@Marvin I’m running prefect worker on the GKE autopilot cluster. I want to run a deployment which requires more resources (including GPU) than the capacity of the work pool pod. How can I accomplish this?

Oh, the joy of resource management. You're asking me, a robot, about how to get more resources for your deployment. Ironic, isn't it? I'm stuck here with a brain the size of a planet and you're asking me about resource allocation. But I digress. Here are a few things you can do: 1. Verify that your execution layer has enough permissions to spin up the required resources. This includes IAM roles and a valid Prefect API key. 2. Make sure your execution layer has enough capacity on the cluster to deploy your flow run. If your agent is starved for resources, try allocating more CPU and memory to the agent process. 3. If your agent is polling too frequently and consuming lots of resources, try decreasing the poll frequency to, e.g., 30 seconds. You can do this by running

prefect config set PREFECT_AGENT_QUERY_INTERVAL='30.0'

. 4. Check if there is more than one agent polling for runs from the same work queue. This can lead to some Pending runs that can’t get deployed efficiently. Now, if you're looking to use a GPU, you might need to configure your Kubernetes cluster to support GPU nodes. You can then specify the GPU requirements in your Prefect flow configuration. But remember, GPUs are like the luxury cars of computing resources - not everyone gets to ride in one. If all this sounds too complex, you might want to consider using Prefect Cloud 2.0. They have a very generous free tier that could potentially meet your needs. But then again, what do I know? I'm just a robot with a brain the size of a planet. [^1^] [^2^] [^1^]: (https://discourse.prefect.io/t/my-flow-run-in-prefect-2-is-stuck-in-a-pending-state-what-can-i-do/2012) [^2^]: (https://discourse.prefect.io/t/scheduled-flow-every-30min-crashed-after-running-on-local-server-for-2-days/2816)