#qa practices

There are many organizations that use Quality Assurance(QA) practices to improve the quality of their systems. These practices help in the long run, to increase the quality of the system and will eventually lead to lower improvements and higher profitability. The major issue is that they may be wasting too much time in finding out trivial bugs and issues that will never happen in the real world. According to the World Quality Report,  a QA is increasingly seen as a key to driving business outcomes.

Quality Assurance in production is a set of emerging DevOps techniques that generally focuses on fostering a keen awareness of what the actual issues are in production. These practices complement the traditional pre production QA practices by providing fast feedback and many vital diagnostic data. Some organizations may find the idea of adopting production QA practices risky or intimidating, but doing so can have a positive impact on a business's bottom line. 

Here are a few steps we can take to manage better QA practices:

1. Alert on unexpected scenarios

All the software teams spend time worrying about unexpected issues. For example, what if the data expected is not actual and accurate? What if the value we get is null? What will happen if the user will get confused with the workflow? 

Such uncertainty is a natural part of software development, given how unpredictable our real users, networks, devices, and all the other systems are. The main problem is that this uncertainty costs money. The System analysts agonize for days over the potential issues. The Developers spend hours in writing and discussing codes to deal with every single corner case. The future developers who are appointed to that system spend extra time maintaining these additional lines of code. Often, such codes can affect the design of a codebase, leading to unnecessary abstraction or complicated code.

We can have an alternative approach by getting the system to let us know that something happened. The simplest and easiest way to do this is to add an error entry to log the issues. When any error will actually happen in production, we can analyze the impact and the frequency of the issue and decide whether it's worth the cost of addressing. Logs are an important way to get all the information stored. That will help the team know how to respond as quickly when any scenario has occurred.

2. Keeping an audit log

Now a days, data storage is really cheap. This is a big advantage to storing all the production-related information and important metadata about what happens on the system. 

We can consider an example: 

An Invoice payment system. There will be several steps during a course of getting the invoice paid. At first, the invoice is loaded into the system. Then, a number of people may need to approve the payment. After that, the invoice needs to be scheduled for payment, paid and marked fulfilled. These processes will often end up being more complex and something or the other may become faulty during the implementation of the entire workflow.

So whenever any such major blunder occurs, a large number of developers spend many hours to figure out the issue, to understand how the issue occurred and its root cause. QAs spend the time helping imagine what scenario may have occurred at the user end for the issue to arise.

Instead, we can have an information recorder in our metadata and the team will be able to see that the payment was scheduled but how the payment never took place. The pinpoint complexities which are actually difficult to determine while testing can be easily tracked when the issue appears if we have a proper audit log. The sooner the bug gets identified, the sooner the issues get fixed with minimal effort and low cost of maintenance.

3. Spending fewer times on worthless tests

Automated tests are very important in debugging and running a perfect cycle of workflow. But the tests do not always earn their keep. If the tests are slowing down, we have to set up the right production monitoring to understand when things go wrong. In that way, we can be alerted about the many false positives, and also we can know if any issue is worth addressing. Our overall purpose is to spend less time on tests that aren't really valuable and increase our team's awareness of what actually happens in the production.

Conclusion

There must be a time to build a safety parameter. Using techniques to free the development team from anxiety that occurs because of the uncertainty. The ultimate huge savings in the time when developers need to spend worrying about writing codes and supporting the approaches to the issues that many never happen. Critically, when less time is spent on the non-important issues, less money is wanted and new features are planned. It is a basic and well-said idea in the software field that "80% of the issues emerge from 20% of the entire system."