For example, a feasibility concern for the chat app may be memory availability on the device that the chat app runs on.
A conversation can have an arbitrarily large number of messages. If we load all the messages into memory without pagination when the app first mounts, we will quickly run out of memory and the app will crash.
Practicality
Choosing to pursue a more technically complex and robust solution at a higher engineering cost is not always appropriate for a business that needs to be agile to test hypotheses and iterate quickly.
A social media platform like OkCupid operates in a very competitive landscape so there’s an urgency to launch quickly and iterate on experimental features in response to new market insights. A flexible architectural design that is easier and faster to implement but has more technical debt is often the right choice for OkCupid.
Another practicality constraint is the tolerance for risk which depends on the business case for the feature. For example, if the KPI is measured in the number of new user onboarding and conversion of these users to paid users, the business cost of shipping a broken onboarding flow or broken table-stakes feature like matching and chatting can be very high. In this case, it is better to trade off velocity for higher code quality.
Maintainability is a goal for any software engineering project. We want to make sure that the solution we implement is consistent with the existing patterns in the codebase and is easy to maintain.
A more technically complex solution may be more robust but it also introduces more risk of bugs and crashes. A more technically complex solution may also be more expensive to maintain and scale. Other Things We Want to Optimize for weiterlesen
