Bruce Davie (VMware)

Talk: Networking and Security in a Multi-Cloud World

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Abstract

Public clouds today may appear to be the default choice for deployment of new applications, but most enterprises have a range of applications that may not readily migrate to the cloud. Some “legacy” applications require low-level network services or specific hardware that may be unavailable in the cloud. Concerns around security, cost control, or data sovereignty also affect the willingness to move applications to public clouds. Furthermore, all clouds are not equivalent - the services provided by various clouds differ widely. For these reasons, many enterprises expect to have workloads deployed across multiple clouds as well as in their own private data centers for the foreseeable future. This raises challenges for both developers and security teams. For example, if a web front end running in a public cloud needs to connect to an on-premises database, how does the security team ensure the security of the database while allowing developers access from the front-end application? This talk will lay out the case for a consistent approach to networking and security in these multi-cloud environments and discuss some ways in which software-defined networking and network virtualization may be applied to the problem.

Bio

Bruce Davie is CTO for Networking at VMware, and a Principal Engineer in the Networking and Security BU. He joined VMware as part of the Nicira acquisition, and focuses on network virtualization. He has over 25 years of networking industry experience, and was a Cisco Fellow prior to joining Nicira. At Cisco, he worked closely with leading service providers to enhance the capabilities of their networks. He led the team that developed multi-protocol label switching (MPLS) and contributed to the standards on IP quality of service. He has written over a dozen Internet RFCs and several networking textbooks. Bruce received his Ph. D. in computer science from the University of Edinburgh in 1988 and is an ACM Fellow.

Luiz Andre Barroso (Google)

Talk: Programming a Warehouse-scale Computer

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Abstract

Public clouds are quickly making massive-scale computing capabilities available to an ever larger population of programmers, and are no longer a playground restricted to a handful of institutions, such as national labs or large Internet services companies. In this talk, we will highlight some of the features of this new class of computers, the challenges faced by their programmers, and some of the techniques that we have developed to address those challenges.

Bio

I am a Google Fellow, and the VP of Engineering for the Geo Platform team, the group responsible for collecting and curating maps, local and imagery data that powers our consumer products (such as Google Search and Google Maps). My technical interests that range from distributed systems software to the design of Google's computing platform. While at Google I have co-authored some well-cited articles on warehouse-scale computing, energy proportionality and storage system reliability. I also co-wrote "The Datacenter as a Computer", the first textbook to describe the architecture of warehouse-scale computing systems, now in its 2nd edition. I was previously a member of the research staff at Digital Equipment Corporation and Compaq, where our group did some of the pioneering research on modern multi-core architectures. Some of those multi-core processors also use variants of the ring-based cache-coherency interconnects that were the subject of my doctoral research.

I am a Fellow of the Association for Computing Machinery (ACM) and the American Association for the Advancement of Science. I was the program chair of ACM ISCA'09, a keynote speaker at FCRC''11, SIGMOD''10, ASPLOS''09, and a National Academy of Engineering Gilbreth Lectureship awardee in 2012. I am currently serving at the National Academies' Computer Science and Telecommunications Board. I hold B.S. and M.S. degrees in Electrical Engineering from the Pontifícia Universidade Católica of Rio de Janeiro, and a Ph.D. in Computer Engineering from the University of Southern California.

Ion Stoica (UC Berkeley)

Talk: Lessons from Apache Spark: To unify or to specialize?

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Abstract

Almost seven years ago we started the Spark project at UC Berkeley. Apache Spark is a cluster computing engine that is optimized for in-memory processing, and unifies support for a variety of workloads, including batch, interactive querying, streaming, and iterative computations. Spark is now the most active big data project in the open source community, and is already being used by over one thousand organizations. At the same time, in the database community there has been a recent push on building specialized engines for different workloads and use cases. In this talk, I'll take a look back at our experience with building a unified engine with Apache Spark, the lessons we learned in the process, and speculate on what could make unified or specialized systems successful.

Bio

Ion Stoica is a Professor in the EECS Department at University of California at Berkeley. He does research on cloud computing and networked computer systems. Past work includes Dynamic Packet State, Chord DHT, Internet Indirection Infrastructure (i3), declarative networks, and large scale systems, including Apache Spark, Apache Mesos, and Alluxio. He is an ACM Fellow and has received numerous awards, including the SIGOPS Hall of Fame (2015), the SIGCOMM Test of Time Award (2011), and the ACM doctoral dissertation award (2001). In 2006, he co-founded Conviva, a startup to commercialize technologies for large scale video distribution, and in 2013, he co-founded Databricks a startup to commercialize Apache Spark.