@Marvin ERROR | Flow run 'stirring-mayfly' - Flow could not be retrieved from deployment.

It seems you're experiencing an issue where your flow run cannot retrieve the flow from the deployment. Here are a few potential causes and solutions: 1. Storage Configuration: Ensure that the appropriate storage file system library is installed prior to building your deployment. For example, if using AWS S3, the

s3fs

library is required. Detailed information can be found in the Prefect documentation on block-based deployment storage. 2. Path Configuration: There might be an issue with how paths are specified in the storage block. An example issue reported on GitHub mentions that specifying folders incorrectly could lead to flow retrieval failures (GitHub Issue #13062). 3. Private Repository Access: If you're using a private GitHub repository for flow code, ensure that the personal access token is correctly configured. An error log example highlights that an incorrect configuration could lead to failed flow retrieval (GitHub Issue #8310). ### Summary of Steps to Troubleshoot: 1. Verify that the correct storage file system library is installed. 2. Double-check the path configuration in your storage block. 3. If using a private repository, ensure that the access token is properly configured. For more detailed debugging, you might need to check the deployment configuration in your

deployment.yaml

file and ensure all paths and access permissions are correctly specified. If you continue to face issues, I recommend visiting the linked GitHub issues for similar reported problems and their discussions.

@Marvin here is my prefect.yaml file: cat prefect.yaml version: 2.0 build: {} pull: {} deployments: - name: pull_and_run_image version: 1.0 entrypoint: "flow.py:pull_and_run_image" work_queue_name: default description: A flow to pull and run nginx:latest Docker container storage: {} infrastructure: type: docker-container image: seedoo-prefect-agent:latest tags: [] parameters: {} work_pool: name: seedoo-custom-worker work_queue_name: job_variables: {} schedules: [] build: pull: - prefect.deployments.steps.set_working_directory: directory: /opt/prefect

Your

prefect.yaml

file appears to be set up for deploying a flow using a custom Docker image. There are a few points to address that might be causing the error "Flow could not be retrieved from deployment." ### Things to Check: 1. Storage Specification: You have an empty storage block (

storage: {}

). Ensure that you specify where the flow is stored, for example, using an S3 bucket or other supported storage systems. 2. Correct Configuration Paths: Verify that paths provided in the YAML file are valid and accessible, especially the

entrypoint

path. 3. Infrastructure Configuration: Check if the infrastructure Docker container image

seedoo-prefect-agent:latest

is correctly built and available. 4. Working Directory: Ensure the working directory

/opt/prefect

is correctly set up in your Docker image. ### Example YAML with Storage Configuration: Here's a modified example that specifies S3 storage:

yaml
version: 2.0

build: {}

pull: {}

deployments:
- name: pull_and_run_image
  version: 1.0
  entrypoint: "flow.py:pull_and_run_image"
  work_queue_name: default
  description: A flow to pull and run nginx:latest Docker container
  storage:
    block: s3/my-bucket/flows
  infrastructure:
    type: docker-container
    image: seedoo-prefect-agent:latest
  tags: []
  parameters: {}
  work_pool:
    name: seedoo-custom-worker
    work_queue_name:
    job_variables: {}
  schedules: []
  build:
  pull:
  - prefect.deployments.steps.set_working_directory:
    directory: /opt/prefect

### External Dependencies: Ensure that: - The

s3fs

library is installed if using S3 storage. - You've configured the access and permissions correctly for S3 or the relevant storage backend used. ### Additional Documentation: - Prefect Block-Based Deployments - Deployments YAML Specification ### Final Steps: 1. Validate your

prefect.yaml

file. 2. Verify storage configurations. 3. Ensure the Docker image and working directory are properly set up. This should help in solving the "Flow could not be retrieved from deployment" error. If the issue persists, please provide more details or logs for further assistance.

@Marvin here is checking what my container is running: docker start stirring-mayfly && docker exec -it stirring-mayfly pwd && ls -la && cat flow.py stirring-mayfly /opt/prefect total 16 drwx------ 2 seedooadmin seedooadmin 4096 Jun 21 14:49 . drwxr-xr-x 7 root root 4096 Jun 21 13:04 .. -rw------- 1 seedooadmin users 3052 Jun 21 14:49 flow.py -rw------- 1 seedooadmin users 2537 Jun 21 14:23 flow.py.bak

It seems some of the necessary files are present in the

/opt/prefect

directory in your Docker container. To troubleshoot further, let's validate a few points: ### 1. Check Flow File Location: Ensure the flow file (

flow.py

) is located where Prefect expects it, based on your entrypoint configuration. ### 2. Verify Entrypoint Specification: The

entrypoint

key in your

prefect.yaml

should match the module and function names expected in

flow.py

. ### 3. Docker Permissions: Ensure that there are no permission issues preventing Prefect from reading the flow file. #### Updated

prefect.yaml

Ensure the entrypoint is correctly mapped, and no misspellings or path issues exist:

yaml
version: 2.0

build: {}

pull: {}

deployments:
- name: pull_and_run_image
  version: 1.0
  entrypoint: "flow.py:pull_and_run_image"  # Ensure this matches the actual function name
  work_queue_name: default
  description: A flow to pull and run nginx:latest Docker container
  storage:
    block: local-file-system
    directory: /opt/prefect  # specifying storage location
  infrastructure:
    type: docker-container
    image: seedoo-prefect-agent:latest
  tags: []
  parameters: {}
  work_pool:
    name: seedoo-custom-worker
    work_queue_name:
    job_variables: {}
  schedules: []
  build:
  pull:
  - prefect.deployments.steps.set_working_directory:
    directory: /opt/prefect

### Verify the Flow Function: Ensure the function

pull_and_run_image

exists in

flow.py

and is correctly defined. ### Example

flow.py

Make sure your flow is defined similarly to this:

python
from prefect import flow, task

@task
def pull_image():
    # Pull Docker image logic
    pass

@task
def run_image():
    # Run Docker image logic
    pass

@flow
def pull_and_run_image():
    pull_image()
    run_image()

if __name__ == "__main__":
    pull_and_run_image()

### Final Steps: 1. Validate the

flow.py

content: - The function

pull_and_run_image

should be defined as shown. 2. Ensure the

entrypoint

matches the function definition. 3. Confirm that the file permissions allow Prefect to read the files. After verifying these points, try redeploying the flow and triggering a new run. This should help resolve the "Flow could not be retrieved from deployment" issue. If the error persists, please share any additional logs for deeper analysis.

@Marvin prefect.yaml version: 2.0 build: {} pull: {} deployments: - name: pull_and_run_image version: 1.0 entrypoint: "flow.py:pull_and_run_image" work_queue_name: default description: A flow to pull and run nginx:latest Docker container storage: {} infrastructure: type: docker-container image: dijarvrella444/prefect-agent:1.0 tags: [] parameters: {} work_pool: name: seedoo-custom-worker work_queue_name: job_variables: {} schedules: [] build: pull: - prefect.deployments.steps.set_working_directory: directory: /opt/prefect flow fails: 160332.284 | ERROR | Flow run 'nonchalant-serval' - Flow could not be retrieved from deployment. docker start nonchalant-serval && docker exec -it nonchalant-serval pwd && ls -la /opt/prefect total 16 drwx------ 2 seedooadmin seedooadmin 4096 Jun 21 14:49 . drwxr-xr-x 7 root root 4096 Jun 21 13:04 .. -rw------- 1 seedooadmin users 3052 Jun 21 14:49 flow.py

Your message was too long by 100 tokens - please shorten it and try again. For reference, here's your message at the allowed limit:

updated prefect.yaml:

cat prefect.yaml version: 2.0 build: {} pull: {} deployments: - name: pull_and_run_image version: 1.0 entrypoint: "flow.py:pull_and_run_image" work_queue_name: default description: A flow to pull and run nginx:latest Docker container storage: {} infrastructure: type: docker-container image: dijarvrella444/prefect-agent:1.0 tags: [] parameters: {} work_pool: name: seedoo-custom-worker work_queue_name: job_variables: {} schedules: [] build: pull: - prefect.deployments.steps.set_working_directory: directory: /opt/prefect flow fails: 160330.202 | INFO | prefect.flow_runs.runner - Opening process... /opt/conda/envs/prefect/lib/python3.10/runpy.py126 RuntimeWarning: 'prefect.engine' found in sys.modules after import of package 'prefect', but prior to execution of 'prefect.engine'; this may result in unpredictable behaviour warn(RuntimeWarning(msg)) 160332.284 | ERROR | Flow run 'nonchalant-serval' - Flow could not be retrieved from deployment. Verification steps docker start nonchalant-serval && docker exec -it non