The use case:
Say I’ve got a homogenous set of batch jobs (crunching data) and I’d like to execute them in parallel on a heterogenous cluster of machines. Some of these machines support containerization/virtualization and some do not. Perhaps they are also running different operating systems. All agents are capable of processing the incoming data, but some might be executing a container while others are running an executable in exec or raw_exec mode to do so.
More detail:
My assumption is that tasks for these jobs might need to look slightly different depending on which agent they’re running on- specifically the task driver will need to be different depending on the capabilities of the agent, and the task definition itself may need to vary as a result. However, the agents are all capable of processing the data in one way or another, so it makes more sense to treat them as a homogenous set during work assignment and to deal with the details of how the data is processed once the work has been assigned.
The question(s):
Does Nomad have facilities for dealing with this case? Am I thinking about this wrong, or asking the wrong questions? I imagine this could be solved by writing a custom task driver, but that seems a bit drastic as a solution that could presumably be solved by dynamic driver/task selection.