My coworker tried to build and deploy some workflows to our Flyte cluster (runs over AWS EKS). For a couple of the workflows, he got

current limit set in the platform configuration

errors (one for CPU, one for memory). Yet in our Flyte code we don't see anything particular about those workflows that would be causing that problem. (1) Is there a comprehensive list of the settings (in Flyte and in k8s) that influence what resources are available? (2) Is there a way to use

flyteadmin

or

kubectl

to try to locate the element or layer that's setting the resources too conservatively?

Depending on your type of deployment (flyte-binary, flyte-core), there is a

resources

section in the values file for

memory

and

cpu

.

OK, I'll try those. I think our setup is

flyte-core

.

You can update the values file and

helm upgrade ...

to apply new values to the resources limits/requests. The tasks may also need to be configured for greater resources but I think you will get a different error if that's the issue.

@task(
    limits=Resources(cpu="500m", mem="500Mi"),
    requests=Resources(cpu="200m", mem="400Mi"),
)
def my_task() ->...