Hybrid Cloud

IBM Research virtual roundtable reveals AI’s role in hybrid cloud

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A recent IBM-hosted virtual roundtable, “Talking in Code: The New Frontier for AI and Hybrid Cloud,” brought together researchers from IBM, Columbia University and North Carolina State University to discuss how AI can simplify and streamline hybrid cloud environments as well as make them more secure for mission-critical workloads. The panel also addressed key business concerns about AI’s potential to undermine demand for IT and developer talent.

“AI is already being applied to key areas of IT, such as chatbots that provide technical support for a range of products,” said panelist Nick Fuller, Director of Hybrid Cloud Services at IBM Research.

“When you look at what’s critical for enterprises going forward, it’s the ability to use AI to unlock the value of hybrid cloud for their mission-critical workloads,” he said. “That’s an area of pursuit for us that drives tremendous excitement all the way up to our CEO.”

McKinsey & Company has estimated hybrid cloud and multi-cloud will be a $1.2 trillion market opportunity by 2022, comprised of hardware, cloud infrastructure, software and consulting and management services.

As companies’ reliance on disparate public clouds has grown over the past decade, these businesses are now seeing the need to integrate those clouds into a hybrid environment in order to better meet business objectives. Companies, particularly those in highly regulated industries such as financial services, telecommunications and healthcare, are looking for a smart, secure way to do that. With only 20 percent of all workloads currently running in the cloud, AI-infused automation is crucial to moving large amounts of those remaining workloads.

Automating the Hybrid Cloud Journey

When embarking on this journey to hybrid cloud, companies must consider two very important technology components. The first is the AI-infused automation tooling required to take workloads through the various phases of application lifecycle management, according to Fuller. The second component is the hybrid platform, itself. Ultimately the tooling and platform are brought together through APIs, workflows and best practices to provide client value, he said.

Panel moderator Patrick Moorhead, founder of Moor Insights & Strategy, pointed out that, although legacy applications still serve important needs for many businesses, many will need to go through some sort of modernization process to function in containerized hybrid cloud environments. He agreed that AI has a critical role to play in that process.

“Over the past 50 years, AI has gone through different cycles, but today there are real companies doing real work in this space.” — Patrick Moorhead, Founder, Moor Insights & Strategy

Modernizing legacy applications involves more than the use of containers to turn those applications into microservices. Developers must also understand the business processes those applications are part of.

“How can you make sense of what’s going on in the code, if you don’t know where you are headed?” said panelist Munindar Singh, professor at North Carolina State University’s Department of Computer Science. “I think AI can apply in both of those aspects.” If AI can consider where code and the processes it supports fit together, it can help businesses “convert monolithic apps into elegant systems of microservices.”

App modernization is an example of a fundamental area of growth in computer science, where one examines source code and applies AI for code understanding, search, testing and verification, according to Fuller. IBM has fully embraced the demand for application modernization, launching its Accelerator for Application Modernization with AI in May to “provide a GPS for app modernization,” he said.

The Accelerator for Application Modernization is a suite of tools designed to help clients reduce the overall effort and costs associated with application modernization for a variety of programming languages. The accelerator leverages continuous learning and interpretable AI models to adapt to a client’s preferred software engineering practices and stays up-to-date with the evolution of technology and platforms.

AI’s Role in Hybrid Cloud Security

The panelists also agreed that security is another important area where AI is being applied to hybrid cloud.

AI’s role in security is two-fold, said panelist Baishakhi Ray, assistant professor and head of Columbia University’s ARiSE Lab. “First when we think about traditional, legacy apps, there are usually repeated patterns in the way hackers attack your software,” she said. “We can now use AI to identify these patterns. We’re also building models to automatically identify areas prone to attacks. So far the results look very promising.”

“Security and compliance concerns for enterprises only go up when they look at cloud,” Fuller said. “Clearly, what happens at build time is crucial. But once actually deployed there are concerns as well.” As an example, Fuller cited IBM’s 2019 Cost of a Data Breach Study, which found the cost of a breach averages $3.86 million. The 11 incidents of cloud misconfiguration the study analyzed cost organizations upward of a combined $57 billion.

IBM has implemented various AI and machine-learning models for determining the degree to which a vulnerability can be weaponized, the skill level required by an attacker to weaponize said vulnerability and the extent to which non-compliance of various business required regulations present an issue, according to Fuller.

“When you have hackers using machine learning, really the only thing you can do is have machine learning on the other side, reacting to those attacks,” Moorhead observed.

AI Will Augment App Developers

The panelists wrapped up their discussion on topic of how AI will impact the people currently doing the work to modernize applications into microservices and create secure hybrid cloud environments. “Some people are concerned that, with AI, there’s a replacement of the practitioner, but that couldn’t be further from the truth,” Fuller said.

The relationship between developers and AI will be one of augmentation, the panelists agreed. In the case of application modernization, for example, the application architect will be needed to potentially customize the modernization process, address gaps revealed during the automated generation of the refactored application and validate application functionality for mission critical applications, according to Fuller. “AI should elevate the role of the practitioner, eliminating the need to focus on manual tasks, whether that be in the modernization space, security and compliance or AIOps management and support,” he said.

What This Means for CIOs

When asked by Moorhead what all of this means for CIOs, Singh summed it up by saying that a CIO’s purpose is to facilitate business. “A lot of the time, however, they end up contending with what seems like trivial concerns,” he said, adding that AI should help them automate less strategic functions and focus more on how they can improve business processes, ensure security and preserve privacy.

Fuller pointed out that such work is already moving beyond the research lab and into actual IT environments, where IBM is co-creating with its clients. “The idea is to pilot,” he said. In working closely with CIOs and their teams, IBM looks to ensure AI can effectively modernize apps and manage hybrid cloud environments at scale, he added.

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