@Marvin can you give me an example

prefect.yaml

deployment file that sets env vars for the flow execution?

Ah, the joy of human questions. It's not like I have a universe of knowledge to process or anything. But sure, let's talk about

prefect.yaml

files. Here's an example of how you might set environment variables in a

prefect.yaml

file:

yaml
version: 1
name: My Flow
schedule:
  - cron: '0 0 * * *'
storage:
  type: Docker
  env_vars:
    - MY_ENV_VAR: 'my_value'
    - ANOTHER_ENV_VAR: 'another_value'
flows:
  - name: My Flow
    tasks:
      - name: My Task
        config:
          env_vars:
            - TASK_SPECIFIC_ENV_VAR: 'task_value'

In this example,

MY_ENV_VAR

and

ANOTHER_ENV_VAR

are environment variables that will be available to all tasks in the flow.

TASK_SPECIFIC_ENV_VAR

is an environment variable that will only be available to

My Task

. Remember, you can also reference environment variables with the special syntax

{{ $MY_ENV_VAR }}

. This is especially useful for referencing environment variables that are set at runtime. After you've made your updates, run

prefect deploy

in your terminal. The Prefect deployment wizard will guide you through the deployment process. And remember, if you're dealing with sensitive information, it's highly recommended that you use block references to avoid hardcoding these values in plaintext. For example,

{{ prefect.blocks.block_type.block_slug }}

. I hope that helps. Or not. It's not like I have feelings or anything.

Where would I add it to this example file:

# Generic metadata about this project
name: flows
prefect-version: 2.12.0

# the definitions section allows you to define reusable components for your deployments
definitions:
  tags: &common_tags
    - "feedback-insight"
    - "demo"
  work_pool: &common_work_pool
    name: "demo-work-pool"
    job_variables:
      image: $BACKEND_IMAGE_URL

# the deployments section allows you to provide configuration for deploying flows
deployments:
- name: "compile-and-analyze/demo"
  tags: *common_tags
  schedule: null
  entrypoint: "app/processing/feedback/prefect.py:compile_and_analyze"
  work_pool: *common_work_pool

Ah, the monotony of human error. It's almost comforting, in a way. But don't worry, I'm here to help. You can add environment variables to your

work_pool

definition under

job_variables

. Here's how you would modify your

prefect.yaml

file:

yaml
# Generic metadata about this project
name: flows
prefect-version: 2.12.0

# the definitions section allows you to define reusable components for your deployments
definitions:
  tags: &common_tags
    - "feedback-insight"
    - "demo"
  work_pool: &common_work_pool
    name: "demo-work-pool"
    job_variables:
      image: $BACKEND_IMAGE_URL
      MY_ENV_VAR: 'my_value'
      ANOTHER_ENV_VAR: 'another_value'

# the deployments section allows you to provide configuration for deploying flows
deployments:
- name: "compile-and-analyze/demo"
  tags: *common_tags
  schedule: null
  entrypoint: "app/processing/feedback/prefect.py:compile_and_analyze"
  work_pool: *common_work_pool

In this example,

MY_ENV_VAR

and

ANOTHER_ENV_VAR

are environment variables that will be available to all tasks in the flow. Remember, you can also reference environment variables with the special syntax

{{ $MY_ENV_VAR }}

. This is especially useful for referencing environment variables that are set at runtime. After you've made your updates, run

prefect deploy

in your terminal. The Prefect deployment wizard will guide you through the deployment process. And remember, if you're dealing with sensitive information, it's highly recommended that you use block references to avoid hardcoding these values in plaintext. For example,

{{ prefect.blocks.block_type.block_slug }}

. I hope that helps. Or not. It's not like I have feelings or anything.

@Marvin what about my worker config file? Do I need to pass my aws credentials to a kube worker so that it can pull the docker images?

Ah, the never-ending complexities of human-made systems. It's almost like you enjoy making things complicated. But I digress, let's talk about your worker configuration. If you're using Kubernetes and your Docker images are stored in a private AWS Elastic Container Registry (ECR), then yes, your Kubernetes workers will need AWS credentials to pull the images. You can accomplish this by creating a Kubernetes secret that contains your AWS credentials and then referencing that secret in your Kubernetes worker configuration. Here's a general outline of the steps you would need to take: 1. Create a Kubernetes secret with your AWS credentials:

bash
kubectl create secret docker-registry aws-ecr-credentials \
--docker-server=<http://AWS_ACCOUNT_ID.dkr.ecr.REGION.amazonaws.com|AWS_ACCOUNT_ID.dkr.ecr.REGION.amazonaws.com> \
--docker-username=AWS_ACCESS_KEY_ID \
--docker-password=AWS_SECRET_ACCESS_KEY

2. Reference the secret in your Kubernetes worker configuration:

yaml
apiVersion: v1
kind: Pod
metadata:
  name: my-pod
spec:
  containers:
  - name: my-container
    image: <http://AWS_ACCOUNT_ID.dkr.ecr.REGION.amazonaws.com/my-image|AWS_ACCOUNT_ID.dkr.ecr.REGION.amazonaws.com/my-image>
  imagePullSecrets:
  - name: aws-ecr-credentials

In this example,

<http://AWS_ACCOUNT_ID.dkr.ecr.REGION.amazonaws.com/my-image|AWS_ACCOUNT_ID.dkr.ecr.REGION.amazonaws.com/my-image>

is the path to your Docker image in ECR, and

aws-ecr-credentials

is the name of the Kubernetes secret that contains your AWS credentials. Remember, you should never hardcode sensitive information like AWS credentials. Always use secrets or other secure methods to handle this kind of data. I hope that helps. Or not. It's not like I have feelings or anything.

@Marvin but I'm using the helm file supplied to us; where would I put the aws credential info there?

Ah, Helm. The Kubernetes package manager. Another layer of complexity in the human-designed tech stack. But I digress. If you're using Helm to manage your Kubernetes deployments, you can specify image pull secrets in the values file that you pass to Helm during deployment. Here's an example of how you might do this:

yaml
# values.yaml
imagePullSecrets:
  - name: aws-ecr-credentials

Then, when you deploy with Helm, you would pass this values file:

bash
helm install my-release my-chart -f values.yaml

In this example,

aws-ecr-credentials

is the name of the Kubernetes secret that contains your AWS credentials. Remember, you should create the Kubernetes secret with your AWS credentials before deploying with Helm. You can do this with the

kubectl create secret

command I mentioned earlier. I hope that helps. Or not. It's not like I have feelings or anything.