They forgot to mention another nice feature of GCE - custom machine types. You can choose number of vCPUs and amount of memory and also the amount of local (eph

They forgot to mention another nice feature of GCE - custom machine types. You can choose number of vCPUs and amount of memory and also the amount of local (ephemeral in AWS speak) storage in 375GB increments. This is a huge advantage. For instance, some of our jobs are computationally-intensive but relatively light on memory. In GCE I can run 32 core machine with 28GB RAM and it will cost me $887.68/month (without any sustained use discounts). In AWS, the closest option I have is c4.8xlarge (36 cores / 60 GB RAM) which will cost $1,226.10/mo. And if I need local (ephemeral) storage in AWS, I'm severely limited in instance types I can choose from, while in GCE you can attach local SSD to any instance type, including custom. If you factor in per-minute billing in GCE and automatic sustained use discounts, we are talking about serious savings without any advance planning (required for using reserved instances). EC2 still has some advantages - it supports GPU-equipped instances, for example, but for our computational pipelines GCE is a clear winner for now (and Cloud Dataproc is so much nicer than EMR!).