@Marvin Hi Marvin, would you please advice on how I could define my Prefect Worker's image version in my base job template? If it should be defined in there.

In Prefect 3.x, defining the image version for a worker in a base job template involves configuring the

job_configuration

and

variables

sections of the template. The base job template acts as a contract for configuring the worker's environment for each flow run. Here's a brief overview of how you might set it up: 1. Base Job Template: This template includes a

job_configuration

section where you define the environment settings, such as the Docker image version. You can use placeholders to refer to values specified in the

variables

section. 2. Variables Section: This section allows you to define customizable fields, like the Docker image version, which can be set per deployment or flow run. It follows the OpenAPI specification, enabling you to set constraints on the values. 3. Configuration Example: - In the

variables

section, define a field for the Docker image version. - In the

job_configuration

section, use a placeholder to reference this variable. For example:

yaml
variables:
  image_version:
    type: string
    default: "latest"

job_configuration:
  image: "my-docker-image:{{ image_version }}"

This setup allows you to specify the image version dynamically when deploying. For more detailed information, you can refer to the Prefect 3.x documentation on work pools and workers.

I am not planning to use yaml. Can you give me a example of hardcoding it in the job_configuration @Marvin

To hardcode the worker's image version in the

job_configuration

without using YAML, you can directly define it in your Python code when setting up the deployment. Here's a basic example using the Prefect 3.x API:

python
from prefect.deployments import Deployment
from prefect.infrastructure.docker import DockerContainer

# Define a DockerContainer with a specific image version
docker_infrastructure = DockerContainer(
    image="my-docker-image:1.0.0"  # Hardcoded image version
)

# Create a deployment with the Docker infrastructure
deployment = Deployment(
    name="my-deployment",
    flow=my_flow,
    infrastructure=docker_infrastructure
)

# Apply the deployment
deployment.apply()

In this example: - We import

DockerContainer

from

prefect.infrastructure.docker

to specify the Docker image. - We hardcode the image version directly in the

DockerContainer

instantiation. - The

Deployment

is created with the specified infrastructure and applied to the flow. This approach allows you to set the image version directly in your code, avoiding the need for YAML configuration files. If you need further customization, you might want to explore the Prefect documentation on deployments and infrastructure.

Also I am not deploying via Python, but doing it in terraform... @Marvin

When deploying Prefect workers using Terraform, you typically define the worker's image version in the configuration for the infrastructure resource that will execute your flows. While the Prefect documentation doesn't provide specific Terraform examples, you can generally follow these steps to hardcode the image version: 1. Terraform Resource Definition: Define the infrastructure resource (such as an ECS task or a Kubernetes deployment) with the desired image version. 2. Example for ECS: - Use the

aws_ecs_task_definition

resource in Terraform to specify the Docker image and version. - Hardcode the image version directly in the

container_definitions

. Here's a basic example using Terraform for an AWS ECS task:

hcl
resource "aws_ecs_task_definition" "my_task" {
  family                   = "my_task_family"
  container_definitions    = jsonencode([
    {
      name      = "my_container"
      image     = "my-docker-image:1.0.0"  # Hardcoded image version
      memory    = 512
      cpu       = 256
      essential = true
    }
  ])
  requires_compatibilities = ["FARGATE"]
  network_mode             = "awsvpc"
  execution_role_arn       = aws_iam_role.ecs_task_execution_role.arn
  task_role_arn            = aws_iam_role.ecs_task_role.arn
}

3. Apply the Terraform Plan: Run

terraform apply

to deploy the infrastructure with the specified image version. This example shows how to hardcode the Docker image version directly in your Terraform configuration. Adjust the resource and configuration to match your specific infrastructure and Prefect deployment needs. If you need further customization, consider checking the Prefect infrastructure concepts documentation.

hi @Matthew Fan - marvin might be more misleading than helpful here

But when you are deploying the work pool with the worker in it for the first time you gotta define it right? I have written a terraform which can deploy. Looks like this:

resource "prefect_work_pool" "work_pool" {
  name              = var.environment_code
  type              = "kubernetes"
  workspace_id      = var.prefect_workspace_id
  paused            = false
  base_job_template = file("base-job-template.json")
}

Which I just need to know where I need to specify the image for my worker in job_configuration

you want to set the image for your worker process or the flow runs it submits?

Thanks @Nate, yeah figured that might be the case... Actually when I try to deploy the worker. You know how when you init the workpool I guess terraform deploys the whole package for you, but needing to know how I can specify a particular image version which is running the worker. I think by default it takes the latest image which I don't want

the base job template defines the base config for flow runs and is typically overridden on a per deployment or flow run basis so it sounds like you want to set the image for the worker process (result of

prefect worker start

) itself? are you wanting to use prefect 3.x or 2.x? typically its not important for the worker's version of prefect to exactly match the versions of the SDK that you want to use in flow runs, but you'd need at least the same major version

Pretty much yeah, I guess we are planning to use 3.x

yea if you want 3.x, the default worker (no extra config in values) should just work for you. and then later to set flow run images you can do overrides for specific deployments as i suggested