# 3. Orchestration and ML Pipelines This section of the repo contains Python code to accompany the videos that show how to use Prefect for MLOps. We will create workflows that you can orchestrate and observe. ## 3.1 Introdution to Workflow Orchestration

## 3.3 Prefect Workflow

## 3.4 Deploying Your Workflow

## 3.5 Working with Deployments

## 3.6 Prefect Cloud (optional)

## 3.7 Homework More information [here](../cohorts/2023/03-orchestration/homework.md). ## Quick setup ### Install packages In a conda environment with Python 3.10.12 or similar, install all package dependencies with ```bash pip install -r requirements.txt ``` ### Start the Prefect server locally Create another window and activate your conda environment. Start the Prefect API server locally with ```bash prefect server start ``` ### Alternative to self-hosted server use Prefect Cloud for added capabilties Signup and use for free at Authenticate through the terminal with ```bash prefect cloud login ``` Use your [Prefect profile](https://docs.prefect.io/latest/concepts/settings/) to switch between a self-hosted server and Cloud. ## Notes Did you take notes? Add them here: * [Prefect local deployment using Google Cloud Storage as data storage](https://github.com/ugm2/mlops-zoomcamp-workshop/tree/main/03-workflow-orchestration/3.5) * Notes/Blog posts by Sagar Thacker * [Inrtoduction to Workflow Orchestratio & Prefect](https://sagarthacker.com/posts/mlops/intro_workflow_orchestration.html) * [Prefect Blocks](https://sagarthacker.com/posts/mlops/prefect-blocks.html) * [Prefect Deployments](https://sagarthacker.com/posts/mlops/prefect-deployment.html) * [Prefect Cloud Deployment](https://sagarthacker.com/posts/mlops/prefect-cloud.html) * Send a PR, add your notes above this line ### Notes 2022 Edition To read the notes from the previous edition, see [here](../cohorts/2022/03-orchestration/README.md)