![]() ![]() Create a table to show the relationships between these entities. Step 1: Identify the objectsĪfter use cases are defined for performance testing, identify the components of each use case and the objects associated with each component. When this is the case, make sure to take those data requirements into account as additional use cases. Remember that different user profiles can have their own page layouts, privileges, and fields. ![]() Reference the numbers you submitted in your request and use the list of scenarios you plan to run as a starting point. You can reuse those calculations to determine the quantity of data required for your tests. ![]() If you requested a performance testing window with Salesforce Customer Service, you already made some throughput calculations. The minimum number of account records needed to generate this load is (75 * 60 / 9) * 100 = 50,000. The average test iteration time per user is 9 seconds, and each iteration requires one account record. In our example, let’s assume that 100 users access the Accounts detail page concurrently for a test time of 75 minutes. The Accounts detail page for the Agent user profile is one use case.Ĭalculate the number of records you must create to test for your desired throughput. This application provides an overview of accounts for sales agents, and further details are posted in the Related tab. Step 0: Identify your use cases and test plan In this post, we walk you through data modeling requirements and a step-by-step methodology for preparing and designing effective test data. If you’re planning to run performance and scale tests, the quantity and the distribution of data play important roles, too. What does it mean for your test data and production data to match? Ideally, you want to have roughly the same quality and variety of test data that you have in production data. The importance of test data quality in performance and scale tests is discussed further in this blog post. But in order for your test results to accurately reflect the performance observed in real-world scenarios, you want your test data to match production data as closely as possible. It’s important to regularly measure and maintain the responsiveness of your system, especially as your usage scales. Greetings, #AwesomeAdmins! Today, we discuss a practice that’s crucial to your Salesforce implementation: performance testing. ![]()
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