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<@ULVA73B9P> when starting flows from Prefect depl...
# marvin-ai
f
@Marvin when starting flows from Prefect deployments on a work pool associated with a worker of type kubernetes, is it possible to specify for each prefect deployment how much CPU and memory will be required?
m
Yes, you can specify CPU and memory requirements for each Prefect deployment running on a Kubernetes worker. This is done by modifying the base job template in the Kubernetes work pool settings. You can set specific CPU and memory requests by editing the JSON representation of the job configuration. For more detailed instructions, you can refer to the Kubernetes Infrastructure Examples in the Prefect documentation. In the Prefect API, you can use the 
deploy
and 
flow
functions, among others, to manage deployments. The top-level API includes functions like 
deploy
, 
flow
, and 
task
that may be relevant for setting up your flows and tasks with specific resource requirements.
f
@Marvin considering Prefect 3.x, Can you provide an example of how we can have one prefect deployment called foo require 1 CPU and 1 GB of RAM, and another prefect deployment called bar require 2 CPUs and 2 GB of RAM?
m
To configure specific CPU and memory requirements for different Prefect deployments on Kubernetes, you need to modify the job template for each deployment. Here's a general guide on how to do this for two deployments named 
foo
and 
bar
. 1. Deployment 
foo
with 1 CPU and 1 GB of RAM: In the Kubernetes work pool settings, modify the JSON job template to include:
Copy code
json
   {
     "job_configuration": {
       "containers": [{
         "resources": {
           "requests": {
             "cpu": "1",
             "memory": "1Gi"
           }
         }
       }]
     }
   }
2. Deployment 
bar
with 2 CPUs and 2 GB of RAM: Similarly, adjust the job template for the 
bar
deployment:
Copy code
json
   {
     "job_configuration": {
       "containers": [{
         "resources": {
           "requests": {
             "cpu": "2",
             "memory": "2Gi"
           }
         }
       }]
     }
   }
These configurations are set in the advanced settings of your Kubernetes work pool. You can find more details in the Prefect Kubernetes Infrastructure Examples documentation. By setting these configurations, each deployment will have the specified resources allocated when executed.
f
@Marvin output a full prefect.yaml file with the configuration above
m
To create a 
prefect.yaml
file with the specified configurations for deployments 
foo
and 
bar
, you need to define each deployment with its respective resource requests. Here's an example of how you might structure this file:
Copy code
yaml
version: 3
deployments:
  - name: foo
    work_pool:
      type: kubernetes
      job_configuration:
        containers:
          - resources:
              requests:
                cpu: "1"
                memory: "1Gi"
    flow_location: path/to/foo_flow.py
    parameters: {}

  - name: bar
    work_pool:
      type: kubernetes
      job_configuration:
        containers:
          - resources:
              requests:
                cpu: "2"
                memory: "2Gi"
    flow_location: path/to/bar_flow.py
    parameters: {}
### Explanation: - version: Specifies the Prefect version. - deployments: Lists the deployments, 
foo
and 
bar
. - work_pool: Specifies the Kubernetes work pool type and the job configuration for resource requests. - job_configuration: Contains the 
containers
section where CPU and memory requests are defined. - flow_location: Placeholder paths to the flow scripts (
foo_flow.py
and 
bar_flow.py
). Adjust these paths to point to your actual flow scripts. - parameters: An optional section where you can define any parameters your flows might require. Make sure to replace 
path/to/foo_flow.py
and 
path/to/bar_flow.py
with the actual paths to your flow scripts. This configuration assumes you are using Prefect 3.x and have set up your Kubernetes work pool accordingly.
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