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YotaScale 2019 Predictions: Cloud Wars, Cloud Culture and AI Disruption

Industry executives and experts share their predictions for 2019.  Read them in this 11th annual series exclusive.

Contributed by Asim Razzaq, CEO of YotaScale

Cloud Wars, Cloud Culture and AI Disruption: YotaScale's 2019 Technology Predictions

YotaScale delivers Autonomous Cloud Operations with a platform that provides intelligent, actionable insights to cloud operations, allowing teams to take ever-changing application needs into account and optimize the infrastructure to meet business needs.

My 2019 technology predictions are as follows:

AWS Wins the Cloud Wars; Microsoft Doubles Down on Kubernetes

The cloud wars have already been won by AWS, and Microsoft and Google will fight for second place. A shift to "cloud native" and Kubernetes adoption will result in more instances of multi-cloud and hybrid cloud -- and will help level the playing field among the three. Interestingly enough, Azure is doubling down on Kubernetes, even more so than Google itself, and this trend will continue in 2019. Kubernetes, born out of Google, has become the de-facto containers orchestration tool, and it is Microsoft that is capitalizing on its growth.

When it comes to choosing the right cloud to use, cloud DNA will be an important factor. Google has a DNA of machine learning and analytics, AWS is aligned with efficiencies and supply chain expertise, and Microsoft for being tied so closely to enterprise organizations.  Each one of these cloud providers has a specialty, and engineering and DevOps teams will pick and choose the "right" cloud based on these differentiated capabilities.

Rise of the Machine Learning Engineer

As AI continues to disrupt industries that have been static for 50 years, we will see a critical need for data experts who can understand and apply data in a meaningful way -- specifically to machine learning models. This will lead to a data scientist skill-set shortage. Overall demand for data scientists is growing, yet many organizations are having a difficult time finding enough qualified candidates  - much like the Java Programmer of the early 2000s. As a result, today's organizations will look inside and start training their engineers on data science and machine learning. Call it the 2019 "Rise of the Machine Learning Engineer."

Data science is not a unicorn-like, mysterious field of study. Engineers can learn standard technology skills and apply them to machine learning. Specialized training and boot camps can deliver proficiency within a week, as it's less about formal training and more about applying skills to a specific domain or use case. The machine learning engineer is the master classman when it comes to specialized techniques, supervised learning and domain expertise. This expert will apply his/her training to analyze, understand and apply data in meaningful ways, fulfilling many of the actual duties of a data scientist.

The Cloud Migration Culture Shift

One common mistake organizations need to correct in 2019 is how they plan and execute their move to the public cloud. Most see it as a technology issue instead of a business issue. The move to the cloud is more than a technology shift; it's similar to change management, involving a company culture and mindset shift. The move to the cloud should not be taking a 10-year-old ERP system and modernizing it. What it should involve is clearly articulating the business reasons for shifting to the cloud. Focus on the culture of the organization. Retire that ERP system and start net-new with another application in the cloud instead. Also, bring in new talent and people who have made this transition. This is the complete cultural change that must take place within an organization before the company can properly transition mission critical apps to the cloud.


About the Author


Asim Razzaq is an entrepreneur and technology executive with a proven track record of building and managing high performing local and global teams that develop cloud-scale applications and platforms. Prior to YotaScale, he held senior positions at eBay and PayPal where he built the first global payments developer platform in just 2 years (processes over $1B in payments annually).

Published Thursday, January 10, 2019 7:35 AM by David Marshall
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