Reduce Testing Automation Time for a Large Telecom OEM
Business Challenge
Despite the automation of 50K test cases for one of the optical switch products, the customer was not able to release the product to production before 3 weeks. This delay was due to the time taken for manual verification of 2GB worth of Test Case / Application Logs / System Logs, Database, and Protocol logs. Time to market was critical and they needed an accelerated timeline.
- Infinite’s team proposed use of AlOps technology to reduce the test result validation effort.
- Our data science experts and test SMEs collaborated to develop an intelligence module that will predict the pass/ fail of test runs based on. runs based on.
- Infinite’s AlOps solution based on Azure Machine Learning developed Al model using past test results/system logs/ database/protocol logs.
- The trained-tested model was integrated with the existing automation module in the Cl/CD pipeline and the test result is generated immediately after the automation run.
- Only those test cases that passed/failed with low percentage accuracy are manually verified.
- Infinite’s AlOps solution was able to reduce QA release time from weeks to days.
- With continuous training the percentage accuracy increased 15%-20% in 6 months.
