Massively parallel big data platforms are quickly becoming the industry standard for organizations looking to extract greater value from data. As architectures have shifted, application development paradigms have also changed to reflect growing needs for agility, scale, robustness, efficiency, and ease of collaboration on these new platforms.
Companies like Ericsson and Uber are touting the advantages they have realized by implementing microservices applications, including:
Crystal Valentine draws on lessons learned from companies like Uber and Ericsson to outline the key principles to developing a microservices application. Along the way, Crystal describes how certain next-gen application areas—such as machine learning—are particularly well suited to implementation in a microservices architecture rather than a legacy application paradigm.
This session is sponsored by MapR.
Crystal Valentine is the vice president of technology strategy at MapR Technologies. She has nearly two decades’ experience in big data research and practice. Previously, Crystal was a consultant at Ab Initio, where she worked with Fortune 500 companies to design and implement high-throughput, mission-critical applications and with equity investors as a technical expert on competing technologies and market trends. She was also a tenure-track professor in the Department of Computer Science at Amherst College. She is the author of several academic publications in the areas of algorithms, high-performance computing, and computational biology and holds a patent for extreme virtual memory. Crystal was a Fulbright Scholar in Italy and holds a PhD in computer science from Brown University as well as a bachelor’s degree from Amherst College.
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