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Tens thousands of customers, a few millions of users, frequent deployments and immediate feedback about bugs. This is how I would shortly describe the context of deploying JIRA Cloud releases. In Spartez, based on our partnership with Atlassian, not only we take part in the process of developing new functionalities but also we take care of the quality of JIRA Cloud releases. It is not difficult to notice that taking into account above mentioned context measuring the quality of our product is a challenge. How to manage thousands of customer tickets a year? How to handle the fact that in case of Cloud solutions we are service providers and not only product providers? How to automate the process of measuring quality at least partially? These are the kind of challenges we as Quality Assistance Engineers have to face.
During the presentation I will answer the above questions. I will present our approach to measuring quality, its advantages and disadvantages, data and experiences. I will also go beyond the specifics of our product and process. Measuring quality of any product is difficult. Very often either we give up getting valid data completely or we have metrics in which no one believes. What is even worse, sometimes although we have proper data we do not use them to improve our process and product. In the presentation I will describe our best practices to get valid measurements and how we use this information to avoid defects in the future.