March 16, 2020 | Written by: IBM Research Editorial Staff
Categorized: Hybrid Cloud
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Talk to hybrid cloud researchers at IBM, and the conversations soon swing to AI, cryptography and loads of enabling technologies. It’s clear that cloud computing can’t be considered a single discipline, because clouds encompass virtually all the technologies—and the associated challenges—of computing itself.
The three women featured here represent the tremendous breadth of expertise, and the depth of research, that goes into building this next generation of computing. The cloud systems they are developing are destined not only to process, manage and optimize the operations of companies around the world, but also to advance research and discovery.
Shielding Secrets in the Cloud
Dalit Naor, Hybrid cloud department manager, IBM Research
One of the enduring challenges in the data economy, says Dalit Naor, is to engineer systems that provide openness and control at the same time. Analysts require mountains of data to perform analytics such as optimize harvests, spot and predict engine failures or provide customers with crucial components just in time, for example. The trick is to provide only the necessary data while shielding other information such as confidential parts, like people’s medical records or a company’s acquisition strategy. “We have to develop different permissions for different uses of the data,” says Naor, who leads the hybrid cloud department at IBM Research in Haifa, Israel.
Her work involves sorting out immense complexity. One of the great strengths of cloud computing, after all, is not only secure and reliable data storage in the cloud, but the ability to extract value and insights from that data. To accomplish this, researchers in Naor’s team create encryption technologies and vast architectures of rules and permissions, so that different entities can access only the encrypted data when they need it. “We encrypt it in a way that people can do analytics while decrypting only the necessary parts and only during the computation,” she says.
Naor, a 20-year veteran at IBM Research, came upon the challenges of data management early in her career. With a newly minted Ph.D. in computer science from the University of California-Davis, she plunged into human genome research at Stanford University. At that point, in the 1990s, the challenge was to decode the three billion base pairs in human DNA.
These days, much of Naor’s research is concentrated on building platforms for data analytics while protecting sensitive data, from businesses’ financial and trade secrets to the privacy of individuals—their banking details, geographic location and medical records.
In addition to cloud data platforms, Naor and her global team also focus on the reliability and resilience of hybrid clouds. “This infrastructure is extremely important, because everything else runs on top of it,” she says. IBM researchers are developing AI to spot anomalies in the flows of data and to issue alerts, so that people operating the cloud—or the system itself—can tend to a problem before it surfaces.
Naor was born in Israel and studied at the Israel Institute of Technology—the Technion—in Haifa, before moving to California for her graduate studies. She lives with her husband and three children in Tel Aviv, and shuttles up and down Israel’s coast, between the labs in Tel Aviv and Haifa. “I know that highway very well,” she says.
Modernizing Apps for the Cloud using AI
Research Manager, Principal RSM, Member IBM Academy of Technology & Master Inventor, IBM Research
Maja Vukovic knows that if businesses want to successfully modernize their applications from legacy environments to the cloud, they first have to understand what they are modernizing. Complex legacy applications are often mission critical, have millions of lines of code and were written dozens of years ago, which means their original developers and documentation might not be available to provide guidance. Vukovic and her team specialize in the use of AI to understand the core business functions of those applications and extract those functions into microservices that can be deployed in increasingly popular hybrid cloud environments.
“My primary focus is using AI to accelerate application modernization,” says Vukovic, Principal Research Staff Member and Research Manager for Hybrid Cloud Research at the T.J. Watson Research Center in Yorktown Heights.
Vukovic began her career at IBM in 2003 as a pre-doctoral researcher for IBM Research—Zurich. “I was interested in IBM Research because it is a leading industrial research organization,” she says. That appealed to her desire to connect high-level innovation and research with real-world problems.
She now manages teams responsible for researching application modernization and AIOps, software designed to combine artificial intelligence with IT management tasks. “It’s about being able to understand the behavior of legacy applications,” says Vukovic, who holds 112 patents, with about 100 more pending. “I’m responsible for the technical strategy for application modernization.”
Typically, someone goes through code manually to figure out what it does and how to modernize it. “We’re looking to AI to accelerate the process of understanding what a client’s application portfolio looks like, and to help them decide how to modernize it and deploy in the cloud,” Vukovic says. That process cannot be fully automated using AI, at least not yet. “This is one of the most sought-after challenges in terms of AI and how it applies to the cloud,” she adds.
Vukovic was born in the former Yugoslavia and earned her undergraduate degree in computer science and mathematics at the University of Auckland in New Zealand. Her next stop was International University in Germany, where she received her master’s in computer science, before she was off to pursue a Ph.D. at the University of Cambridge in England. Her doctoral research focused on context-aware service composition using AI planning. Context-aware applications respond and adapt to changes in their computing environment, such as when the location of the user or the capabilities of the device change. “I was interested in exploring how technology can infer what a human wants to do and react to that,” she says.
That research has strong connections with her current application modernization work. “In hybrid cloud environments, you’re trying to understand a user’s intent, so the systems you create can adapt and fulfill those requirements,” Vukovic says.
She credits a series of mentors, not all of them women, with helping her succeed at IBM Research. Those positive experiences led her to help organize the events at Watson Women’s Network in Yorktown, which offers a venue for women researchers to meet. Vukovic also mentors female students at local high schools. “One way to get them interested in technology and science is by talking about my career and what I do at IBM Research,” she says.
Cutting through Hybrid Cloud Complexity
Priya Nagpurkar, director, hybrid cloud platform, IBM Research
Despite the emergence of Kubernetes and other technologies meant to ease cloud-based development, it can still be very difficult to program in hybrid cloud environments. It’s Priya Nagpurkar’s job to help change that, and she has her work cut out for her.
“Kubernetes skills are sparse,” says Nagpurkar, Director of Cloud Platform Research at IBM’s T.J. Watson Research Center. “You need to be a distributed systems expert to do this properly today, and that’s not good for helping the cloud evolve.”
Nagpurkar’s team is working to address that, having developed a number of cloud development and management technologies over the past few years. For example, they contributed to the creation of Istio, an open technology helping developers connect, manage and secure networks of different microservices, regardless of platform, source or vendor. More recently, her team introduced SolSA (Solution Service Architecture), a programming model for hybrid clouds, kui, a modern terminal to enhance CLI interactions, and iter8, a set of AI driven tools to automate DevOps and SRE tasks.
“The changing nature of the cloud means research needs to continue—in security, in virtualization, in programmability,” Nagpurkar says. “Cloud still hasn’t reached the level of productivity that we have on mainframes and PCs. Our goal is to give the platform richer capabilities.” That includes building app-centric, developer-centric systems that simplify management and enable programmers to more easily build event-driven applications that can, for example, trigger an AI response to a sensor at the network’s edge. In the oil exploration industry, this could mean adjusting something in the operational environment in response to a low pressure reading.
Nagpurkar’s original career ambition had been to study what lies well beyond the clouds, as an astrophysicist or astronomer. By 2000, however, she could see that most of the jobs available in her native Pune, India, were in professions related to computer science. “My father was an electronics engineer and always tinkering with stuff,” she says. “That’s how I learned that a computer isn’t just a box to play games on. I began studying computer programming and started thinking in terms of how the technology could be improved.”
In 2007, Nagpurkar received her Ph.D. in computer science from the University of California, Santa Barbara. She felt that her options were either to continue in academia or to join an industry lab. “I saw IBM as a place where the best Ph.Ds. get to work,” she adds.
Nagpurkar spent her first six years at IBM with the Power Systems Research group, before joining the Cloud Research group in 2014. “At the time, Netflix, which had special open source software for building on the cloud, was top of mind,” she says. “That influenced my thinking about opportunities for IBM in the cloud. We had to think about what it means to write applications and run workloads in multicloud and hybrid cloud environments.”
As the mother of 4 and 7-year-old daughters, Nagpurkar often thinks about better ways to encourage girls to pursue careers that will help them tackle the challenges that industry and society face. “Unfortunately,” she says, “the ball gets dropped very early in terms of keeping girls interested in science and technology.”
This post is presented by The Watson Women’s Network, a community of technical staff, primarily based at the T.J. Watson Research Center, that seeks to encourage a workplace environment that advances the professional effectiveness, individual growth, recognition, and advancement of all women at IBM Research. The WWN partners with senior management, human resources and other diversity network groups to promote programs in mentoring, networking, diversity, knowledge sharing and recruiting.