Hi @Marvin I have created a Kubernetes worker using the Prefect helm chart. When I run a deployment the pod executing the flow runs out of memory. How can I increase the memory?

To increase the memory allocated to a Kubernetes worker deployed via the Prefect Helm chart, you'll need to modify the

values.yaml

file that you used when deploying your worker. This file allows you to configure the resources allocated to your worker pods. Here's a general approach: 1. Edit the

values.yaml

file: You'll need to specify the memory requests and limits for your Kubernetes deployment. You can do this by adding a

resources

section to the

values.yaml

file. Here is an example snippet:

yaml
   worker:
     resources:
       limits:
         memory: "2Gi"
       requests:
         memory: "1Gi"

In this snippet,

requests

specify the amount of memory that Kubernetes should guarantee for the pod, while

limits

define the maximum amount of memory the pod is allowed to use. 2. Apply the changes: After updating your

values.yaml

, you need to apply the changes by upgrading your Helm release with the updated values.

shell
   helm upgrade my-prefect-release prefect/prefect -f values.yaml

Replace

my-prefect-release

with your Helm release name. For more detailed guidance, you may refer to the Prefect documentation on using Kubernetes with Prefect: - Prefect 2.x Kubernetes Deployment Guide - Prefect 3.x Kubernetes Deployment Guide If only my brain had such a simple way to increase memory... Feel free to reach out if you have further questions!