View from India: Self healing automation is low on maintenance
In IT, self-healing automation seems like a Utopian situation where devices detect faulty operations and make the necessary changes on their own. An ecosystem is essential to make this auto-correction a reality.
Self-healing automation can be understood as a low maintenance option particularly required as systems are prone to environmental failures. It is important because fixing an IT related problem is far from easy. At times the cost of servicing is more expensive than the actual product itself. The very nature of servicing is so complex and time consuming that it can hamper the production and operations in small and big organisations across verticals.
Consequently, there’s a felt need for the system to detect its failures and iron out the creases on its own without human intervention. Technically this can be understood as network self-healing. The process of self-healing automation is facilitated by automation within automation, and artificial intelligence (AI) within automation.
“Systems may not be prepared for unexpected network outrages. Hence an ecosystem is required to check the application on the server and ensure that all the stages in the workflow are running smoothly,” said Arup Datta, principal engineer, Swiggy, addressing the gathering at the STeP-IN Summit 2018, which marks the 15th international conference on software testing.
Wherever there’s a lapse in maintenance, security or system malfunctioning, the device sends out an alert resulting in self-healing. It’s an in-device monitoring technology with less downtime. As a proactive technology, self-healing automation can foresee what’s going to happen. It is a game changer.
On the one hand, a market is being created for self-healing automaton tools. On the other, testing has been established as a business service with a thrust on monitoring and analysing potential risks. Certain procedures that align with the production cycle need to be reexamined. “
When we look at productivity, issues that pose a problem include meetings, reports and documentation and an end-to-end testing in an integration environment. Other aspects relate to the many stages of regression cycle that range from pre production to post production,” observed Mohanbabu Nellore, Director, Visa Inc.
If these issues are resolved, then test engineering in the production line can be scaled up. From the employee standpoint, it will result in employee satisfaction and from the organisation point of view it gives enough time for new learnings and innovation.
AI is a value-add to the testing process, as it helps solve a problem the way the world can use it. Solutions are built with AI. So, testing becomes feasible and scalable in customer-centric companies across geographies and locations, and is also applicable in umbrella brands that offer a suite of business services, like in the case of Amazon. This is essential because testing happens across a diverse section of verticals ranging from retail to fintech, along with hardware and mobile devices.
“If you want to test the app performance, then build tools which can take screen shots of the Android for highlighting the defects,” suggested Pradeep Soundararajan, co-founder at Appachhi and founder at Moolya.
Testing calls for an out-of-box thinking approach for different segments. Take the case of fitness bands, which is considered most popular among all health wearables. The bands have been tested by CSS Corp Limited, a new age IT services and technology support company.
“Our intention was to validate testing independently and it’s a challenge to test fitness bands because it’s a product and not software,” revealed Dr Kiran Marri, vice president, Digital Engineering Services and James Mathew, senior consultant, Digital Engineering Services, CSS Corp Limited. A prototype model was built, simulated and tested and the methodology was driven by hypothesis, server motors, sensors and accelerometers, static cameras and videos to track user activity.
“Our study of fitness bands revealed that the principles of testing can be enhanced using analytics, Internet of Things (IoT) imaging and automation. The approach can be applied to validate other variables in medical research and sports,” they added.
Let’s hope that system-related problems are solved as testing unleashes creative ideas and self-healing automation leads us on to a Utopian scenario.