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What Can Go Wrong During Results Analysis
Recommended guidance Results analysis can be misleading when test data, environment, load model, monitoring, or reporting context is incomplete. Review failures and performance results with enough evidence to separate application defects from test or environme...
Determine the Scale and Resources Needed for a Performance Test
Contents Linear Scalability in Test Servers The Methodology Transforming Calibration Results to TPS Mitigations Rapidly Determine The Scale Of A Performance Test The Appvance Calibration Testing Methodology is an important step in determining app s...
Linear Scalability in Test Servers
Start a performance test too high and the test delivers results that are a function of a performance bottleneck in the test server itself and not the application under test. Start too low and the results may not hit the upper limits of your app performance and...
The Methodology
Here are the steps to this methodology: Determine a starting number of concurrently running virtual users. I use ...
Transforming Calibration Results to TPS
Apps are increasingly used as part of marketing campaigns to engage customers in brands. Brand managers and business managers typically do not talk in terms of virtual users and transactions per second. For example, PepsiCo's brand manager for a Mountain Dew a...
Mitigations
Calibration testing focuses on throughput measured from the client (load-generation) equipment. Monitoring resource usage—including CPU, network, and memory—on both the client and server during a calibration test can help identify and diagnose performance issu...
SQL Testing with AIQ
SQL Testing with AIQ Use SQL testing in AIQ when a scenario must validate database state, prepare controlled test data, or confirm that an application workflow created the expected records. Keep these tests focused on non-production data unless the activity ha...
How to Create a Valid SQL Script
To create a valid SQL script in Appvance AIQ, you must configure the database connection properties correctly. These properties are based on Hibernate and are used to map the database configuration and establish a connection through the appropriate JDBC driver...
Setting up the Environment
Now let’s see how to create an SQL script using the required configuration settings. In this example, we use a MySQL database named appvancetest with a worker table containing the following columns: idworker name lastname The database can be hosted on a loca...
Creating a New Database Scenario
Once you have created a valid SQL script, you can create an AppVance Scenario to execute it using the Scenario Builder. This article assumes basic knowledge of AppVance Scenario Builder and focuses only on the configuration required to create a Database Scenar...
Reviewing SQL Test Execution Results
This section explains how to review the results of a SQL test execution and how to customize the step names displayed in the execution results. In this example, the SQL test inserts a new record into the database and then retrieves the records using a SELECT ...
Sample SQL Scripts for AIQ Testing
Recommended guidance Sample SQL scripts should demonstrate safe, repeatable validation patterns for AIQ testing. Examples must avoid production data, destructive statements, and customer-specific credentials. Example hygiene Use placeholder connection values, ...
Reduce MySQL Results Database Storage Usage
Reduce MySQL Results Database Storage Usage Use this procedure when the AIQ results database is consuming excessive storage. Treat database cleanup as a controlled maintenance task because deleting execution data can permanently remove historical evidence and ...
SQL Testing Appendix for AIQ
Recommended guidance Use the SQL Testing appendix for supplemental reference material that supports active SQL testing workflows. Keep appendix content concise, current, and linked to the main SQL testing guidance. What belongs here Reference examples that are...
Operational Test Data with DPLs in AIQ
Recommended guidance Use DPLs to manage operational test data for Scenario Editor and Service Suite assets when tests need repeatable, controlled, or generated values. Treat DPLs as part of the test design, not as incidental data pasted into individual steps. ...
AIQ DPL Types
Recommended guidance DPLs provide operational test data for AIQ scenarios and services. Choose the DPL type based on data ownership, repeatability, volume, security, and whether values are static, generated, or retrieved from an external system. Common DPL con...
Configure AIQ DPLs
Recommended guidance Configure AIQ DPLs so scenarios and services receive the right data at the right time. DPL configuration should define source, format, ownership, lifecycle, reset behavior, and security boundaries. Configuration checklist Choose the correc...
Providing Data to Distributed Tests
AIQ is a distributed test system. Multiple virtual users run in a TestNode and tests run across one or more TestNodes. Tests often need unique data for each virtual user. For example, a test of a banking system needs a separate and unique customer number for e...