prefect-northflank 0.1.0

Prefect integrations for Northflank platform

prefect-northflank

Prefect integrations for running flows on the Northflank platform.

This collection provides a Prefect worker that can execute flow runs as containerized jobs on Northflank's cloud platform, giving you powerful orchestration capabilities with Northflank's container-native infrastructure.

Installation

Install prefect-northflank with pip:

pip install prefect-northflank

Quick Start

1. Set up Northflank credentials:

   from prefect_northflank import Northflank
   
   credentials = Northflank(
       api_token="your-northflank-api-token",
   )
   credentials.save("northflank-creds")
   

2. Create a work pool:

   prefect work-pool create --type northflank my-northflank-pool
   

3. Configure your deployment (prefect.yaml):

   deployments:
   - name: my-northflank-deployment
     entrypoint: flows.py:my_flow
     work_pool:
       name: my-northflank-pool
        job_variables:
          credentials: "{{ prefect.blocks.northflank.northflank-creds }}"
          project_id: "your-northflank-project-id"
          deployment_external_image_path: "python:3.12-slim"
          billing_deployment_plan: "nf-compute-20"
   

4. Start a worker:

   prefect worker start --pool my-northflank-pool
   

5. Deploy and run your flow:

   prefect deploy --all
   prefect deployment run 'my-flow/my-northflank-deployment'
   

Complete CLI Walkthrough

Here's a complete step-by-step guide to set up and run a flow:

# 1. Install the package
pip install prefect-northflank

# 2. Save your Northflank credentials
python -c "
from prefect_northflank import Northflank
creds = Northflank(api_token='your-api-token-here')
creds.save('my-northflank-creds')
"

# 3. Create a work pool
prefect work-pool create --type northflank my-northflank-pool

# 4. Create a simple flow file
cat > my_flow.py << 'EOF'
from prefect import flow, task

@task
def process_data(data: str):
    return f"Processed: {data.upper()}"

@flow
def my_northflank_flow(data: str = "hello world"):
    result = process_data(data)
    print(result)
    return result
EOF

# 5. Create prefect.yaml configuration
cat > prefect.yaml << 'EOF'
name: northflank-demo
prefect-version: 3.1.1

deployments:
  - name: demo-deployment
    entrypoint: my_flow.py:my_northflank_flow
    parameters:
      data: "Hello from Northflank!"
    work_pool:
      name: my-northflank-pool
      job_variables:
        credentials: "{{ prefect.blocks.northflank.my-northflank-creds }}"
        project_id: "your-project-id"  # Replace with your Northflank project ID
        deployment_external_image_path: "python:3.12-slim"
        billing_deployment_plan: "nf-compute-20"
        settings_active_deadline_seconds: 1800
        runtime_environment:
          CUSTOM_VAR: "production"
EOF

# 6. Deploy the flow
prefect deploy --all

# 7. Start a worker (in one terminal)
prefect worker start --pool my-northflank-pool

# 8. Trigger a flow run (in another terminal)
prefect deployment run my-northflank-flow/demo-deployment

# 9. Monitor the run
prefect flow-run ls --limit 5

Features

• Containerized execution: Run flows in isolated containers on Northflank
• Resource control: Configure CPU, memory, and GPU resources via deployment plans
• Secret management: Secure injection of environment variables and secrets
• Job lifecycle management: Automatic job creation, execution, and cleanup
• Status monitoring: Real-time tracking of job execution status
• Retry handling: Built-in support for job retries and failure handling
• Cancellation support: Proper handling of flow run cancellation with job termination
• Environment merging: Automatic injection of Prefect environment variables
• Flexible commands: Support for custom container commands or default Prefect engine execution

Configuration

Flattened Configuration Structure

The Northflank worker uses a flattened configuration structure to work with Prefect's JSON schema requirements. Complex nested objects are flattened using underscore notation:

• billing.deploymentPlan → billing_deployment_plan
• deployment.external.imagePath → deployment_external_image_path
• settings.activeDeadlineSeconds → settings_active_deadline_seconds

This allows for easier configuration in YAML files and work pools while maintaining compatibility with the full Northflank API.

Worker Configuration

The Northflank worker supports the following configuration options:

Parameter	Type	Description	Default
credentials	Northflank	API credentials	Required
project_id	str	Northflank project ID	Required
cleanup_job	bool	Delete job after completion	True
name	str	Job name	Auto-generated
description	str	Job description	Auto-generated
tags	List[str]	Resource tags	None
Infrastructure
infrastructure_architecture	str	CPU architecture (x86/arm)	None
Billing
billing_deployment_plan	str	Resource allocation plan	"nf-compute-20"
billing_build_plan	str	Build plan ID	None
billing_gpu_enabled	bool	Enable GPU support	False
billing_gpu_type	str	GPU type	None
billing_gpu_count	int	Number of GPUs	1
billing_gpu_timesliced	bool	Timesliced GPU sharing	None
Deployment
deployment_external_image_path	str	Container image	"prefecthq/prefect:3-python3.12"
deployment_external_credentials	str	Registry credentials ID	None
deployment_internal_build_service	str	Build service ID	None
deployment_internal_branch	str	Git branch	None
deployment_internal_sha	str	Git commit SHA	None
deployment_docker_config_type	str	Docker config type	"customCommand"
deployment_docker_custom_command	str	Custom command	None
Build
build_configuration_docker_credentials	List[str]	Docker credential IDs	None
Runtime
runtime_environment	Dict[str, str]	Environment variables	None
Settings
settings_backoff_limit	int	Retry attempts	3
settings_active_deadline_seconds	int	Job timeout (seconds)	3600
settings_run_on_source_change	str	Source change trigger	"never"

Cancellation and Error Handling

The Northflank worker provides robust cancellation support:

• Flow cancellation: When a Prefect flow run is cancelled, the worker automatically attempts to cancel the corresponding Northflank job run
• Timeout handling: Jobs that exceed their active_deadline_seconds are automatically terminated
• Cleanup on failure: Failed jobs are cleaned up according to the cleanup_job setting
• Graceful error handling: Network errors and API failures are logged with appropriate detail levels

Environment Variables

The worker automatically injects Prefect environment variables into job containers:

• PREFECT_FLOW_RUN_ID: The unique flow run identifier
• PREFECT_FLOW_ID: The flow identifier
• PREFECT_API_URL: Prefect server/cloud API URL (if configured)
• PREFECT_API_KEY: Prefect API authentication key (if configured)

User-provided environment variables in runtime_environment take precedence over automatic variables.

Examples

Basic Flow Example

from prefect import flow

@flow
def my_flow():
    print("Hello from Northflank!")
    return "Flow completed successfully"

if __name__ == "__main__":
    my_flow()

GPU Configuration Example

# prefect.yaml for GPU workloads
deployments:
  - name: gpu-training
    entrypoint: train_model.py:training_flow
    work_pool:
      name: northflank-gpu-pool
      job_variables:
        credentials: "{{ prefect.blocks.northflank.my-creds }}"
        project_id: "proj-123456"
        deployment_external_image_path: "nvidia/pytorch:23.10-py3"
        billing_deployment_plan: "nf-gpu-h100-80-1g"
        billing_gpu_enabled: true
        billing_gpu_type: "h100-80"
        billing_gpu_count: 2
        settings_active_deadline_seconds: 14400  # 4 hours
        runtime_environment:
          CUDA_VISIBLE_DEVICES: "0,1"
          TORCH_CUDA_ARCH_LIST: "8.9"

Authentication

API Token Setup

1. Log in to your Northflank dashboard
2. Navigate to Account Settings > Tokens
3. Create a new API Role with appropriate permissions

• Select the Job General/Deployment scopes

4. Create a new API Token using the role you just created
5. Store the token securely using Prefect's block system

from prefect_northflank import Northflank

credentials = Northflank(api_token="nf-...")
credentials.save("my-northflank-creds")

Environment Variables

You can also set the API token via environment variable:

export NORTHFLANK_API_TOKEN="nfp_..."

Development

Setup

1. Clone the repository:

   git clone https://github.com/northflank/prefect-northflank.git
   cd prefect-northflank
   

2. Install with uv:

   uv sync
   uv run python -m pip install -e .
   

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

Support

For support with this integration, please:

1. Check the documentation
2. Search existing issues
3. Create a new issue if needed

Links

• Prefect Documentation
• Northflank Documentation
• Northflank API Documentation