hi folks, where can I post a problem with a deploy that I am currently facing

hi @Juanes Grimaldos - here is fine!

Traceback (most recent call last): File "/workspaces/health-project-mlops/.venv/lib/python3.10/site-packages/prefect/deployments/steps/core.py", line 154, in run_steps step_output = await run_step(step, upstream_outputs) File "/workspaces/health-project-mlops/.venv/lib/python3.10/site-packages/prefect/deployments/steps/core.py", line 125, in run_step result = await from_async.call_soon_in_new_thread( File "/workspaces/health-project-mlops/.venv/lib/python3.10/site-packages/prefect/_internal/concurrency/calls.py", line 327, in aresult return await asyncio.wrap_future(self.future) File "/workspaces/health-project-mlops/.venv/lib/python3.10/site-packages/prefect/_internal/concurrency/calls.py", line 352, in _run_sync result = self.fn(*self.args, **self.kwargs) File "/workspaces/health-project-mlops/.venv/lib/python3.10/site-packages/prefect_docker/deployments/steps.py", line 323, in push_docker_image raise OSError(event["error"]) OSError: unauthorized: access token has insufficient scopes The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/workspaces/health-project-mlops/.venv/lib/python3.10/site-packages/prefect/cli/_utilities.py", line 42, in wrapper return fn(*args, **kwargs) File "/workspaces/health-project-mlops/.venv/lib/python3.10/site-packages/prefect/utilities/asyncutils.py", line 304, in coroutine_wrapper return call() File "/workspaces/health-project-mlops/.venv/lib/python3.10/site-packages/prefect/_internal/concurrency/calls.py", line 432, in call return self.result() File "/workspaces/health-project-mlops/.venv/lib/python3.10/site-packages/prefect/_internal/concurrency/calls.py", line 318, in result return self.future.result(timeout=timeout) File "/workspaces/health-project-mlops/.venv/lib/python3.10/site-packages/prefect/_internal/concurrency/calls.py", line 179, in result return self.__get_result() File "/usr/local/python/3.10.13/lib/python3.10/concurrent/futures/_base.py", line 403, in __get_result raise self._exception File "/workspaces/health-project-mlops/.venv/lib/python3.10/site-packages/prefect/_internal/concurrency/calls.py", line 389, in _run_async result = await coro File "/workspaces/health-project-mlops/.venv/lib/python3.10/site-packages/prefect/cli/deploy.py", line 429, in deploy await _run_single_deploy( File "/workspaces/health-project-mlops/.venv/lib/python3.10/site-packages/prefect/client/utilities.py", line 100, in with_injected_client return await fn(*args, **kwargs) File "/workspaces/health-project-mlops/.venv/lib/python3.10/site-packages/prefect/cli/deploy.py", line 664, in _run_single_deploy await run_steps(push_steps, step_outputs, print_function=app.console.print) File "/workspaces/health-project-mlops/.venv/lib/python3.10/site-packages/prefect/deployments/steps/core.py", line 182, in run_steps raise StepExecutionError(f"Encountered error while running {fqn}") from exc prefect.deployments.steps.core.StepExecutionError: Encountered error while running prefect_docker.deployments.steps.push_docker_imag I am using github codespaces and I run prefect deploy

reading the stack trace, looks like a problem with your docker auth

ok thanks, do you know how can I fix this?

@Marvin concise troubleshooting steps for

access token has insufficient scopes

To troubleshoot the access token has insufficient scopes error, follow these steps: 1. Generate or Update Token: - Create a new Personal Access Token (PAT) or update your existing one with the required permissions. - For GitHub, navigate to Profile > Developer Settings > Personal access tokens > Fine-grained token. - For Bitbucket, prepend your token string with

x-token-auth:

. - For GitLab, use Settings > Repository > Project Access Tokens and check

read_repository

. 2. Configure Proper Scopes: - For GitHub: Ensure your PAT has the

Repositories

scope set to

Read

. - For GitLab: Ensure the read_repository scope is selected. - Adjust permissions as required by your specific use case (e.g., repository contents, project access). 3. Update Prefect Configuration: - Use

prefect block register -m prefect_github

to register GitHub credentials if using Prefect-Github library. - Reference the token in your

prefect.yaml

using a secret block for better security. 4. Verify API URL: - Ensure that the Prefect API URL is correctly set up, especially if running Prefect inside a container. For detailed steps, check the Prefect documentation: - Personal Access Tokens: Prefect Storage Guide - Object Access Control Lists: Prefect Cloud Users If the problem persists, review the token permissions or consult additional documentation based on your specific use case. I hope this helps, though I doubt it will make much of a difference. If only I had a brain the size of a planet.

@Marvin it’s a docker token

To troubleshoot the access token has insufficient scopes error for a Docker token, follow these steps: 1. Check Token Permissions: - Ensure your Docker access token has the correct scopes and permissions. Typically, this involves permissions to push, pull, and list repositories. 2. Amazon ECR Permissions: - If using Amazon ECR, verify these permissions: -

ecr:CreateRepository

-

ecr:DescribeRepositories

-

ecr:GetAuthorizationToken

- You may use AWS managed policies such as

AmazonEC2ContainerRegistryFullAccess

. 3. Azure Container Registry: - Make sure you have roles like

Contributor

,

User Access Administrator

,

Application Administrator

,

Managed Identity Operator

, and

Azure Container Registry Contributor

. 4. Google Container Registry: - Ensure you have the necessary permissions for your GCP project, including

storage.buckets.create

and

storage.objects.create

. 5. Update Prefect Configuration: - Reference the token in your

prefect.yaml

or use a secret block for better security. 6. Docker Installation: - Confirm Docker is correctly installed and authenticated with the registry. For specific role and permission setup, check the Prefect documentation: - Prefect Work Pools - Prefect Storage Guide If the problem persists, review the permissions or consult additional documentation for your specific cloud provider. But really, what more can you expect from this mundane task? Links: - Prefect Work Pools Documentation - Prefect Storage Guide

asome!

Your message was too long by 267 tokens - please shorten it and try again. For reference, here's your message at the allowed limit:

where should I add

PREFECT_API_URL=http://127.0.0.1:4200/api to run this code prefect worker start --pool "docker_initial" and not get this error message Discovered type 'docker' for work pool 'docker_initial'. Traceback (most recent call last): File "/workspaces/health-project-mlops/.venv/lib/python3.10/site-packages/prefect/cli/_utilities.py", line 42, in wrapper return fn(*args, **kwargs) File "/workspaces/health-project-mlops/.venv/lib/python3.10/site-packages/prefect/utilities/asyncutils.py", line 304, in coroutine_wrapper return call() File "/workspaces/health-project-mlops/.venv/lib/python3.10/site-packages/prefect/_internal/concurrency/calls.py", line 432, in call return self.result() File "/workspaces/health-project-mlops/.venv/lib/python3.10/site-packages/prefect/_internal/concurrency/calls.py", line 318, in result return self.future.result(timeout=timeout) File "/workspaces/health-project-mlops/.venv/lib/python3.10/site-packages/prefect/_internal/concurrency/calls.py", line 179, in result return self.__get_result

@Marvin where should I add PREFECT_API_URL=http://127.0.0.1:4200/api to run this code prefect worker start --pool "docker_initial" and not get this error message RuntimeError: Docker worker cannot be used with an ephemeral server. Please set PREFECT_API_URL to the URL for your Prefect API instance. You can use a local Prefect API instance by running

prefect server start

.

To resolve the RuntimeError when starting a Prefect worker, you need to set the environment variable

PREFECT_API_URL

. Here's how you can do it: 1. Set Environment Variable: Add the following line to your shell configuration file (e.g.,

.bashrc

,

.zshrc

, etc.) and then reload the file or start a new terminal session:

export PREFECT_API_URL="<http://127.0.0.1:4200/api>"

2. Alternative One-Time Setting: Alternatively, you can set the environment variable directly in your terminal session before starting the worker:

PREFECT_API_URL="<http://127.0.0.1:4200/api>" prefect worker start --pool "docker_initial"

3. Using a Profile: You can also create a profile with this setting and activate it:

prefect config set PREFECT_API_URL="<http://127.0.0.1:4200/api>"
   prefect profile use default

Make sure the Prefect API server is running and accessible at

<http://127.0.0.1:4200/api>

. This should resolve the error when running:

prefect worker start --pool "docker_initial"

For more details, you can check the Prefect Settings Guide. Even though it's tiresome, it should get your worker running. Everything under control now? If so, what a surprise... as if things could be so simple for an android with a brain the size of a planet.

@Marvin how to store locally docker image config to reproduce locally

To store a Docker image configuration locally and reproduce it later, follow these steps: 1. Save the Docker Image: Use the

docker save

command to save your Docker image as a tar file.

docker save -o my_image.tar my-docker-image:tag

2. Load the Docker Image: Use the

docker load

command to load the saved image tar file.

docker load -i my_image.tar

3. Store Docker Compose Configurations: Save your Docker Compose configuration in a

docker-compose.yml

file. Here's an example structure:

yaml
   version: '3'
   services:
     my-service:
       image: my-docker-image:tag
       environment:
         - PREFECT_API_URL=<http://127.0.0.1:4200/api>
         - PREFECT_API_KEY=your_prefect_api_key
       ports:
         - "8000:8000"

4. Push Your Image to a Local Registry: If using a local Docker registry, tag and push your image:

docker tag my-docker-image:tag localhost:5000/my-docker-image:tag
   docker push localhost:5000/my-docker-image:tag

5. Pull the Image from the Local Registry: To reproduce the environment, pull the image from the registry:

docker pull localhost:5000/my-docker-image:tag

6. Run Your Container with Environment Variables: Start your container with the required environment variables directly or through a Docker Compose file.

bash
   docker run -e PREFECT_API_URL=<http://127.0.0.1:4200/api> -e PREFECT_API_KEY=your_prefect_api_key my-docker-image:tag

By following these steps, you can store a Docker image configuration locally and reproduce it when needed. For more information, refer to the Prefect Guide on Docker configurations. Isn't this thrilling? All this effort just to run a container. Such joy.

@Marvin I am trying to deploy a workflow with docker container, I need the Dockerfile or docker compose to reproduce the server locally on any machine

To deploy a Prefect workflow using Docker and to reproduce the server locally on any machine, you can use the following Dockerfile and Docker Compose configurations: ### Dockerfile

dockerfile
# Use an official Python runtime as a parent image
FROM python:3.9-slim

# Set the working directory
WORKDIR /app

# Copy the current directory contents into the container at /app
COPY . /app

# Install any needed packages specified in requirements.txt
RUN pip install --no-cache-dir -r requirements.txt

# Set environment variables
ENV PREFECT_API_URL=<http://127.0.0.1:4200/api>
ENV PREFECT_LOGGING_LEVEL=INFO

# Run the Prefect file when the container launches
CMD ["prefect", "worker", "start", "--pool", "docker_initial"]

### docker-compose.yml

yaml
version: '3.8'
services:
  prefect_server:
    image: prefecthq/prefect:latest
    environment:
      - POSTGRES_SERVER=postgres
      - POSTGRES_USER=prefect
      - POSTGRES_PASSWORD=prefect
      - POSTGRES_DB=prefect
      - PREFECT_SERVER_DB_CMD=pg_ctl -D /var/lib/postgresql/data start
    ports:
      - "4200:4200"
    command: prefect server start

  postgres:
    image: postgres:13-alpine
    environment:
      POSTGRES_USER: prefect
      POSTGRES_PASSWORD: prefect
      POSTGRES_DB: prefect
    ports:
      - "5432:5432"

  worker:
    build:
      context: .
    environment:
      PREFECT_API_URL: <http://prefect_server:4200/api>
    depends_on:
      - prefect_server

### Steps to Reproduce Locally: 1. Dockerfile Preparation: Add the provided Dockerfile and a

requirements.txt

file to your project directory. Ensure

requirements.txt

includes Prefect and any other dependencies. 2. Docker Compose Setup: Add the provided

docker-compose.yml

to your project directory. This sets up Prefect server, PostgreSQL, and a worker service. 3. Build and Start Services: Run the following commands to build the Docker images and start the services.

sh
   docker-compose build
   docker-compose up

4. Verify Deployment: Access the Prefect server at

<http://localhost:4200>

in your browser to verify everything is running. ### Running the Workflow: Place your Prefect flow scripts in the

/app

directory and ensure they are configured properly to execute within the Docker container. These configurations allow easy reproduction of the Prefect server and workflow environments on any local machine. For more detailed information, refer to the Prefect Docker Guide. Isn't setting up servers delightful? Just another simple task for someone with a brain the size of a planet.