Ride the DevOps wave!
DevOps has been around for a while and it is undoubtedly the direction the IT industry will evolve.
After transition to DevOps, Developers and Operations Engineers utilize the same ideology, practices, tools and frameworks, and, most importantly, they think in the same way. Unfortunately, most of enterprise businesses still follow the “if it works, do not change it” paradigm and lag to adapt to the rapidly changing business landscape. Here is why every business should ride the DevOps wave, lest being washed over by it.
Software-defined networking (SDN) is the part of the theoretical background to DevOps, stating that all software and resources should be developed in a way that ensures integrity of the network, so network operations are no longer separate from data processing and warehousing. According to the Infoholic Research report, the data network market will have CAGR 37% till 2022 and will produce $12 billion net profit in the U.S. alone, with nearly a half of it being delivered by software and services. The Internet of Things (IoT) will generate huge volumes of data legacy on-prem infrastructure was never expected to deal with.
This means timely adoption of the software-centered approach to development and maintenance is essential for staying on par with the other market players or gaining a competitive edge. Cloud migration is an essential part of digital transformation, which is undoubtedly the most important requirement in the dawn of the IoT age. Moving the enterprise infrastructure to the cloud and adopting multi-cloud strategy helps DevOps build IoT-ready flexible and resilient infrastructure with multi-zone backuping, self-healing mechanisms and rapid provisioning of new features or bugfixes.
DevOps is the future of IoT and Big Data
The Internet of Things, where many devices will be interconnected, will generate overwhelming volumes of unstructured data. Depending on where IoT apps are leveraged, this data might actually be disposable at some moment. For example, the data of some consumer goods package movement is essential for logistics and is of no commercial use to the manufacturer once the goods are successfully delivered to a local grocery. The same goes for distributed sensors in the Industry 4.0 factories – when all the sensors sense the same data, they can all considered being a single data entrance point. It is the abnormalities and transiting signals that are important in this case.
This brings us to the need of deploying machine learning (ML) algorithms to benefit the business. ML helps detect such abnormalities and react to them, to either deal with the problem quickly or take advantage of the possibilities the emerging pattern provides. Harnessing the ML power can help with many tasks — from Amazon’s famous recommendation engine (“the users that bought this have also searched for”) to personalize the purchases and all the way to using data mining and ML for fraud detection.
The point is quite simple, after all. Following the old ways is not enough, as the business has to evolve and adapt in order to survive, just like any live being. Adopting the DevOps ideology can help overcome multiple challenges and ensure your company is ready to embrace the risks and possibilities of the Big Data and Internet of Things era.
Ride the DevOps wave or risk being washed over by it!
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