AWS naming of instance types is broken down here:
Each class (like mem1) is scaled so that each core in an instance has access to the same amount of memory/disk space:
Example: mem1_ssd1_v2_x2:
4 Gb total memory / 2 cores =
2 Gb / Core
Example: mem1_ssd1_v2_x8:
Scale usage/instance type according to usage statistics and dataset size
If it doesn't utilize all resources
Use a smaller instance type
Runs out of memory, or is slow
Each stage of a workflow is run by a different set of workers
Each stage can be customized in terms of instance type
To create a support ticket if there are technical issues:
Go to the Help header (same section where Projects and Tools are) inside the platform
Select "Contact Support"
Fill in the Subject and Message to submit a support ticket.
16 Gb total memory / 8 cores =
2 Gb / core
Consider using a larger instance type
Does the software utilize multiple cores?
mem2_ssd1_v2_x16
Is the software GPU optimized?
mem2_ssd1_gpu_x32
How much memory does the software use (per core)?
mem2_ssd1_v2_x16
How much disk space is needed for the software (per core)?
mem2_ssd1_v2_x16
Always use version 2 of an instance type!
mem2_ssd1_v2_x16