![]() You can find the code in the Github repo. The FaceTec Postman Tests are configured to read these larger data files via. Step 3- Collection runner has a lot of important parts to consider for load testing. The FaceTec Test Data contains FaceScans, FaceMaps, Audit Trail Images, and more. Collection runner is the part which is used for sort of Load testing. There are two different ways to create test artifacts for release pipeline a. You can easily simulate large amounts of data to assess how an application behaves. For instance, Apache JMeter is an open source solution that enables you to make HTTP requests to a given endpoint and measure the response time, error rates, and other data from responses. Create test artifacts Test artifacts are the Postman scripts which needs to be execute. There are many different tools that you can use to load test APIs. Step 2- Then click on the Run button to launch Collection runner. Configuring pipeline will be divided to 3 main steps: Create test artifacts Run postman scripts Generate report 01. ![]() Const path = require ( ' path ' ) const async = require ( ' async ' ) const newman = require ( ' newman ' ) const PARALLEL_RUN_COUNT = 2 const parametersForTestRun = ) Īnd here you can play around with your api and build some stress tests to see how it handles the pressure. Step 1- Click on the little arrow along with your collection in the collection listing.
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