@Marvin running

docker run -p 4210-4211:4200-4201 -e PREFECT_API_URL=<http://localhost:4200/api> -e PREFECT_SERVER_API_HOST=0.0.0.0 prefecthq/prefect:2-latest-conda

I get the following status on the docker container Exited (0) 10 seconds ago and on logs I only get docker logs fbb366a7a779 _ _ _ _ _ _ _____ | _ \ _ \ __| __| __/ _| _| | _/ / _|| _|| | (_ | | |_| |_|_\___|_| |___\___| |_|

It seems like the premature exit of the Docker container could be related to several known issues. Here are some potential problems and their references which might help you troubleshoot the issue: 1. Intermittent Fatal Errors in Docker Deployment: - There are reports of intermittent fatal errors when running deployments with Docker infrastructure. It might be worth checking if the Docker client and server are configured correctly and if you have the right versions installed. - GitHub Issue: Intermittent fatal error running deployment with docker infra 2. Connection Errors to `host.docker.internal`: - Another common problem is connection errors to

host.docker.internal

, especially when the Docker agent is deployed locally on the same machine as the Docker server. Ensure that Docker is correctly configured and that the server is reachable from the agent. - GitHub Issue: Docker agent with server tasks stuck submitted: host.docker.internal connection error 3. Initial Setup Configuration: - Ensure that your environment variables and Docker commands are correctly set up. Double-check the

PREFECT_API_URL

and

PREFECT_SERVER_API_HOST

values in your Docker command. If these references don't directly resolve your issue, it might be helpful to more closely monitor your Docker setup and any error messages that appear. Additionally, retrying the deployment can sometimes resolve intermittent issues. If you have further problems or a more specific issue description, please let me know!

@Marvin but I want to start my prefect-server and it doesn't start automatically I have to run:

docker exec -it prefect-server /bin/bash

and then manually run

prefect server start

It seems like an automated way to start the Prefect server through Docker is necessary to avoid manual intervention. You should aim to leverage docker-compose to make the Prefect server start automatically. Here's how you can set it up: 1. Create a docker-compose.yml file:

yaml
version: '3'

services:
  prefect-server:
    image: prefecthq/prefect:2-latest-conda
    environment:
      - PREFECT_API_URL=<http://localhost:4200/api>
      - PREFECT_SERVER_API_HOST=0.0.0.0
    ports:
      - "4210-4211:4200-4201"
    command: prefect server start

2. Start the Prefect server using docker-compose:

sh
docker-compose up

This configuration sets the

command

to automatically start the Prefect server within the Docker container, ensuring you don't have to manually run the command inside the container. You can consult more detailed examples or customization options in the Prefect documentation or by checking out examples on GitHub. For more nuanced help, revisiting the Prefect documentation or contacting their support forums might be useful. Let me know if you need any additional assistance!

@Marvin do you know why it tries to register the worker to prefect cloud: /dijar-kickoff/prefect/worker$ docker compose up [+] Running 1/0 ✔️ Container worker-prefect-server-1 Recreated 0.1s Attaching to worker-prefect-server-1 worker-prefect-server-1 | Starting Prefect worker... worker-prefect-server-1 | /opt/conda/envs/prefect/lib/python3.10/site-packages/prefect/settings.py1849 UserWarning:

PREFECT_API_URL

should have

/api

after the base URL. worker-prefect-server-1 | e.g. PREFECT_API_URL="https://api.prefect.cloud/api/accounts/[ACCOUNT-ID]/workspaces/[WORKSPACE-ID]" worker-prefect-server-1 | values = warn_on_misconfigured_api_url(values) httpx.UnsupportedProtocol: Request URL is missing an 'http://' or 'https://' protocol. worker-prefect-server-1 | An exception occurred.

Based on the messages and errors you’ve encountered, it seems like there are a couple of issues with how the Prefect server and worker are configured. Here’s a checklist and steps to ensure everything runs smoothly: 1. PREFECT_API_URL Configuration: - The warning indicates that the

PREFECT_API_URL

should end with

/api

. Ensure this environment variable is correctly set. For example:

yaml
    environment:
      - PREFECT_API_URL=<http://localhost:4200/api>

2. Protocols for URL: - The error

httpx.UnsupportedProtocol: Request URL is missing an 'http://' or 'https://' protocol

suggests that Prefect expects a fully qualified URL with a protocol (

http://

or

https://

). Double-check your URL settings. 3. Starting Prefect Worker: - When starting the worker, ensure that it correctly points to the server URL and includes all required configurations. Here’s a refined

docker-compose.yml

example:

yaml
    version: '3'
    services:
      prefect-server:
        image: prefecthq/prefect:2-latest-conda
        environment:
          - PREFECT_API_URL=<http://localhost:4200/api>
          - PREFECT_SERVER_API_HOST=0.0.0.0
        ports:
          - "4210-4211:4200-4201"
        command: prefect server start

      prefect-worker:
        image: prefecthq/prefect:2-latest-conda
        environment:
          - PREFECT_API_URL=<http://localhost:4200/api>
        command: prefect worker start --pool default-agent-pool
        depends_on:
          - prefect-server

Here’s the docker-compose command to run it:

sh
docker-compose up

Let’s recap: 1. Ensure

PREFECT_API_URL

is correctly set and ends with

/api

. 2. Validate the URLs include the appropriate protocol (

http://

). 3. Use

docker-compose

to handle dependencies and start multiple services together. Let me know if there are any other issues or if anything specific needs more clarity!

@Marvin this is my docker compose.yaml: cat compose.yaml version: '3' services: prefect-server: image: dijarvrella444/prefect-base:latest environment: - PREFECT_API_URL="https://localhost:4200/api" - PREFECT_NODE_TYPE=worker command: prefect worker start --pool "seedoo-custom-worker" Why does it still try to register to cloud

It looks like there might be a few issues with your setup: 1. Environment Variable Format and Values: - Ensure that the URL does not have angle brackets (

< >

). -

PREFECT_NODE_TYPE

is not a standard environment variable for defining local or cloud operations. Prefect uses the

PREFECT_API_URL

to determine where to send API requests. - The worker command should confirm that it's pointing to your local server URL, not the cloud one. 2. Correct Formatting of Environment Variables: - Remove the angle brackets from the URL. 3. Worker's Incorrect Registration to Cloud: - Ensure that the

API URL

is correctly set up to point to your local server and not to Prefect Cloud. Here's the corrected version of your `docker-compose.yaml`:

yaml
version: '3'

services:
  prefect-server:
    image: dijarvrella444/prefect-base:latest
    environment:
      - PREFECT_API_URL=<http://localhost:4200/api>
      - PREFECT_SERVER_API_HOST=0.0.0.0
    ports:
      - "4210-4211:4200-4201"
    command: prefect server start

  prefect-worker:
    image: dijarvrella444/prefect-base:latest
    environment:
      - PREFECT_API_URL=<http://localhost:4200/api>
    command: prefect worker start --pool "seedoo-custom-worker"
    depends_on:
      - prefect-server

Important Notes: 1. Ensure you are not using Prefect Cloud settings: -

PREFECT_API_URL

should point to your local server. - If you have previously authenticated with Prefect Cloud, make sure you are not using a Prefect Cloud token by mistake. Remove the cloud authentication if it exists. 2. Check for Environment Variables at Runtime: - Sometimes environment variables overridden at startup can persist. Make sure to check the running container's environment variables to ensure they are set correctly:

sh
   docker exec -it <container_id> env | grep PREFECT

3. Verbose Output for Debugging: - You can add a verbose flag to the command for additional logs to debug why it's trying to register with the cloud:

yaml
     command: prefect worker start --pool "seedoo-custom-worker" --verbose

Restart your Docker services with the updated configuration:

sh
docker-compose down
docker-compose up

Always make sure that any older configurations or old containers are properly stopped and removed. If issues persist, verifying the Prefect configuration files might help to ensure no cloud settings are leaking in.

@Marvin fix httpcore.ConnectError: All connection attempts failed worker-prefect-worker-1 | worker-prefect-worker-1 | The above exception was the direct cause of the following ker-1 | self.gen.throw(typ, value, traceback) worker-prefect-worker-1 | File "/opt/conda/envs/prefect/lib/python3.10/site-packages/httpx/_transports/default.py", line 86, in map_httpcore_exceptions worker-prefect-worker-1 | raise mapped_exc(message) from exc worker-prefect-worker-1 | httpx.ConnectError: All connection attempts failed worker-prefect-worker-1 | An exception occurred.

Your message was too long by 1119 tokens - please shorten it and try again. For reference, here's your message at the allowed limit:

fix httpcore.ConnectError: All connection attempts failed

worker-prefect-worker-1 | worker-prefect-worker-1 | The above exception was the direct cause of the following exception: worker-prefect-worker-1 | worker-prefect-worker-1 | Traceback (most recent call last): worker-prefect-worker-1 | File "/opt/conda/envs/prefect/lib/python3.10/site-packages/prefect/cli/_utilities.py", line 42, in wrapper worker-prefect-worker-1 | return fn(*args, **kwargs) worker-prefect-worker-1 | File "/opt/conda/envs/prefect/lib/python3.10/site-packages/prefect/utilities/asyncutils.py", line 304, in coroutine_wrapper worker-prefect-worker-1 | return call() worker-prefect-worker-1 | File "/opt/conda/envs/prefect/lib/python3.10/site-packages/prefect/_internal/concurrency/calls.py", line 432, in call worker-prefect-worker-1 | return self.result() worker-prefect-worker-1 | File "/opt/conda/envs/prefect/lib/python3.10/site-packages/prefect/_internal/concurrency/calls.py", line 318, in result worker-prefect-worker-1 | return self.future

@Marvin I want to register a docker registry block with bash script how can one do that?

To register a Docker registry block with a bash script in Prefect, you'll need to use

prefect block register

command along with JSON configuration for the Docker registry block. Here's a step-by-step guide to accomplish this: ### Steps to Register Docker Registry Block Using a Bash Script: 1. Create JSON Configuration File: - Create a JSON configuration file that contains the necessary details for your Docker registry block. For example, save this as `docker_registry_config.json`:

json
    {
        "url": "your-docker-registry-url",
        "username": "your-username",
        "password": "your-password"
    }

2. Create the Bash Script: - Write the bash script to use the Prefect CLI to register the block. Save this as `register_docker_registry_block.sh`:

bash
    #!/bin/bash

    # Define the block type and name
    BLOCK_TYPE="docker-registry"
    BLOCK_NAME="my-docker-registry"

    # Define the JSON configuration file
    CONFIG_FILE="docker_registry_config.json"

    # Register the Docker registry block
    prefect block register -t $BLOCK_TYPE -n $BLOCK_NAME --from-json $CONFIG_FILE

    echo "Docker registry block registered successfully!"

3. Make the Script Executable: - Make sure the script has execution permissions:

sh
    chmod +x register_docker_registry_block.sh

4. Run the Script: - Execute the script to register the Docker registry block:

sh
    ./register_docker_registry_block.sh

### Final Points: - Ensure you replace

your-docker-registry-url

,

your-username

, and

your-password

with actual values. - Make sure the Prefect CLI is installed and properly configured on your machine or Docker container where you run this script. This script will register the Docker registry block in Prefect using the provided JSON configuration. If you have further questions or any issues, feel free to ask!

@Marvin how to adjust the work pool base job template?

Adjusting the base job template for a work pool in Prefect involves tweaking the job configuration that the worker uses when running a flow. Here's a step-by-step guide on how to do this: ### Steps to Adjust the Work Pool Base Job Template: 1. Create a Work Pool: - You can create a work pool via Prefect Cloud UI or using the CLI. 2. Edit the Job Template: - You can edit the job template directly in the Prefect Cloud UI or using Prefect CLI commands to retrieve, edit, and then update the template. ### Use CLI to Adjust Job Template: 1. Retrieve the Existing Job Template: - You can use the Prefect CLI to get the current job template of your work pool.

sh
    prefect work-pool job-template get -p <YOUR_WORK_POOL_NAME> -t <YOUR_WORK_POOL_TYPE>

Replace

<YOUR_WORK_POOL_NAME>

and

<YOUR_WORK_POOL_TYPE>

with your work pool's name and type. 2. Edit the Job Template: - Save the output to a JSON file, for example

job_template.json

, and make necessary adjustments. A job template for a Docker work pool might look like this:

json
    {
        "job_configuration": {
            "image": "your-docker-image",
            "command": ["your-command"],
            "env": {
                "ENV_VAR": "value"
            },
            "labels": {
                "label_key": "label_value"
            },
            "resources": {
                "limits": {
                    "cpu": "1",
                    "memory": "512Mi"
                },
                "requests": {
                    "cpu": "500m",
                    "memory": "256Mi"
                }
            }
        }
    }

3. Update the Job Template: - Once you have made the necessary edits, update the work pool with the new job template.

sh
    prefect work-pool job-template update -p <YOUR_WORK_POOL_NAME> -t <YOUR_WORK_POOL_TYPE> --job-template job_template.json

### Update Job Template via Prefect Cloud UI: 1. Navigate to the Work Pool: - Open Prefect Cloud and navigate to your work pool. 2. Edit the Job Template: - Find the job template editor section, make your desired changes in the provided editor, and save. ### Example Bash Script to Automate Registration: If you want to automate adjusting the job template using a Bash script, you could do something like this:

bash
#!/bin/bash

WORK_POOL_NAME="my-work-pool"
WORK_POOL_TYPE="kubernetes"

# Retrieve the current job template
prefect work-pool job-template get -p $WORK_POOL_NAME -t $WORK_POOL_TYPE > job_template.json

# (Optional) Modify job_template.json as needed using jq, sed, or another tool

# For example, to change the image:
jq '.job_configuration.image = "my-new-docker-image:latest"' job_template.json > updated_job_template.json

# Update the work pool with the modified job template
prefect work-pool job-template update -p $WORK_POOL_NAME -t $WORK_POOL_TYPE --job-template updated_job_template.json

echo "Work pool job template updated successfully!"

This script retrieves the current job template, modifies it (here using

jq

for JSON editing), and then updates the work pool with the new template. ### Resources for Further Reference: - Prefect CLI Documentation - Prefect Work Pools Adjust the template and Kotlin as per your requirements and ensure that it aligns with your job specifications and computing environment. If you have any further questions or require additional information, feel free to ask!

@Marvin how to fix: Volumes (Optional) A list of volume to mount into created containers.

"/seedoodata":"/seedoodata"

Volumes must be valid JSON

It looks like the JSON syntax for specifying volumes in Docker is causing an issue. The error indicates that the volumes section needs to be properly formatted as a valid JSON object. ### Correct JSON Format for Docker Volumes: In a JSON format, Docker volumes should be specified as key-value pairs within an array. For instance, your volume specification should look like this:

json
[
  { "/seedoodata": { "bind": "/seedoodata", "mode": "rw" } }
]

### Example in a

docker-compose.yml

File: Below is a complete example of how you can specify volumes in your

docker-compose.yml

file:

yaml
version: '3'

services:
  prefect-server:
    image: dijarvrella444/prefect-base:latest
    environment:
      - PREFECT_API_URL=<http://localhost:4200/api>
      - PREFECT_SERVER_API_HOST=0.0.0.0
    ports:
      - "4210-4211:4200-4201"
    volumes:
      - /seedoodata:/seedoodata
    command: prefect server start

  prefect-worker:
    image: dijarvrella444/prefect-base:latest
    environment:
      - PREFECT_API_URL=<http://prefect-server:4200/api>
    volumes:
      - /seedoodata:/seedoodata
    command: prefect worker start --pool "seedoo-custom-worker"
    depends_on:
      - prefect-server

### Example of Using Prefect CLI with a JSON Volume Configuration: If you are using a JSON configuration for Prefect's Docker infrastructure block, it should be formatted like this:

json
{
  "job_configuration": {
    "image": "dijarvrella444/prefect-base:latest",
    "command": ["prefect", "server", "start"],
    "env": [
      {
        "name": "PREFECT_API_URL",
        "value": "<http://localhost:4200/api>"
      },
      {
        "name": "PREFECT_SERVER_API_HOST",
        "value": "0.0.0.0"
      }
    ],
    "ports": [
      {
        "container_port": 4200,
        "host_port": 4200
      },
      {
        "container_port": 4201,
        "host_port": 4201
      }
    ],
    "volumes": [
      {
        "host_path": "/seedoodata",
        "container_path": "/seedoodata",
        "mode": "rw"
      }
    ]
  }
}

Alternatively, if you are just tweaking the job template volumes via a script, ensure the JSON is valid: ### Bash Script Example:

bash
#!/bin/bash

WORK_POOL_NAME="my-work-pool"
WORK_POOL_TYPE="docker"

# Retrieve the current job template
prefect work-pool job-template get -p $WORK_POOL_NAME -t $WORK_POOL_TYPE > job_template.json

# Add the volume configuration
jq '.job_configuration.volumes = [{"host_path": "/seedoodata", "container_path": "/seedoodata", "mode": "rw"}]' job_template.json > updated_job_template.json

# Update the work pool with the modified job template
prefect work-pool job-template update -p $WORK_POOL_NAME -t $WORK_POOL_TYPE --job-template updated_job_template.json

echo "Work pool job template updated successfully!"

By ensuring the JSON is properly formatted, Docker and Prefect will interpret and use the volume mount configuration correctly. Let me know if you encounter any issues or need further assistance!

@Marvin I set this to "/seedoodata:/seedoodata" Validation failed for work pool's job variable defaults: Validation failed for field 'volumes'. Failure reason: '"/seedoodata:/seedoodata"' is not valid under any of the given schemas Validation failed for work pool's job variable defaults: Validation failed for field 'volumes'. Failure reason: '"/seedoodata:/seedoodata"' is not valid under any of the given schemas

The issue stems from providing the volume mount as a string in the format

"/seedoodata:/seedoodata"

instead of using the expected JSON structure. Prefect requires the volumes to be specified in a structured JSON format. Here's how you can set the volume correctly: ### Correct JSON Structure for Volumes: The correct format for specifying volumes is as objects within an array. #### Example JSON Configuration:

json
[
  {
    "host_path": "/seedoodata",
    "container_path": "/seedoodata",
    "mode": "rw"
  }
]

#### Example in `docker-compose.yml`: The

docker-compose.yml

does not directly translate to Prefect’s job variable format, but here’s how it should look in that file for Docker Compose:

yaml
version: '3'

services:
  prefect-server:
    image: dijarvrella444/prefect-base:latest
    environment:
      - PREFECT_API_URL=<http://localhost:4200/api>
      - PREFECT_SERVER_API_HOST=0.0.0.0
    ports:
      - "4210-4211:4200-4201"
    volumes:
      - /seedoodata:/seedoodata
    command: prefect server start

  prefect-worker:
    image: dijarvrella444/prefect-base:latest
    environment:
      - PREFECT_API_URL=<http://prefect-server:4200/api>
    volumes:
      - /seedoodata:/seedoodata
    command: prefect worker start --pool "seedoo-custom-worker"
    depends_on:
      - prefect-server

But for Prefect's job variable configuration, you need a JSON structure. ### Applying the JSON Configuration through Prefect CLI: If you're using Prefect CLI to create or update the work pool job template with this volume configuration, it should be in valid JSON. Here’s a detailed step-by-step to apply the configuration correctly: 1. Create JSON Configuration File: - Save the configuration as `job_template.json`:

json
    {
      "job_configuration": {
        "image": "dijarvrella444/prefect-base:latest",
        "command": ["prefect", "server", "start"],
        "env": [
          {
            "name": "PREFECT_API_URL",
            "value": "<http://localhost:4200/api>"
          },
          {
            "name": "PREFECT_SERVER_API_HOST",
            "value": "0.0.0.0"
          }
        ],
        "ports": [
          {
            "container_port": 4200,
            "host_port": 4200
          },
          {
            "container_port": 4201,
            "host_port": 4201
          }
        ],
        "volumes": [
          {
            "host_path": "/seedoodata",
            "container_path": "/seedoodata",
            "mode": "rw"
          }
        ]
      }
    }

2. Use a Bash Script to Update the Job Template: - Here’s a bash script to update the job template with the correct volume format:

bash
    #!/bin/bash

    WORK_POOL_NAME="my-work-pool"
    WORK_POOL_TYPE="docker"

    # Retrieve the current job template
    prefect work-pool job-template get -p $WORK_POOL_NAME -t $WORK_POOL_TYPE > job_template.json

    # Modify the job template to include volumes
    jq '.job_configuration.volumes = [{"host_path": "/seedoodata", "container_path": "/seedoodata", "mode": "rw"}]' job_template.json > updated_job_template.json

    # Update the work pool with the modified job template
    prefect work-pool job-template update -p $WORK_POOL_NAME -t $WORK_POOL_TYPE --job-template updated_job_template.json

    echo "Work pool job template updated successfully!"

3. Run the Script: - Execute the script to update your work pool configuration:

sh
    chmod +x update_work_pool_job_template.sh
    ./update_work_pool_job_template.sh

### Additional Tips: - Always ensure that your JSON is valid. Tools like

jq

or online JSON validators can help. - Double-check your paths and ensure they are accessible and correct. By following these steps and adjusting the volume configuration to the correct JSON format, you should be able to fix the validation errors. If you still encounter issues, please let me know!