Forgive the basic questions but I'm relatively new to RStudio.
I'm trying to figure out the most cost effective way to deploy RStudio Server on AWS with the need to scale to large amounts of memory. We are doing RNA-seq using Seurat with large datasets. On the desktop this requires a machine with at least of 256GB of RAM.
I'm trying to figure out if there's a way to do this on the cloud to minimize cost. Obviously an On-Demand EC2 instance with those kinds of resources would be extremely expensive to run for long periods of time, so I'm wondering if there's a way to use EC2's auto-scaling to spin up additional resources when resource intensive operations are performed then scale back down when the job is complete. I'm thinking using auto-scaling in conjunction with RStudio Server Pro's load balancing might be a solution but even then it seems every instance of RStudio Server would have to have a Pro license again making it very cost prohibitive even if for a short time.
Maybe there's a completely different approach I'm missing. Any thoughts on how to deal with this problem would be greatly appreciated. Thanks in advance.