forms, add lots of custom fields to artifact types, create custom reports, and so forth. The more sophisticated your usage becomes, the more commands will be generated and the bigger artifacts will get, both of which increase demand.

Consider these factors when deciding the size of your configuration. Because of the unique factors that define your environment, take these deployment suggestions as guidelines only.