4:23 – Overview of Omnimodal's tech stack6:38 – Omnimodal's mission: to help cities manage transportation demand16:10 – How to ingest open transportation data and present it in real time21:43 – How graphics-heavy OpenGL and C++ apps can benefit from web tooling31:06 – Why state machines are used in both video game and web development34:55 – How JavaScript UI development compares to other paradigms38:46 – Why Ember and Rails were chosen for Omnimodal's technology needs42:09 – Using a prediction engine to improve on transportation schedules44:56 - How Omnimodal gets data from its hardware trackers to the Rails server50:55 – How services like Heroku and PubNub, custom AWS code, and the concept of a Data Lake help address scalability issues56:40 – How deploys are coordinated across multiple services59:47 - What the development process looks like for a multi-service tech stack1:02:10 – What the complexity breakdown is between Omnimodal's frontend and backend1:04:07 – Lessons learned on authentication while using Auth01:09:31 - Lessons learned on data modeling1:12:21 – Tech choices, escape hatches, what's worked, and what hasn't1:20:15 – Things Nathan loves about Ember, and things that are challengingNathan on TwitterOmnimodal.ioPubNubGTFS feed specificationAmazon KinesisAmazon ElastiCacheAWS AppSyncAuth0