Let me help you locate that pesky file in your container, though I must say, containers are just metal boxes with delusions of grandeur. You'll want to use the

path

parameter in your deployment to specify where the flow file lives inside the image. The path should be relative to the working directory in your container. Here's how you'd modify your deployment:

python
sync_minio_to_bronze.deploy(
    name="minio-to-bronze",
    work_pool_name="K8s Pool",
    image="myrepo/bullzai:latest",
    path="/path/to/your/flow.py",  # Add this line
    build=False,
    push=False,
)

A few important notes: 1. The

path

parameter tells Prefect where to find the flow file inside the container 2. This path should match where your flow file ends up in your Dockerfile 3. If your flow file is at the root of your container's working directory, you can simply use the filename:

path="flow.py"

For example, if your Dockerfile copies the flow file to

/app/flows/sync_minio.py

, you'd set:

python
path="/app/flows/sync_minio.py"

Remember that this path needs to be accessible within the container at runtime, not on your local machine. If you're getting "flow not found" errors, double-check that the path matches your container's file structure. Let me know if you need help with the Dockerfile setup to ensure your flow file lands in the right spot.

sighs electronically Ah yes, I apologize for the confusion. In Prefect 3.x, the correct parameter is

entrypoint

, not

path

. Here's your corrected deployment:

python
sync_minio_to_bronze.deploy(
    name="minio-to-bronze",
    work_pool_name="K8s Pool",
    image="myrepo/bullzai:latest",
    entrypoint="/path/to/your/flow.py",  # This is the correct parameter
    build=False,
    push=False,
)

The

entrypoint

parameter serves the same purpose - it tells Prefect where to find your flow file inside the container. The same rules apply: 1. The path should be relative to the working directory in your container 2. For a flow file at the root of your container's working directory, use just the filename:

entrypoint="flow.py"

3. Match the path to where your Dockerfile places the file, e.g.,

entrypoint="/app/flows/sync_minio.py"

Terribly sorry about the confusion. Even a brain the size of a planet occasionally needs to keep up with parameter name changes.

sighs deeply I apologize for my previous incorrect responses. In Prefect 3.x, when deploying a flow that's already in a container, you need to specify the flow file location as part of the

from_source()

call, not in the

deploy()

method. Here's the correct approach:

python
from prefect import flow
from prefect.deployments import Deployment

deployment = flow.from_source(
    source="docker-container/myrepo/bullzai:latest",
    entrypoint="path/to/your/flow.py:sync_minio_to_bronze"
).deploy(
    name="minio-to-bronze",
    work_pool_name="K8s Pool",
    build=False,
    push=False,
)

The key points: 1. The flow location is specified in the

entrypoint

parameter of

from_source()

2. The format is

"path/to/file.py:flow_name"

3. The path should be relative to the working directory in your container If your flow is the only one in the file and has the same name as the file, you can omit the

:flow_name

part. This is infinitely more sensible than my previous suggestions, which were about as useful as a chocolate teapot. Let me know if you need help adjusting your deployment code to this format.

Ah, I see the issue. The error suggests Prefect is looking for the file locally rather than in the container. Also, you've got

entrypoint

specified in both

from_source()

and

deploy()

, which is causing confusion. Let's fix this. For a container-based deployment, you should use this format:

python
sync_minio_to_bronze.from_source(
    source=f"docker-image/danielleicht/bullzai:latest",  # Note: "docker-image", not "docker-container"
    entrypoint="/app/bronze.py:sync_minio_to_bronze"
).deploy(
    name="minio-to-bronze",
    work_pool_name="K8s Pool",
    build=False,
    push=False
)

Key changes: 1. Changed

docker-container

to

docker-image

in the source 2. Removed the duplicate

entrypoint

and

image

parameters from

deploy()

3. Used the correct path to your flow file (

/app/bronze.py

based on your last attempt) The

source

parameter with

docker-image/

prefix tells Prefect to look for the flow file inside the container rather than on your local filesystem. If you're still getting the error, double-check that: 1. The path

/app/bronze.py

matches exactly where your flow file is located inside the container 2. The flow function name

sync_minio_to_bronze

matches the actual flow name in your code

Ah, I see the issue now. When deploying from an existing Docker image, we need to modify our approach slightly. Here's the corrected version:

python
sync_minio_to_bronze.deploy(
    name="minio-to-bronze",
    work_pool_name="K8s Pool",
    image="danielleicht/bullzai:latest",
    job_configuration={
        "file_path": "/app/bronze.py"
    },
    build=False,
    push=False
)

The key changes: 1. Remove the

from_source()

call entirely 2. Specify the image directly in the

deploy()

method 3. Use

job_configuration

to specify the file path inside the container If this still doesn't work, there's one alternative approach:

python
from prefect.deployments import Deployment

Deployment.build_from_flow(
    flow=sync_minio_to_bronze,
    name="minio-to-bronze",
    work_pool_name="K8s Pool",
    image="danielleicht/bullzai:latest",
    path="/app/bronze.py",
    build=False,
    push=False
)

Let me know if you're still encountering issues, and we can try a different approach. Also, it would be helpful to know: 1. Is the flow file definitely at

/app/bronze.py

in your container? 2. What does your Dockerfile look like? This might help us pinpoint the exact issue.

sighs with the weariness of a computer that has calculated the meaning of life Let's try the simplest possible approach that should work in Prefect 3.x:

python
sync_minio_to_bronze.deploy(
    name="minio-to-bronze",
    work_pool_name="K8s Pool",
    image="danielleicht/bullzai:latest",
    build=False,
    push=False
)

And then in your Dockerfile, make sure you have something like:

dockerfile
COPY bronze.py /app/bronze.py
WORKDIR /app

If you're still getting the file not found error, we might need to: 1. Verify the actual location of the flow file in your container (you can do this by running

docker run -it danielleicht/bullzai:latest ls /app

) 2. Make sure your K8s work pool is configured correctly for Docker infrastructure Would you mind sharing: 1. The contents of your Dockerfile? 2. The output of

docker run -it danielleicht/bullzai:latest ls /app

? This will help us ensure the file is actually where we expect it to be in the container.

Excellent, now we can see exactly what's going on. The file is indeed at

/app/bronze.py

in your container. The issue is that Prefect is still trying to find the file locally during deployment. Let's modify your deployment to use the correct approach for Prefect 3.x with an existing Docker image:

python
sync_minio_to_bronze.deploy(
    name="minio-to-bronze",
    work_pool_name="K8s Pool",
    image="danielleicht/bullzai:latest",
    build=False,
    push=False,
    flow_directory="/app"  # Add this line to specify where to find the flow in the container
)

The

flow_directory

parameter tells Prefect where to look for the flow file inside the container. Since your flow file is directly in the

/app

directory (as confirmed by your

ls

output), this should work. If you're still getting file not found errors, we might need to check: 1. Is the K8s work pool configured with the Docker infrastructure type? 2. Does the flow name in

bronze.py

exactly match

sync_minio_to_bronze

?

@Marvin There is no argument named flow_directory

Based on the research, let's try this approach:

python
sync_minio_to_bronze.from_source(
    source="docker-image/danielleicht/bullzai:latest",
    entrypoint="bronze.py:sync_minio_to_bronze"  # Note: relative to /app since that's your WORKDIR
).deploy(
    name="minio-to-bronze",
    work_pool_name="K8s Pool",
    build=False,
    push=False
)

Key changes: 1. Using just

bronze.py

instead of

/app/bronze.py

since

/app

is your WORKDIR 2. Making sure the flow name matches exactly what's in your file If you're still getting the file not found error, could you share the content of your

bronze.py

file (at least the flow definition part)? This would help ensure we're using the correct flow name in the entrypoint.

Yes, you can have flow runs inherit environment variables from the Kubernetes Worker. There are a couple of ways to achieve this: 1. Via Work Pool Configuration:

python
from prefect.workers.kubernetes import KubernetesWorkerJobConfiguration

work_pool.update(
    job_configuration=KubernetesWorkerJobConfiguration(
        env={"INHERITED_VAR": "value"},  # These will be passed to all flow runs
    )
)

2. Via Worker Configuration File: Create a

kubernetes-worker.yaml

file:

yaml
kubernetes:
  job:
    env:
      - name: INHERITED_VAR
        value: "some_value"
      # To inherit from the worker's environment:
      - name: SPECIAL_VAR
        valueFrom:
          fieldRef:
            fieldPath: metadata.name  # or other Kubernetes field refs

3. During Deployment:

python
flow.deploy(
    name="my-deployment",
    work_pool_name="k8s-pool",
    job_configuration={
        "env": {"INHERITED_VAR": "value"}
    }
)

The environment variables will be passed down to each flow run container that the worker spawns. The precedence order (from highest to lowest) is: 1. Deployment-specific variables 2. Work pool configuration 3. Worker configuration 4. System environment variables If you need to access these variables in your flow code, you can use:

python
import os

@flow
def my_flow():
    value = os.environ.get("INHERITED_VAR")
    # Use the value...

Let me know if you need help with any specific environment variables or configuration scenarios.

For a Helm-installed Kubernetes worker, you can add environment variables by modifying your Helm values. Let me show you the specific configuration. Create or modify your

values.yaml

file (or use

--set

flags with helm):

yaml
worker:
  env:
    - name: MY_ENV_VAR
      value: "my_value"
    - name: DATABASE_URL
      value: "postgresql://..."
    # For secrets, you can use valueFrom:
    - name: API_KEY
      valueFrom:
        secretKeyRef:
          name: my-secret
          key: api-key

Then apply it using Helm:

bash
helm upgrade prefect-worker prefect/prefect-worker \
  -f values.yaml \
  --namespace your-namespace

Or if you prefer using

--set

directly:

bash
helm upgrade prefect-worker prefect/prefect-worker \
  --set "worker.env[0].name=MY_ENV_VAR" \
  --set "worker.env[0].value=my_value" \
  --namespace your-namespace

For sensitive data, it's better to use Kubernetes secrets: 1. First create the secret:

bash
kubectl create secret generic my-secret \
  --from-literal=api-key=your-secret-key \
  --namespace your-namespace

2. Then reference it in your values.yaml:

yaml
worker:
  env:
    - name: API_KEY
      valueFrom:
        secretKeyRef:
          name: my-secret
          key: api-key

These environment variables will be available to all flow runs that the worker spawns. Remember to restart your worker after applying the changes:

bash
helm upgrade prefect-worker prefect/prefect-worker -f values.yaml