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Pivotal 2019 Predictions: The Year of Kubernetes, Serverless, and AI

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

Contributed by Frank McQuillan, Cornelia Davis and Mark Fisher, Pivotal

The Year of Kubernetes, Serverless, and AI

Companies today are under more pressure than ever before to deliver products and outcomes faster to their customers. Kubernetes, serverless and AI are three technologies poised to enable companies in 2019 to outpace their competitors and innovate at unprecedented speeds.

Applied Artificial Intelligence (AI) and Machine Learning (ML)

There is no shortage of hype about artificial intelligence, but we're still in the early stages of AI deployment in the enterprise. This is especially true when it comes to deep learning, barely 5 years into the current explosion. The AI realist, who should become more vocal in 2019, might ask: "That's an impressive demo of image recognition, but how does it translate into helping my business?" AI projects will require different implementations, different data (a lot of it), and different skill-sets for which companies will have to aggressively hire. Fortunately, help is coming in the form of better software products and services to make AI more accessible to the enterprise. One example is tooling for model management, where many of the same patterns from building and deploying complex applications and microservices apply. Startups in this area will continue to attract funding in 2019, as well as those applying AI to specific use cases within verticals.


Some would argue that Kubernetes has crossed the chasm, as evidenced by 8,000 people attending the final Kubecon of the year in Seattle in December. And while the conference saw a marked increase in presentations coming from users (rather than only from open source contributors and vendors), most of these still came from cloud-native companies-those that were born in the web era (say within the last 10 years). Most of the enthusiasm around Kubernetes is still coming from the developer-the consumer of Kubernetes. 2019 is the year that Kubernetes will cross the chasm in the traditional enterprise. Early adopters are seeing value coming from their use of Kubernetes and are beginning to speak publicly about it. And the people who provide infrastructure to those developers asking for Kubernetes are actively looking for ways to offer that service. Of course, security and compliance reign supreme in the enterprise; and Kubernetes has matured to the point where it is possible to meet these requirements, however, the level of complexity remains a challenge. 2019 will see emphasis placed on making Kubernetes more accessible to exponentially more consumers-this will truly enable the crossing of the chasm.


The terms "serverless" and "FaaS" (Functions-as-a-Service) are often used interchangeably. However, the characteristics of serverless are more generally beneficial, allowing developers to be more productive since they can focus on code that solves business problems rather than "server" concerns such as load-balancing and scaling deployments to zero and back. The specific benefit of a FaaS is that it narrows the developer focus to an even higher level of abstraction. When describing application frameworks, such as Spring, we refer to that as Inversion of Control: as the framework and/or platform takes control of more concerns, the developer has fewer responsibilities and thus more focus. It also means the platform can provide and patch even more of the stack, such as a security vulnerability in an application framework dependency. Five years ago at SpringOne 2013, Paul Maritz described IaaS as the new hardware and PaaS as the new OS. In 2019, we expect more developers to consider FaaS as the new application framework for those use cases where a single-responsibility event-driven function is a good fit, while still benefiting from "serverless" characteristics for their full-stack cloud-native applications, increasing developer productivity at any layer of abstraction.


About the Authors


Frank McQuillan is Director of Product Management at Pivotal, focusing on analytics and machine learning for large data sets. Prior to Pivotal, Frank has worked on projects in the areas of robotics, drones, flight simulation, and advertising technology. He holds a Masters degree from the University of Toronto and a Bachelor's degree from the University of Waterloo, both in Mechanical Engineering.


Cornelia Davis is a Senior Director of Technology for Pivotal, and was recognized as one of the "Top 10 Women in Cloud" by CloudNOW, a non-profit consortium of women in cloud computing. A teacher at heart, Cornelia has spent the last 25 making better software and better software developers. She leads Pivotal's engineering team tasked with exploring how far we can push the bleeding edge of cloud computing.


Mark Fisher is a Senior Staff Engineer at Pivotal. Mark has been a member of the Spring team for over nine years, contributing to the Spring Framework and several other Spring projects. He founded Spring Integration in 2007 and is the lead author of "Spring Integration in Action," published by Manning in 2012. Currently, he's at Pivotal where he co-leads the Spring XD project, where he focuses on runtime portability and everything related to the flow of data.

Published Tuesday, January 08, 2019 7:46 AM by David Marshall
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