[mbostock]

Yes, we use continuous deployment (cron) to rebuild as needed. You can also get realtime data on the client if you need to (via fetch or WebSocket to your own servers — it’s “just” JavaScript), but generally we find building static data snapshots a useful constraint because it forces you to think about exactly what data is needed, and as a result the dashboard loads instantly.

[sroussey]

Row64 dashboards are pretty instant. And interactive.

Edit: link: https://row64.com/

[ipsum2]

My use case is monitoring machine learning models as they train, static snapshots doesn't seem like the right approach for me.

[mbostock]

If you’re developing the models locally, perhaps Framework’s preview server could work: it watches local files and automatically pushes updates to the browser when files change. This enables reactive updates for data loaders, but also works with static files. So you could visualize the models as they are being generated — meaning as some external process writes local files.

But in general the use case we’re targeting is a shared data app, dashboard, or report. Not something just for you individually, or something ephemeral (that you look at in real-time during training). For example, Framework would work well for sharing a report or dashboard evaluating the performance of the latest models you’ve built with your team.