3 Ways to Customize DevOps

3 Ways to Customize DevOps


In 2019 and beyond, DevOps will be increasingly customizable


An increased fine-tuning of DevOps will take place in 2019 and the years ahead, according to tech strategists at a recent DevOps expo.  Sufficient points of evidence on DevOps implementations substantiate a viable approach to achieving competitive advantages in the marketplace.

Here are the innovative ways that govern how DevOps will be fine-tuned in the future:


#1: Cloud and Containers


Making life easier for the end-user begins with the developers in software delivery. By focusing on cloud and container based solutions from the testing phase to production, developers can make room for increased self-service, which is very popular among end-users.  The need for an elaborate script detailing various tasks, to-do lists, and models describing work processes are a thing of the past. Ultimately, with the introduction of self-service capabilities, these preliminary efforts should be curtailed or eliminated entirely. When trying to build a Kubernetes pipeline for instance, commands such as “get entire data set” should be available so as to ensure faster operations for teams in the workplace and beyond.


#2: Machine Learning and Artificial Intelligence


We can expect to see an increase in machine learning and artificial intelligence integration in tech trends for 2019. According to a DevOps strategist and expert, emerging DevOps operating systems merge concepts involving artificial intelligence and machine learning. The focus predominately relies on next-level  predictive analytics, with efforts resulting in the production of authentic, valuable business deliverables.  What’s more, a focus on the best application of both Machine learning and artificial intelligence will become hot items this year.


Ultimately, machine learning and artificial intelligence will promote efficiency throughout every phase within the DevOps lifecycle. One may ask, could tasks be done faster? What are methods to reduce the cycle time in a pipeline, from inception to production? Now, assuming the pipeline lasts two days, if competitors offer same-day processing, you can see the difference in competitive advantage. Harnessing Machine Learning and AI will help curb the competition, by completing this process in just one single day or less, other than the typical two days.


#3: DevOps Security


Prioritizing security when it comes to DevOps is a trend we will definitely see gaining traction in 2019. The buzzword “DevSecOps” (Dev Security Ops) may become a household term in the coming years. The time is nigh to stop the practice of adopting vulnerable frameworks susceptible to attack. Security integration will become part of the lifecycle upon inception, rather than an afterthought – as DevSecOps sees it’s way into the pipeline upon the beginning of development. Prior to the production phase, security teams should reinforce efforts in checking and validating code to maximize safety and prevent problematic encounters.



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