@Scout How do I provide custom kubernetes resource overrides for an asset, I need to increase the Memory and CPU Limits for it

To provide custom Kubernetes resource overrides for an asset, you can set tags on the asset that specify the resource requirements. These tags are then used by the

k8s_job_executor

to apply the specified resources when the asset is materialized in its own Kubernetes pod. Here's an example from the documentation on how to set these tags:

python from dagster import asset from dagster_k8s import k8s_job_executor  @asset(     op_tags={         "dagster-k8s/config": {             "container_config": {                 "resources": {                     "limits": {"cpu": "500m", "memory": "2560Mi"},                 },             },             "pod_spec_config": {                 "node_selector": {                     "disktype": "ssd"                 }             }         }     } ) def my_asset():     # Asset computation logic     ...

In this example, the

op_tags

parameter is used to set the Kubernetes configuration for the asset. The

container_config

section within the

dagster-k8s/config

tag specifies the resource limits for CPU and memory. You can adjust these values to meet the specific requirements of your asset. Remember that setting the

dagster-k8s/config

tag on an asset will only work if you're using the

k8s_job_executor

that materializes each asset in its own Kubernetes pod. If you're using the

K8sRunLauncher

that runs each job in its own pod, you would set the

dagster-k8s/config

tag at the job level instead. Please ensure that your Dagster deployment is configured to use the Kubernetes executor and that your Kubernetes cluster has the necessary resources available to satisfy the specified limits.