Quality in the Time of DevOps
OK, so we have heard all these terms – software quality, DevOps, IoT Applications, and data. We know that DevOps is a significant movement. Its goal is to close out the gap between development and operation within the larger IT team. This is with a goal to release better applications faster. So far so good. And one more truth – quality cannot be left behind.
Quality will need to pedal in and become more agile in its behavior. This would mean that testing has to happen alongside development. This would mean ingraining an agile DNA in your overall application development mechanics. In industry terms, this entire movement is denoted as shift-left.
And, all of this transition to DevOps can be driven a lot better by changing the ‘human mindset.’ The mindset needs to be more agile, analytical, and automation focused on conducting tests quickly, measuring and monitoring the results and plugging-in changes fairly quickly with automated testing efforts.
The Confluence of DevOps and IoT at the Testing Center of Excellence
Now, let’s step outside the bounds of traditional applications to think IoT or Internet of Things applications. These applications have several new demands and new challenges.
The biggest being bringing ‘predictability’ in the overall experience of the application. And it crosses paths with DevOps to bring that ‘better experience’ of the application. And, this is not so easy to do with complex IoT applications which need to be hyper-connected, hyper-secure, and hyper-available.
Different factors need to ‘factor-in’ including capacity constraints as they deal with storage, and network bandwidth. Some consequences need to be accounted for. It is important to consider this because an underperforming application (or a not so thoroughly tested application) can cause damages unpredictably.
Consider an untested drone or a malfunctioning driverless car. And everything considered IoT is still an emerging field with lots of grounds which need to be learned. DevOps is a somewhat established a discipline that can be leveraged to pass this learning curve fairly quickly.
The Role of Data-Driven Intelligence and Quality Metrics –Understand Your IoT Application Performance in the Context of DevOps
Now to circumvent many of the constraints that IoT poses, DevOps principles help. But in the DevOps needs contribute to better run IoT applications. And that last mile is tying in the measurements, the analytics, and the intelligence from these applications to the DevOps ecosystem of this application.
This becomes the last mile that can make a huge difference. Hence, relaying the exact performance analytics from all of these applications will do the trick. It is not different from other test and performance analytics we have already mentioned.
But there are some very specific metrics around security of the IoT applications that needs to be carefully crafted. Also, because tacking its breach and impact drives a better analysis. Imagine if someone hacked into your Alexa and sent misleading information! DevOps also has to work with the IoT application module to establish a continuous delivery model for release and track the roadblocks real time to understand and correct instantly.
And you need deployment analytics. These applications have to live on a live platform and thrive on remote devices. But you also need intelligence around how the deployment infrastructure including firmware and other stuff is performing for that particular application.
We look forward to talking with you more about how our QMetry suite of products is making a dent to the DevOps and IoT application world with its suite of automation products and frameworks.