Google's products, e.g. Search, YouTube, Gmail, etc. are used by billions of people the world over. Google Cloud hosts some of the most popular services in the world. Building systems that scale to support all these applications is among the greatest challenges at the company. Underlying all these systems is the network which must enable low-latency, high throughput, high capacity, high availability and secure access to compute and storage. While Google has been enormously successful in achieving these goals, cloud networking faces exciting new challenges today. With the demise of Moore's Law and explosive data growth, the implications for the performance, reliability, predictability and cost efficiency on networking, from hardware to communication protocols, will be profound.
This talk will focus on highlighting some of the challenges in networking alluded to above. Additionally, we will discuss the current and future challenges in network telemetry systems and Google's approach to overcoming these challenges via statistical inference which allows us to estimate that which cannot be measured.
Bio:
Muhammad Jehangir Amjad is a Software Engineer in the Network Infrastructure team at Google working on inference and statistical learning on data produced by network telemetry systems. He joined Google from MIT where he has an appointment as a Lecturer of Machine Learning in CSAIL. Jehangir received his PhD from the Operations Research Center (ORC) and Laboratory of Information and Decision Systems (LIDS) at MIT, under the supervision of Prof Devavrat Shah. He received his BSE in Electrical Engineering from Princeton University.
To request accommodations for a disability, please contact Emily Lawrence, emilyl@cs.princeton.edu, 609-258-4624 at least one week prior to the event.