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This talk introduces Fluid, a data abstraction and orchestration layer for Kubernetes workloads. It covers the challenges of separating storage and compute, Fluid’s architecture, and a quick start for creating datasets, running apps with data affinity, and autoscaling datasets.
Syllabus
Intro
Agenda
Journey of A Data-driven Company
Technical Challenges Blocking Faster Adoption
st Challenge: Complicated Data Storage
nd Challenge: 1/0 Bottleneck
rd Challenge: Locality-ignoring Scheduling
What is Fluid, indeed
Fluid Architecture
A Quick Start on Fluid: (1) Create a "Dataset"
A Quick Start on Fluid: (2) Run Apps with Data Affinity
Quick Start on Fluid: Auto-scale Dataset
Demo
Roadmap
Plan
Community & Join Us
Taught by
CNCF [Cloud Native Computing Foundation]