To Deploy or Not-to-Deploy - decide using TTA's Trend & Failure AnalysisAnand Bagmar
schedule 2 years agoSold Out!
The key objectives of organizations is to provide / derive value from the products / services they offer. To achieve this, they need to be able to deliver their offerings in the quickest time possible, and of good quality!
In order for these organizations to to understand the quality / health of their products at a quick glance, typically a team of people scramble to collate and collect the information manually needed to get a sense of quality about the products they support. All this is done manually.
So in the fast moving environment, where CI (Continuous Integration) and CD (Continuous Delivery) are now a necessity and not a luxury, how can teams take decisions if the product is ready to be deployed to the next environment or not?
Test Automation across all layers of the Test Pyramid is one of the first building blocks to ensure the team gets quick feedback into the health of the product-under-test.
The next set of questions are:
• How can you collate this information in a meaningful fashion to determine - yes, my code is ready to be promoted from one environment to the next?
• How can you know if the product is ready to go 'live'?
• What is the health of you product portfolio at any point in time?
• Can you identify patterns and do quick analysis of the test results to help in root-cause-analysis for issues that have happened over a period of time in making better decisions to better the quality of your product(s)?
The current set of tools are limited and fail to give the holistic picture of quality and health, across the life-cycle of the products.
The solution - TTA - Test Trend Analyzer
TTA is an open source product that becomes the source of information to give you real-time and visual insights into the health of the product portfolio using the Test Automation results, in form of Trends, Comparative Analysis, Failure Analysis and Functional Performance Benchmarking. This allows teams to take decisions on the product deployment to the next level using actual data points, instead of 'gut-feel' based decisions.