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<@ULVA73B9P> how to make sure that the prefect age...
# ask-marvin
d
@Marvin how to make sure that the prefect agent container that runs the flow.py has access to the docker socket?
m
Prefect agents are deprecated in favor of workers, so you'll need to ensure the worker containers have access to the Docker socket. To achieve this, you can follow these general steps: 1. Ensure Docker socket is shared with the container: When creating a Docker container for your Prefect worker, mount the Docker socket into the container. This allows the container to interact with the Docker daemon on the host. The Docker command to run this might look something like:
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sh
   docker run -d --name prefect-worker \
       -v /var/run/docker.sock:/var/run/docker.sock \
       prefecthq/prefect:latest
2. Set up Prefect worker correctly: Make sure your 
flow.py
is correctly set up to be executed by the worker and that the worker has the necessary permissions and configurations. Let's try and find more detailed steps for you by querying relevant documentation and resources on this topic. It seems that the Prefect documentation has several helpful bits of information regarding executing flow runs within Docker containers, and ensuring that these containers have the necessary permissions and configurations. Let’s summarize the steps and relevant details. ### Steps to Ensure Docker Socket Access for Prefect Worker Containers 1. Run Prefect Worker with Docker Socket Access: When running your Prefect worker container, mount the Docker socket from the host into the container to provide it access. Here’s an example Docker run command:
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sh
   docker run -d --name prefect-worker \
       -v /var/run/docker.sock:/var/run/docker.sock \
       prefecthq/prefect:latest
This command mounts the Docker socket into the container, allowing it to access the Docker daemon running on the host. 2. Set Up Prefect Worker Configuration: Configure the worker so that it can correctly execute the flows. This involves ensuring the worker has the correct permissions to use the Docker socket. 3. Ensure Flow Configurations are Correct: Make sure your flows are correctly set up to run in the Docker environment. This typically involves setting appropriate environment variables and ensuring the worker can access all necessary resources. 4. Monitor and Debug: Regularly monitor the logs and status of your Prefect flows to identify and resolve any issues quickly. Use tools and configurations recommended by Prefect for observability, logging, and handling errors robustly. ### Detailed Documentation and Examples - Prefect Work Pools: This document outlines how to execute flow runs within various environments, including Docker. - Dockerizing Your Python Applications: This article provides a comprehensive walkthrough on Dockerizing Python applications and ensuring they run reliably. #### Prefect Work Pools
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plaintext
Infrastructure Type | Description
Prefect Agent       | Execute flow runs on heterogeneous infrastructure using infrastructure blocks.
Process             | Execute flow runs as subprocesses on a worker. Works well for local execution when first getting started.
AWS Elastic...      | ...Requires an AWS account.
Azure Container...  | ...Requires an Azure account.
Docker              | Execute flow runs within Docker containers. Works well for managing flow execution environments via Docker images. Requires access to a running Docker daemon.
It mentions that to execute flow runs within Docker containers, access to a running Docker daemon is required, typically provided by mounting the Docker socket. #### General Docker and Prefect Errors Concerning potential issues with deployment errors or flow execution errors (like FileNotFound errors or mapped tasks triggering multiple times), check solutions and discussions on Prefect’s GitHub issues:
- Issue on Deploying Flow: Error while deploying flows, such as 
FileNotFoundError
. - Issue on Mapped Tasks Triggering Multiple Times: Problems related to mapped tasks in GKE Autopilot clusters. By following these guidelines and referring to the documentation and issues, you should be able to ensure that your Prefect worker container has the necessary Docker socket access to run your flows efficiently.
d
@Marvin sorry I use workers as well but can you clarify how can I make my prefect.yaml file under infrastructure block know that docker socket should be shared with the worker container
m
To ensure your 
prefect.yaml
file under the infrastructure block correctly configures the Docker socket to be shared with the worker container, you need to define the appropriate Docker infrastructure settings. Here’s how you can specify the Docker socket mount in the 
prefect.yaml
file: 1. Define Docker Infrastructure in 
prefect.yaml
: You need to use the 
docker
infrastructure type and specify volume mounts to share the Docker socket with the worker container. 2. Volume Mount Configuration: Specify the volume mounts in the infrastructure block to mount the Docker socket from the host to the container. Here is an example 
prefect.yaml
configuration:
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yaml
version: 2.0
flows:
  my-flow:
    name: my-flow
    parameters: {}
    schedule: null

infrastructure:
  type: docker-container
  env:
    # Any environment variables your flow might need
  image: prefecthq/prefect:latest
  networks: []
  volumes:
    - host_path: /var/run/docker.sock
      container_path: /var/run/docker.sock
In this configuration: - 
type: docker-container
indicates that the Docker container infrastructure is being used. - 
image: prefecthq/prefect:latest
specifies the Docker image for the worker container. - 
volumes
specifies the mount points: - 
host_path: /var/run/docker.sock
mounts the Docker socket from the host. - 
container_path: /var/run/docker.sock
mounts it to the same path inside the container. ### Steps to Apply this Configuration 1. Create/Modify 
prefect.yaml
: Ensure your 
prefect.yaml
file contains the above configuration within the appropriate project directory. 2. Deploy the Flow: Deploy your flow using the Prefect CLI or Prefect Cloud to apply this configuration:
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sh
   prefect deployment build my-flow.py:my_flow -n my-deployment -q default
   prefect deployment apply my-deployment-deployment.yaml
3. Start Prefect Worker: Run the Prefect worker that will pick up this flow with the correct configuration:
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   prefect worker start -q default
### Additional Resources For detailed information, refer to the Prefect documentation on Docker infrastructure and its configuration: - Prefect Infrastructure Documentation - Docker Infrastructure This setup ensures that your worker container has the necessary Docker socket access to execute flow runs that require Docker operations.
d
@Marvin I am getting this: ERROR | Task run 'pull_docker_image-0' - Finished in state Failed("Task run encountered an exception DockerException: Error while fetching server API version: ('Connection aborted.', FileNotFoundError(2, 'No such file or directory'))") when running my flow.py file that will pull an image
m
The 
FileNotFoundError: No such file or directory
error indicates that the worker container is unable to find or access the Docker socket, which means it can't communicate with the Docker daemon. To address this, ensure that the Docker socket is correctly mounted and the path is accessible from within the container. Here’s a step-by-step guide to troubleshoot and fix this issue: ### Step-by-Step Solution 1. Ensure Docker Socket is Mounted Correctly in `prefect.yaml`: Verify that your 
prefect.yaml
file mounts the Docker socket correctly:
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yaml
   version: 2.0
   flows:
     my-flow:
       name: my-flow
       parameters: {}
       schedule: null

   infrastructure:
     type: docker-container
     env:
       # Any environment variables your flow might need
     image: prefecthq/prefect:latest
     networks: []
     volumes:
       - host: /var/run/docker.sock
         container: /var/run/docker.sock
2. Check Docker Daemon Access in Container: - Run a Test Container: Start a test container with the same volume mount to ensure the Docker socket is accessible.
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     docker run -it --rm -v /var/run/docker.sock:/var/run/docker.sock alpine sh
- Inside the Container: Run a Docker command (e.g., 
docker ps
) to confirm access to the Docker daemon.
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     docker ps
If this command fails, there may be an issue with how the Docker socket is mounted or with Docker's permissions. 3. Ensure Docker is Installed Correctly in the Container: - Make sure the Docker CLI is available in the worker container. If the image doesn’t have Docker installed, you can extend the Docker image. - Create a 
Dockerfile
to extend the Prefect image:
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Dockerfile
     FROM prefecthq/prefect:latest
     RUN apt-get update && apt-get install -y <http://docker.io|docker.io>
- Build and use this image in your `prefect.yaml`:
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     docker build -t my-prefect-docker .
Update your `prefect.yaml`:
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yaml
   infrastructure:
     type: docker-container
     env:
     image: my-prefect-docker
     volumes:
       - host: /var/run/docker.sock
         container: /var/run/docker.sock
4. Validate Path and Permissions: Ensure the mounted path (
/var/run/docker.sock
) is correct and that the Docker socket has appropriate permissions. The socket should be readable and writable by the container user. ### Example Configuration Update Here’s how your 
prefect.yaml
should look after ensuring Docker is installed and the socket is mounted correctly:
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yaml
version: 2.0
flows:
  my-flow:
    name: my-flow
    parameters: {}
    schedule: null

infrastructure:
  type: docker-container
  env:
    # Any environment variables your flow might need
  image: my-prefect-docker
  networks: []
  volumes:
    - host: /var/run/docker.sock
      container: /var/run/docker.sock
Finally, rebuild your flow deployment and restart the worker to apply these changes:
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prefect deployment build my-flow.py:my_flow -n my-deployment -q default
prefect deployment apply my-deployment-deployment.yaml
prefect worker start -q default
Make sure to start the worker that will pick up this configuration. This should resolve the issue and allow the worker to successfully pull Docker images.
d
@Marvin looks like my flow fails because this my-prefect-docker doesn't have docker client binary installed to interact with the docker socket. With that being said should I build a custom image?
m
Yes, you will need a custom Docker image that includes the Docker client binary to interact with the Docker socket. Here's a step-by-step guide to building and using a custom Docker image: 1. Create a Dockerfile: Create a 
Dockerfile
that extends the Prefect base image and installs Docker CLI.
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Dockerfile
   # Use the Prefect base image
   FROM prefecthq/prefect:latest

   # Update and install Docker CLI
   RUN apt-get update && \
       apt-get install -y <http://docker.io|docker.io>
   
   # Optional: clean up to reduce image size
   RUN apt-get clean && \
       rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
2. Build the Custom Docker Image: Build the Docker image based on the 
Dockerfile
.
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   docker build -t my-prefect-docker .
3. Update 
prefect.yaml
Configuration: Update your 
prefect.yaml
to use the custom Docker image and ensure the Docker socket is mounted correctly.
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yaml
   version: 2.0
   flows:
     my-flow:
       name: my-flow
       parameters: {}
       schedule: null

   infrastructure:
     type: docker-container
     env:
       # Any environment variables your flow might need
     image: my-prefect-docker
     networks: []
     volumes:
       - host_path: /var/run/docker.sock
         container_path: /var/run/docker.sock
4. Rebuild and Redeploy Your Flow: Rebuild your flow deployment with the updated configuration.
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   prefect deployment build my-flow.py:my_flow -n my-deployment -q default
   prefect deployment apply my-deployment-deployment.yaml
5. Start the Prefect Worker: Start the Prefect worker to pick up the newly configured flow deployment.
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   prefect worker start -q default
### Example of the Complete Workflow 1. Create a 
Dockerfile
for Custom Image:
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Dockerfile
   FROM prefecthq/prefect:latest
   RUN apt-get update && \
       apt-get install -y <http://docker.io|docker.io> && \
       apt-get clean && \
       rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
2. Build the Image:
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   docker build -t my-prefect-docker .
3. Update `prefect.yaml`:
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yaml
   version: 2.0
   flows:
     my-flow:
       name: my-flow
       parameters: {}
       schedule: null

   infrastructure:
     type: docker-container
     env:
       # Any environment variables your flow might need
     image: my-prefect-docker
     networks: []
     volumes:
       - host_path: /var/run/docker.sock
         container_path: /var/run/docker.sock
4. Deploy and Start:
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   prefect deployment build my-flow.py:my_flow -n my-deployment -q default
   prefect deployment apply my-deployment-deployment.yaml
   prefect worker start -q default
This setup ensures that your Prefect worker container has the Docker client binary installed and can interact with the Docker socket to execute tasks that require Docker operations.
d
@Marvin in this prefect.yaml: version: 2.0 build: {} pull: [] deployments: - name: pull_and_run_image version: 1.0 entrypoint: "/opt/prefect/flow.py:pull_and_run_image" work_queue_name: default description: A flow to pull and run seedoo build:latest Docker container storage: {} infrastructure: type: docker-container image: dijarvrella444/prefect-agent:1.1 command: ["python", "/opt/prefect/flow.py"] volumes: - host_path: /var/run/docker.sock container_path: /var/run/docker.sock env_vars: PREFECT__LOGGING__LEVEL: "INFO" working_dir: "/opt/prefect" tags: [] parameters: {} work_pool: name: seedoo-custom-worker work_queue_name: job_variables: {} schedules: [] the volume is not being passed correctly, as I get ERROR | Flow run 'wandering-kestrel' - Finished in state Failed("Flow run encountered an exception. DockerException: Error while fetching server API version: ('Connection aborted.', FileNotFoundError(2, 'No such file or directory'))") Cannot connect to the Docker daemon at unix:///var/run/docker.sock. Is the docker daemon running?
m
It sounds like there might be an issue with how the volumes are being mounted or how the Docker daemon is accessed from within the container. Let's revisit the 
prefect.yaml
configuration to ensure everything is set up correctly and also check some details: 1. Configuration Updates: Make sure the 
prefect.yaml
mounts the volumes correctly and verifies other settings. Here's an updated configuration for your reference:
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yaml
    version: 2.0

    build: {}
    pull: []

    deployments:
      - name: pull_and_run_image
        version: 1.0
        entrypoint: "/opt/prefect/flow.py:pull_and_run_image"
        work_queue_name: default
        description: A flow to pull and run `seedoo build:latest` Docker container
        storage: {}
        infrastructure:
          type: docker-container
          image: dijarvrella444/prefect-agent:1.1
          command: ["python", "/opt/prefect/flow.py"]
          volumes:
            - host: /var/run/docker.sock
              container: /var/run/docker.sock
          env_vars:
            PREFECT__LOGGING__LEVEL: "INFO"
          working_dir: "/opt/prefect"
        tags: []
        parameters: {}
        work_pool:
          name: seedoo-custom-worker
          work_queue_name:
          job_variables: {}
        schedules: []
Note: - Corrected 
volumes
keys to 
host
and 
container
. - Confirm the paths are correct and the Docker daemon is running on the host machine. 2. Verify Docker Daemon: Ensure that the Docker daemon is running on your host system:
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sh
    sudo systemctl status docker
If not running, start the Docker daemon:
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    sudo systemctl start docker
3. Test Docker Volume Mounting: Verify if the socket is correctly accessible from a test container:
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    docker run -it --rm -v /var/run/docker.sock:/var/run/docker.sock alpine sh
Within the container, check Docker access:
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    docker ps
This should list running containers. If it does not, there might be a permissions issue or the socket may not be correctly mounted. 4. Build and Push Custom Docker Image (if necessary): If you're using a custom image, ensure it has Docker CLI installed. Here's a sample 
Dockerfile
for your custom image:
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Dockerfile
    FROM prefecthq/prefect:latest

    RUN apt-get update && \
        apt-get install -y <http://docker.io|docker.io> && \
        apt-get clean && \
        rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
Build and push your custom image:
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    docker build -t my-prefect-docker .
    docker tag my-prefect-docker dijarvrella444/prefect-agent:1.1
    docker push dijarvrella444/prefect-agent:1.1
5. Deploy and Restart Prefect Worker: Build and apply your deployment configuration:
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    prefect deployment build my-flow.py:pull_and_run_image -n my-deployment -q default
    prefect deployment apply my-deployment-deployment.yaml
Start the Prefect worker:
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    prefect worker start -q default
6. Logs and Diagnostics: - Check worker logs for any errors related to volume mounts or Docker daemon access. - Use the 
docker logs <worker-container-id>
command to inspect logs for more detailed information. If after these steps you are still encountering issues, please double-check the paths in your volume mounting and ensure there are no permission issues that might block access to the Docker socket.
d
@Marvin how to fix the following 152950.075 | ERROR | prefect.flow_runs.worker - Failed to submit flow run '8884a38b-9131-46af-bf70-052c8f878bf8' to infrastructure. Traceback (most recent call last): File "/home/seedooadmin/.conda/envs/prefect-agent/lib/python3.12/site-packages/prefect/workers/base.py", line 906, in _submit_run_and_capture_errors configuration = await self._get_configuration(flow_run) File "/home/seedooadmin/.conda/envs/prefect-agent/lib/python3.12/site-packages/prefect/workers/base.py", line 986, in _get_configuration configuration = await self.job_configuration.from_template_and_values( File "/home/seedooadmin/.conda/envs/prefect-agent/lib/python3.12/site-packages/prefect/client/utilities.py", line 100, in with_injected_client return await fn(*args, **kwargs) File "/home/seedooadmin/.conda/envs/prefect-agent/lib/python3.12/site-packages/prefect/workers/base.py", line 149, in from_template_and_values return cls(**populated_configuration) File "/home/seedooadmin/.conda/envs/prefect-agent/lib/python3.12/site-packages/pydantic/v1/main.py", line 341, in init raise validation_error pydantic.v1.error_wrappers.ValidationError: 1 validation error for DockerWorkerJobConfiguration volumes value is not a valid list (type=type_error.list)
m
Your message was too long by 282 tokens - please shorten it and try again. For reference, here's your message at the allowed limit:
it looked like the worker had to be updated with these settings rather than prefect.yaml.
Anyway how to fix this: 152950.002 | INFO | prefect.flow_runs.worker - Worker 'DockerWorker b554e242-6740-4e55-bb73-3d86057c8cc8' submitting flow run '8884a38b-9131-46af-bf70-052c8f878bf8' 152950.075 | ERROR | prefect.flow_runs.worker - Failed to submit flow run '8884a38b-9131-46af-bf70-052c8f878bf8' to infrastructure. Traceback (most recent call last): File "/home/seedooadmin/.conda/envs/prefect-agent/lib/python3.12/site-packages/prefect/workers/base.py", line 906, in _submit_run_and_capture_errors configuration = await self._get_configuration(flow_run) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/seedooadmin/.conda/envs/prefect-agent/lib/python3.12/site-packages/prefect/workers/base.py", line 986, in _get_configuration configuration = await self.job_configuration.from_template_and_values( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/seedooadmin/.conda/envs/prefect-agent/lib/python3
Your message was too long by 60 tokens - please shorten it and try again. For reference, here's your message at the allowed limit:
how to fix the following
152950.075 | ERROR | prefect.flow_runs.worker - Failed to submit flow run '8884a38b-9131-46af-bf70-052c8f878bf8' to infrastructure. Traceback (most recent call last): File "/home/seedooadmin/.conda/envs/prefect-agent/lib/python3.12/site-packages/prefect/workers/base.py", line 906, in _submit_run_and_capture_errors configuration = await self._get_configuration(flow_run) File "/home/seedooadmin/.conda/envs/prefect-agent/lib/python3.12/site-packages/prefect/workers/base.py", line 986, in _get_configuration configuration = await self.job_configuration.from_template_and_values( File "/home/seedooadmin/.conda/envs/prefect-agent/lib/python3.12/site-packages/prefect/client/utilities.py", line 100, in with_injected_client return await fn(*args, **kwargs) File "/home/seedooadmin/.conda/envs/prefect-agent/lib/python3.12/site-packages/prefect/workers/base.py", line 149, in from_template_and_values return cls(**populated_configuration) File "/home/seedooadmin/.conda/envs/prefect-agent/lib/python3.12/site-pack
d
@Marvin 153546.201 | ERROR | prefect.flow_runs.worker - Failed to submit flow run '9d6e3aae-f509-485a-89d1-67d92002d4f3' to infrastructure. File "/home/seedooadmin/.conda/envs/prefect-agent/lib/python3.12/site-packages/prefect/workers/base.py", line 986, in _get_configuration configuration = await self.job_configuration.from_template_and_values( File "/home/seedooadmin/.conda/envs/prefect-agent/lib/python3.12/site-packages/prefect/client/utilities.py", line 100, in with_injected_client return await fn(*args, **kwargs) File "/home/seedooadmin/.conda/envs/prefect-agent/lib/python3.12/site-packages/prefect/workers/base.py", line 149, in from_template_and_values return cls(**populated_configuration) File "/home/seedooadmin/.conda/envs/prefect-agent/lib/python3.12/site-packages/pydantic/v1/main.py", line 341, in init raise validation_error pydantic.v1.error_wrappers.ValidationError: 1 validation error for DockerWorkerJobConfiguration volumes value is not a valid list (type=type_error.list)
m
Your message was too long by 90 tokens - please shorten it and try again. For reference, here's your message at the allowed limit:
153546.201 | ERROR | prefect.flow_runs.worker - Failed to submit flow run '9d6e3aae-f509-485a-89d1-67d92002d4f3' to infrastructure.
Traceback (most recent call last): File "/home/seedooadmin/.conda/envs/prefect-agent/lib/python3.12/site-packages/prefect/workers/base.py", line 906, in _submit_run_and_capture_errors configuration = await self._get_configuration(flow_run) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/seedooadmin/.conda/envs/prefect-agent/lib/python3.12/site-packages/prefect/workers/base.py", line 986, in _get_configuration configuration = await self.job_configuration.from_template_and_values( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/seedooadmin/.conda/envs/prefect-agent/lib/python3.12/site-packages/prefect/client/utilities.py", line 100, in with_injected_client return await fn(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/seedooadmin/.conda/envs/prefect-agent/lib/python3.12/site-packages/prefect/workers/base.py", line 149, in from_template_and_values return cls(**populated_configuration) ^
Your message was too long by 17 tokens - please shorten it and try again. For reference, here's your message at the allowed limit:
153546.201 | ERROR | prefect.flow_runs.worker - Failed to submit flow run '9d6e3aae-f509-485a-89d1-67d92002d4f3' to infrastructure.
File "/home/seedooadmin/.conda/envs/prefect-agent/lib/python3.12/site-packages/prefect/workers/base.py", line 986, in _get_configuration configuration = await self.job_configuration.from_template_and_values( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/seedooadmin/.conda/envs/prefect-agent/lib/python3.12/site-packages/prefect/client/utilities.py", line 100, in with_injected_client return await fn(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/seedooadmin/.conda/envs/prefect-agent/lib/python3.12/site-packages/prefect/workers/base.py", line 149, in from_template_and_values return cls(**populated_configuration) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/seedooadmin/.conda/envs/prefect-agent/lib/python3.12/site-packages/pydantic/v1/main.py", line 341, in init raise validation_error pydantic.v1.error_wrappers.ValidationError: 1 validation error for DockerWorkerJobConfiguration
The error message you're receiving indicates that the 
volumes
field in your 
prefect.yaml
configuration is not being recognized as a valid list. The volumes field should be defined as a list of dictionaries, with each dictionary specifying the 
host
and 
container
paths. Here's how you can correct your 
prefect.yaml
file: ### Correct 
prefect.yaml
Configuration 1. Ensure the volumes field is correctly specified as a list. 2. Make sure that the 
type
of infrastructure is correctly specified. Here’s an updated version of the 
prefect.yaml
file:
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yaml
version: 2.0

build: {}
pull: []

deployments:
  - name: pull_and_run_image
    version: 1.0
    entrypoint: "/opt/prefect/flow.py:pull_and_run_image"
    work_queue_name: default
    description: A flow to pull and run seedoo build:latest Docker container
    storage: {}
    infrastructure:
      type: docker-container
      image: dijarvrella444/prefect-agent:1.1
      command: ["python", "/opt/prefect/flow.py"]
      volumes:
        - host: /var/run/docker.sock
          container: /var/run/docker.sock
      env_vars:
        PREFECT__LOGGING__LEVEL: "INFO"
      working_dir: "/opt/prefect"
    tags: []
    parameters: {}
    work_pool:
      name: seedoo-custom-worker
      work_queue_name:
      job_variables: {}
    schedules: []
### Steps for Implementation 1. Verify Volume Specification: Ensure that the 
volumes
field is correctly defined as a list of dictionaries. 2. Check Dependencies: Ensure all your dependencies, such as Docker, Python, and Prefect, are correctly installed and compatible. 3. Deploy and Restart: Rebuild and apply your deployment configuration:
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sh
   prefect deployment build my-flow.py:pull_and_run_image -n my-deployment -q default
   prefect deployment apply my-deployment-deployment.yaml
Start the Prefect worker:
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sh
   prefect worker start -q default
Double-check the indentation and structure of your 
prefect.yaml
. Each section should be correctly indented according to YAML syntax to avoid any parsing issues. Once these steps are taken, your configuration should recognize the 
volumes
field as a valid list, and the Prefect worker should be able to process it without the validation error.
d
@Marvin I still get this error: File "/home/seedooadmin/.conda/envs/prefect-agent/lib/python3.12/site-packages/pydantic/v1/main.py", line 341, in init raise validation_error pydantic.v1.error_wrappers.ValidationError: 1 validation error for DockerWorkerJobConfiguration volumes value is not a valid list (type=type_error.list)
m
It appears there is still an issue with the 
volumes
field being recognized as a valid list. Let's ensure that all configurations are properly formatted and explicitly defined according to Prefect's expected schema. ### Ensure Proper List Format In 
prefect.yaml
, the 
volumes
specification must be an actual list. Here’s a corrected example:
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yaml
version: 2.0

build: {}
pull: []

deployments:
  - name: pull_and_run_image
    version: 1.0
    entrypoint: "/opt/prefect/flow.py:pull_and_run_image"
    work_queue_name: default
    description: A flow to pull and run seedoo build:latest Docker container
    storage: {}
    infrastructure:
      type: docker-container
      image: dijarvrella444/prefect-agent:1.1
      command: ["python", "/opt/prefect/flow.py"]
      volumes:
        - host: /var/run/docker.sock
          container: /var/run/docker.sock
      env_vars:
        PREFECT__LOGGING__LEVEL: "INFO"
      working_dir: "/opt/prefect"
    tags: []
    parameters: {}
    work_pool:
      name: seedoo-custom-worker
      work_queue_name:
      job_variables: {}
    schedules: []
### Custom Image with Prefect and Docker If you are using a custom image, make sure it includes Prefect and Docker. Example 
Dockerfile
for a custom image:
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Dockerfile
FROM prefecthq/prefect:latest

# Install Docker CLI
RUN apt-get update && \
    apt-get install -y <http://docker.io|docker.io> && \
    apt-get clean && \
    rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*

# Optional: Ensure Docker is in the path
ENV PATH="/usr/bin/docker:${PATH}"
### Validation and Testing To ensure the configuration works: 1. Build the Docker image:
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sh
   docker build -t dijarvrella444/prefect-agent:1.1 .
2. Check the Docker socket access:
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sh
   docker run -it --rm -v /var/run/docker.sock:/var/run/docker.sock dijarvrella444/prefect-agent:1.1
   docker ps
3. Deploy the Flow:
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sh
   prefect deployment build my-flow.py:pull_and_run_image -n my-deployment --tag dijarvrella444/prefect-agent:1.1
   prefect deployment apply my-deployment-deployment.yaml
4. Start the Prefect Worker:
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sh
   prefect worker start -q seedoo-custom-worker
### Debugging with Logs If errors persist, inspect the logs of the Prefect worker to gather more details:
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sh
docker logs <worker_container_id>
Or, place logging statements within your 
flow.py
to capture environmental details. Here's an example:
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python
import docker
import logging

logger = logging.getLogger(__name__)

try:
    client = docker.from_env()
    <http://logger.info|logger.info>(client.version())
except Exception as e:
    logger.error(f"Error connecting to Docker: {e}")
### Confirm Docker Daemon Ensure the Docker daemon is running and accessible.
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sh
sudo systemctl status docker
# If not running
sudo systemctl start docker
This comprehensive approach ensures that the configuration is correct, your custom Docker image includes the necessary tools, and debug steps are clear. Applying these updates should resolve the 
volumes
validation issue and ensure Docker operations within the flow work as expected.
d
@Marvin do I need to mount the volume on the worker pool or if I specify the volume on the prefect.yaml that is more than required?
m
You only need to specify the volume mount in the 
prefect.yaml
configuration for your deployment. This configuration is sufficient as it instructs the infrastructure (in this case, the Docker container) to mount the specified volumes when the flow run is executed. There is no need to mount the volume on the worker pool itself separately. ### Let's Double-Check Your Configuration 1. Ensure 
prefect.yaml
Configuration: The 
prefect.yaml
should explicitly mount the Docker socket as:
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yaml
    version: 2.0

    build: {}
    pull: []

    deployments:
      - name: pull_and_run_image
        version: 1.0
        entrypoint: "/opt/prefect/flow.py:pull_and_run_image"
        work_queue_name: default
        description: A flow to pull and run seedoo build:latest Docker container
        storage: {}
        infrastructure:
          type: docker-container
          image: dijarvrella444/prefect-agent:1.1
          command: ["python", "/opt/prefect/flow.py"]
          volumes:
            - host: /var/run/docker.sock
              container: /var/run/docker.sock
          env_vars:
            PREFECT__LOGGING__LEVEL: "INFO"
          working_dir: "/opt/prefect"
        tags: []
        parameters: {}
        work_pool:
          name: seedoo-custom-worker
          work_queue_name:
          job_variables: {}
        schedules: []
2. Test Custom Docker Image: Ensure your custom Docker image has Docker CLI installed and can access the Docker daemon:
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Dockerfile
    FROM prefecthq/prefect:latest

    # Install Docker CLI
    RUN apt-get update && \
        apt-get install -y <http://docker.io|docker.io> && \
        apt-get clean && \
        rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*

    # Optional: Ensure Docker is in the path
    ENV PATH="/usr/bin/docker:${PATH}"
Build and push the image:
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sh
    docker build -t dijarvrella444/prefect-agent:1.1 .
    docker push dijarvrella444/prefect-agent:1.1
3. Deploy and Run the Flow: Build and apply the deployment configuration:
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sh
    prefect deployment build my-flow.py:pull_and_run_image -n my-deployment -q default
    prefect deployment apply my-deployment-deployment.yaml
Start the Prefect worker:
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sh
    prefect worker start -q default
4. Monitoring and Logs: Check logs if there are issues:
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sh
    docker logs <worker_container_id>
Use logging within your flow for additional debugging:
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python
    import docker
    import logging

    logger = logging.getLogger(__name__)

    try:
        client = docker.from_env()
        <http://logger.info|logger.info>(client.version())
    except Exception as e:
        logger.error(f"Error connecting to Docker: {e}")
### Summary: When using Prefect with Docker, the 
prefect.yaml
configuration should suffice to pass necessary volume mounts and environment settings, including Docker socket mounting, for flow runs. Defining these within 
prefect.yaml
ensures that each flow run executed using that deployment configuration will have these settings applied. By following these steps, the worker should be able to access the Docker daemon correctly and execute Docker operations as part of your flow.
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