Maximizing performance

In order to maximize performance for IBM® Engineering Lifecycle Management applications, you must understand your own installation environment and how it handles certain factors that can affect its performance.

The following factors can affect performance:
  • Ensure that the network latency between all servers involved is as small as possible. This suggestion is especially true for the network between the application server and the database server as well as for the network between an application and its Jazz® Team Server (JTS). A good rule of thumb is that ping times between servers and the database should be less than 0.5 ms, but smaller is even better.
  • Make sure that the machine specifications match the workload of the installed software. The database server should have fast disk access and the application server should have a fast CPU. Both servers will work better with more memory. Also ensure that the application server and database processes are configured to use the available memory.
  • Make sure that the application server and database software is up to date and tuned using tuning guides for those products.
  • Make sure that the OS is tuned using OS specific tuning options. This is also related to the workload of the machine. Database servers should be tuned to allow fast disk access, while application servers should be tuned for CPU and network performance.
  • Application level tuning, such as reducing the number of widgets on a dashboard.
  • Widget population. If you find that you do not use some of the widgets on the home page, close them. The widgets query the server frequently, which can reduce performance.
  • The browser that you use. For example, the Quality Management application works more efficiently on Firefox than on Microsoft Internet Explorer.
  • In the Quality Management application, when you run queries on test artifacts, you can use the column-filtering capabilities in the list views to help limit the number of artifacts that display and to locate specific test artifacts more quickly, which helps to improve the performance of the product.

For advanced or deployment-specific information about performance troubleshooting, see the Performance troubleshooting section of the Deployment wiki.

Document Description
Performance data sheets A Deployment wiki page that contains links to the ELM-specific performance data sheets and performance related case studies.
CLM Sizing Strategy Information contained in this sizing guide is based on a sophisticated performance test environment using a full application lifecycle workload.
Best practices for configuring LQE for performance and scalability A Deployment wiki page that provides hardware, deployment, and configuration recommendations for LQE.