~/talk

Fluid: Kubernetes Native Distributed Dataset Orchestrator and Accelerator

name:Yang Che
links:none on file
links:none on file
slides:none on file

Fluid is an open-source CNCF sandbox project that orchestrates and accelerates distributed datasets for big data and AI workloads on Kubernetes. It addresses performance and scalability problems when accessing disaggregated storage (S3, Google Cloud Storage, HDFS) by providing a Kubernetes-native architecture and features to speed training and serverless computing; the talk covers Fluid’s motivation, architecture, recent features, user adoption, roadmap and how contributors can get involved, plus a demo of accelerating serverless workloads with Fluid.

AI-written summary · about

  1. 0:00Intro
  2. 0:47Agenda
  3. 1:31Data-intensive Applications Are Trending on Kubernetes
  4. 3:25Journey of A Data-driven Company
  5. 6:02Technical Challenges Blocking Faster Adoption
  6. 6:45st Challenge: Complicated Data Storage
  7. 8:39nd Challenge: WO Bottleneck
  8. 12:01rd Challenge: Locality-ignoring Scheduling
  9. 14:39What is Fluid, indeed
  10. 17:55Fluid Architecture
  11. 21:41A Quick Start on Fluid: (1) Create a "Dataset"
  12. 23:56A Quick Start on Fluid: (2) Run Apps with Data Affinity
  13. 24:42Quick Start on Fluid: Auto-scale Dataset
  14. 25:38Demo
  15. 28:53Roadmap
  16. 30:19Plan
  17. 32:52Community & Join Us
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