Why Siebel load testing?
Siebel provides a wide range of
business-critical applications for Sales, Marketing, Contact Center, Self-Service and more. These Siebel applications
are highly interactive, intuitive and personalized, delivering the user experience of a Win-32 application within a browser environment. Ensuring
Siebel application quality and performance is critical but also challenging.
There are many different applications and business transaction flows to test.
The Siebel application infrastructure is a complex system comprised of multiple components, including a traditional Web-based front end, Siebel application
and gateway servers and one of multiple possible databases. As a result, application quality and performance
can be difficult to ensure prior to deployment with traditional test methods. Poor application quality and performance can have any number of
detrimental effects including lost productivity, failed adoption and dissatisfied users. Any of which can result in impact to bottom-line performance.
How to test the performance?
Load testing can help you ensure that your Siebel application will perform and scale under real user
workloads once it's deployed to production. This can help you ensure that it will be able to withstand
the expected number of concurrent users while maintaining acceptable performance and response
times. It can also help you identify and address critical bottlenecks prior to deployment. Stress testing
can be performed to test beyond the limits of normal operation and helps you assess the capacity and
scalability of your application infrastructure.
Some key questions to consider in terms of application performance are:
- Will the Siebel application be able to handle the number of concurrent users we expect?
- What will the response times be like during peak usage periods?
- Are there any bottlenecks in the application or infrastructure that will limit performance?
- Did we size the hardware appropriately and do we have the capacity to meet future growth?
Load testing will identify system bottlenecks that occur below normal and maximum anticipated load volume.
Retest with identical setup after making changes that correct the bottlenecks.
Testing is repeated until all bottlenecks are eliminated and/or system performance is acceptable.
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