If you’re practicing agile development without QA team members, a reasonably defined testing process, and sufficient criteria to help define “done”, then at some point your development process will go off the cliff of complexity.

That’s right. No QA, off the cliff you go without a parachute.

The size of your development team, the number of technologies used in the development stack, and the business criticality of the applications are all quality criticality indicators. They shape how much runway IT has before quality factors drive material business risk that can easily overwhelm the IT development and operations teams.

Even if you’re a solo citizen developer on a low code platform, at some point you’re going to make application changes where having defined test plans help avoid issues that might impact users, customers, data quality, security or performance. In larger scale applications, performance testing is not something you can do on demand because the first load always fails and valid testing practices need to be implemented as part of the agile development process.

Why a QA Practice Is Critical to Long Term Success

• • More functionality, more testing – As applications are developed with more features and capabilities more functions need testing. Every agile sprint increases the testing landscape, and if the discipline to define test cases and establish regression tests isn’t developed in parallel, the backlog to develop them becomes too hard and long to execute on afterward. If a development team is adding functions and then breaking others, it’s likely because there isn’t regression testing in place to catch these issues.

• • Applications are more complex involving multi-tier architectures, multiple databases, transactions spanning multiple APIs, and computing performed on multi-zone cloud environments. If you aren’t building unit performance tests along the way then identifying a bottleneck can be a lengthy, painful process when it emerges.

• • Data and Analytics Testing – The application is working, but the data is wrong. Many applications today are data driven enabling their users – internal or external to make better data driven decisions. Application testing isn’t sufficient because if the data is wrong, the entire value to the end user is compromised. But testing data, validating calculations, understanding boundary conditions, and insuring aggregations or statistic calculations are valid is really really hard without a defined test strategy.

• • Security Testing – A failed application security test may be costly to fix. Worse is a security failure in production that could have been avoided with security practices entrenched into the development practice. If you’re not testing for security issues, then it’s unlikely the development team is applying basic security design principles into developed applications.

• Multiple devices, browsers – Finally, today’s user experiences span phones, tablets, laptops, IoT devices with different browsers and plugins. Insuring that user interfaces are functioning and that the user experience is optimized across all these modalities has never been easy, however, customers have minimal patience for mediocre or clumsy experiences.