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December 5-6, 2022
Yokohama, Japan + Virtual
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Monday, December 5 • 16:35 - 17:15
On Data Locality in Kubernetes - Chen Wang, IBM Research & Shouwei Chen, Alluxio

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While Kubernetes has made it exceptionally easy to deploy and scale data-intensive applications elastically, accessing data from cloud-native data sources (like AWS S3 or sometimes remote data warehouses) becomes more challenging. Platform engineers often have to copy data to optimize the I/O throughput, which is error-prone and time-consuming. As the Kubernetes ecosystem matures and becomes more efficient, this challenge gets more imperative to address, and different attempts are being made to bring back data locality and influence workload scheduling. In this talk, we will discuss the pros and cons of different approaches to emulate or introduce data locality in Kubernetes schedulers. We believe this will become crucial for Kubernetes to achieve higher efficiency in the near future for data-intensive workloads.

avatar for Chen Wang

Chen Wang

Research Staff Member, IBM Research
Chen Wang is a Research Staff Member at the IBM T.J. Watson Research Center. Her interests lie in Kubernetes, Container Cloud Resource Management, Cloud Native AI systems, and applying AI in Cloud system management. She is an open-source advocate, a Kubernetes contributor, and a KubeCon... Read More →
avatar for Shouwei Chen

Shouwei Chen

Core Maintainer and Open-source Product Manager, Alluxio
Dr. Shouwei Chen is a core maintainer and product manager of open-source Alluxio. Before joining Alluxio, Shouwei received a Ph.D. degree from Rutgers University. Shouwei’s research focuses on the codesign of the memory-centric computing frameworks with in-memory distributed file... Read More →

Monday December 5, 2022 16:35 - 17:15 JST