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3. Orchestration and ML Pipelines

Note: orchestration.py is a ready final version. The rest of the files were worked on together during the video tutorials.

Note With Prefect version 2.2.1 or later DeploymentSpec's are now just Deployment's.

3.1 Negative engineering and workflow orchestration

3.2 Introduction to Prefect 2.0

3.3 First Prefect flow and basics

3.4 Remote Prefect Orion deployment

3.5 Deployment of Prefect flow

Note: There are several changes to deployment in Prefect 2.3.1 since 2.0b8:

  • DeploymentSpec in 2.0b8 now becomes Deployment.
  • work_queue_name is used instead of tags to submit the deployment to the a specific work queue.
  • You don't need to create a work queue before using the work queue. A work queue will be created if it doesn't exist.
from prefect.deployments import Deployment
from prefect.orion.schemas.schedules import IntervalSchedule
from datetime import timedelta

deployment = Deployment.build_from_flow(
    flow=main,
    name="model_training",
    schedule=IntervalSchedule(interval=timedelta(minutes=5)),
    work_queue_name="ml"
)

deployment.apply()

Links:

3.6 MLOps Zoomcamp 3.6 - (Optional) Work queues and agents

3.7 Homework

More information here: TBD

Notes

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