toremaxi.blogg.se - Apache jmeter passing different data for each request

APACHE JMETER PASSING DIFFERENT DATA FOR EACH REQUEST HOW TO
APACHE JMETER PASSING DIFFERENT DATA FOR EACH REQUEST SERIES
APACHE JMETER PASSING DIFFERENT DATA FOR EACH REQUEST FREE

By that I mean keeping some of the parameters consistent for 1000 users, 2000 users, so forth and so on.

It’s about validating our sizing guidelines, which can be done in a variety of ways, but benchmarking is one of the best because it’s done in a controlled environment.

If it costs an average of $1 worth of hardware for the first user, it should remain around $1 for user number 10,000.

In other words, we expect consistent average cost per user.

Performance is about scalability as well, not only because users expect us to deliver guidance with regard to hardware resource consumption, but also because the resource consumption must be predictable as we add more users or process greater volume of data.

We need to answer questions as to what kind of hardware resources will be needed to bring BI to ‘n’ number of users with a certain set of technical criteria.

It’s about sizing, or translating the business requirements of your customer into actual hardware resource consumption.

I’ll borrow something that a colleague of mine, Pierre Leroux, said previously on the subject that boils the concept down pretty well: So, how does one develop a performance testing strategy?Īt a high level, Load Testing is about three things: sizing, scalability and benchmarking. Though some of the steps will, by necessity, be specific to JMeter, I will try to unlock the framework of the BI Platform enough so that the material is relevant to any other load testing tool on the market.

APACHE JMETER PASSING DIFFERENT DATA FOR EACH REQUEST FREE

The tool I’ve chosen to create and execute the performance tests is Apache JMeter, due primarily to the fact it is free and accessible to the general public.

APACHE JMETER PASSING DIFFERENT DATA FOR EACH REQUEST SERIES

I’m planning to propose such a foundation in a series of articles I’ll be publishing to SDN this year and will provide numerous concrete examples for performance testing in SAP BusinessObjects Enterprise XI 3.1 and SAP Business Intelligence Platform 4.0. Questions like this, along with concepts like impact analysis of on-boarding new tenants or business units and forecasting server requirements for the refresh of leased hardware can be answered with a solid methodology for Performance Testing. How do I size my Java Application Server to accommodate a specific amount of concurrent usage?.Can my Crystal and Web Intelligence servers safely co-exist on the same physical machine based on specific usage patterns?.How much impact do report characteristics such as drill filters, subreports, charting, and data volume have on resource consumption?.Here are some other examples of questions that an administrator might need to answer: In order to determine the best value, one should consider running a series of performance tests at 25 and 40 and measure how the system behaves under load from real business processes. Depending on report complexity and usage patterns, the optimum number could be 25, 40, or somewhere in between. Think about it this way … the SAP BusinessObjects Enterprise XI 3.1 Sizing Guide suggests a range of 25-40 Web Intelligence connections per CPU.

APACHE JMETER PASSING DIFFERENT DATA FOR EACH REQUEST HOW TO

Sure there is a fair amount of guidance out there in terms of documentation on how to calculate the amount of CPU and Memory needed to service a given amount of volume, but as with many things, the devil is in the details.

As any SAP BusinessObjects administrator can tell you, sizing an environment can be a challenging task.