> I prefer developing everything locally because it feels snappier to me, even with a good internet connection…
oarsinsync’s IDE is sending each keystroke from his local computer to a cloud machine, where the source code lives. That source code compiles, executes, is tested in the cloud. Is this the setup you’re comparing with?
The theory behind this is sound: “When the size of the program is smaller than the data, move the program to the data.” In this particular instance, the code edit keystrokes are smaller than the total amount of source code. If the complete source code, packaged or compiled program has to be moved to the cloud anyway, it saves a lot of data transfer to just move the edits.
This assumes you’re running your application in the cloud, and the trade-off is that you need a reliable network connection, otherwise you might find yourself unable to edit when the network is down.
I believe when latency is a concern then the calculous skews much more in the direction of providing feedback locally based on the data. For instance a reasonable strategy could be to make updates to the file locally in the ide in order to provide immediate feedback as the user types, but then send those updates to the server where other higher latency features such as code completion or diagnostics are run. Sadly I have yet to see such a setup.
I use "cloud" as a catch-all that covers local and remote VMs, that are all built using standard templates. My local VMs are LAN-local, not host-local. My remote VMs are all <10ms away.
My particular workflow involves running my IDE locally, and having files hosted remotely. My IDE is plenty snappy, running my code is plenty snappy, but I'm slowed down by a need to commit + push changes to a repository.
I have it on my stack to do something like syncthing to keep a local + remote cache without needing to explicitly go through version control, but I suspect that'll just shift the latency out of my workflow, and trip me up in different ways.
oarsinsync’s IDE is sending each keystroke from his local computer to a cloud machine, where the source code lives. That source code compiles, executes, is tested in the cloud. Is this the setup you’re comparing with?
The theory behind this is sound: “When the size of the program is smaller than the data, move the program to the data.” In this particular instance, the code edit keystrokes are smaller than the total amount of source code. If the complete source code, packaged or compiled program has to be moved to the cloud anyway, it saves a lot of data transfer to just move the edits.
This assumes you’re running your application in the cloud, and the trade-off is that you need a reliable network connection, otherwise you might find yourself unable to edit when the network is down.