~/panel

Panel: Argo for ML: Achieving Scalability and User Experience

on YouTube 25m
Panelat ArgoCon Europe 2024 · on Tuesday, 2024-03-19· at 10:25· Pavilion 7 | Level 7.3 | Room N04· [machine-learning]

speakers

name:J.P
links:none on file
name:Elliot Gunton
website:https://elliotgunton.github.io/
name:Sambhav Kothari
links:none on file
name:Alina Schmidt
links:none on file

resources

video:https://youtu.be/Gldnvmn3dSQ
slides:none on file

summary

Companies describe building Argo Workflows platforms plus a Python layer that actually gets used: Argo plus Hera Python SDK powers continuous training and deployment across 300 engineers and over 40 teams, handling spiky cron-driven prediction deadlines and large fan-outs. Key wins are artifact visualization, intermediate parameters and provenance export; key pain is developer UX—YAML vs Python and onboarding—visible in an active support channel (5–10 daily questions). Experimentation with Argo Events and metrics/monitoring is underway.

AI-written summary · about

chapters (14)

  1. 0:00Panel introduction
  2. 1:27ML orchestration challenges
  3. 2:58Trading deadlines and ML
  4. 4:02Bloomberg chose Argo Workflows
  5. 6:31Centrica’s Argo adoption
  6. 7:58Hera and Python role
  7. 9:02Impact of Hera at Bloomberg
  8. 11:30Hera’s wildfire adoption
  9. 12:35Adoption challenges
  10. 17:10Future of ML with Argo
  11. 21:28Q&A
  12. 22:10Resistance to Hera
  13. 23:14Hera’s expansion to projects
  14. 24:20Closing remarks

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