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Nathan Selikoff on Omnimodal's real-time tech stack
Podcast |
Frontend First
Media Type |
audio
Categories Via RSS |
Technology
Publication Date |
May 08, 2019
Episode Duration |
01:27:53

Topics include:

  • 4:23 – Overview of Omnimodal's tech stack
  • 6:38 – Omnimodal's mission: to help cities manage transportation demand
  • 16:10 – How to ingest open transportation data and present it in real time
  • 21:43 – How graphics-heavy OpenGL and C++ apps can benefit from web tooling
  • 31:06 – Why state machines are used in both video game and web development
  • 34:55 – How JavaScript UI development compares to other paradigms
  • 38:46 – Why Ember and Rails were chosen for Omnimodal's technology needs
  • 42:09 – Using a prediction engine to improve on transportation schedules
  • 44:56 - How Omnimodal gets data from its hardware trackers to the Rails server
  • 50:55 – How services like Heroku and PubNub, custom AWS code, and the concept of a Data Lake help address scalability issues
  • 56:40 – How deploys are coordinated across multiple services
  • 59:47 - What the development process looks like for a multi-service tech stack
  • 1:02:10 – What the complexity breakdown is between Omnimodal's frontend and backend
  • 1:04:07 – Lessons learned on authentication while using Auth0
  • 1:09:31 - Lessons learned on data modeling
  • 1:12:21 – Tech choices, escape hatches, what's worked, and what hasn't
  • 1:20:15 – Things Nathan loves about Ember, and things that are challenging

Links:

Nathan joins Sam and Ryan to talk about how he's using Ember, Rails, Node, and AWS infrastructure to build Omnimodal, the startup he co-founded to help cities manage their transportation demand in real time.

Topics include:

  • 4:23 – Overview of Omnimodal's tech stack
  • 6:38 – Omnimodal's mission: to help cities manage transportation demand
  • 16:10 – How to ingest open transportation data and present it in real time
  • 21:43 – How graphics-heavy OpenGL and C++ apps can benefit from web tooling
  • 31:06 – Why state machines are used in both video game and web development
  • 34:55 – How JavaScript UI development compares to other paradigms
  • 38:46 – Why Ember and Rails were chosen for Omnimodal's technology needs
  • 42:09 – Using a prediction engine to improve on transportation schedules
  • 44:56 - How Omnimodal gets data from its hardware trackers to the Rails server
  • 50:55 – How services like Heroku and PubNub, custom AWS code, and the concept of a Data Lake help address scalability issues
  • 56:40 – How deploys are coordinated across multiple services
  • 59:47 - What the development process looks like for a multi-service tech stack
  • 1:02:10 – What the complexity breakdown is between Omnimodal's frontend and backend
  • 1:04:07 – Lessons learned on authentication while using Auth0
  • 1:09:31 - Lessons learned on data modeling
  • 1:12:21 – Tech choices, escape hatches, what's worked, and what hasn't
  • 1:20:15 – Things Nathan loves about Ember, and things that are challenging

Links:

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