Minlan Yu is an associate professor of computer science at Yale and before that at USC. She works in several areas that are relevant to Open vSwitch, including network virtualization and software-defined networking, enterprise and data center networks, and distributed systems.

We begin by talking about ACM

SIGCOMM 2017 1st International Workshop on Hot Topics in Container

Networking and Networked Systems, which Minlan is co-chairing. “HotConNet” is a new workshop at SIGCOMM this year focusing on networking for containers, which is far from a mature field. The workshop is accepting 6-page papers until March 24. Workshop papers will be presented as part of SIGCOMM 2017 in Los Angeles, August 21 to 23.

The main topic of discussion is Trumpet:

Timely and Precise Triggers in Data Centers, published at SIGCOMM in August 2016. The abstract for this paper is:

As data centers grow larger and strive to provide tight performance and

availability SLAs, their monitoring infrastructure must move from passive

systems that provide aggregated inputs to human operators, to active

systems that enable programmed control. In this paper, we propose

Trumpet, an event monitoring system that leverages CPU resources and

end-host programmability, to monitor every packet and report events at

millisecond timescales. Trumpet users can express many network-wide

events, and the system efficiently detects these events using

triggers at end-hosts. Using careful design, Trumpet can

evaluate triggers by inspecting every packet at full line rate even on

future generations of NICs, scale to thousands of triggers per end-host

while bounding packet processing delay to a few microseconds, and report

events to a controller within 10 milliseconds, even in the presence of

attacks. We demonstrate these properties using an implementation of

Trumpet, and also show that it allows operators to describe new network

events such as detecting correlated bursts and loss, identifying the root

cause of transient congestion, and detecting short-term anomalies at the

scale of a data center tenant.

Afterward, Minlan provides a sneak peak at a paper to be presented at NSDI in March, “CherryPick: Adaptively Unearthing the Best Cloud Configurations.” This paper will present an efficient way to choose the best machine type and parameters in a public from among the hundreds of configurations offered by large public clouds.

Minlan may be contacted via email: minlan.yu (at) yale (dot) edu. You can also follow her on

Twitter.

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