Here are some insights based on your questions: 1. Workflow for a data engineer using Prefect: The typical workflow involves coding your flows, writing the desired deployment configuration, committing your project to Git, and letting CI/CD build images and deploy your flows. After this, you would typically monitor the execution of your flows and troubleshoot any issues that arise. You can also configure and monitor infrastructure configuration within the Prefect UI. For more advanced operations like deploying on Kubernetes, you can refer to the Prefect tutorial. 2. Starting a Docker worker with Prefect: Workers are a lightweight polling process that kick off scheduled flow runs on a certain type of infrastructure (like Docker). To start a worker on your laptop, you need to have Prefect installed on your machine and then run the command

prefect worker start

. This starts the worker process. For more details, you can refer to the Prefect workers tutorial. 3. Automatic horizontal scaling for workers: Work pools and workers allow Prefect to exercise greater control of the infrastructure on which flows run. This setup allows you to essentially "scale to zero" when nothing is running, as the worker process is lightweight and does not need the same resources that your workflows do. For more details, you can refer to the Prefect deployments concept. 4. Prefect's design decisions: Prefect's design decisions are largely driven by the need for a flexible, scalable, and robust workflow orchestration tool. The concepts of flows, tasks, and workers are central to this design. Flows allow for the definition of complex workflows, tasks provide the building blocks for these workflows, and workers execute these tasks. The design allows for a high degree of control over the execution environment and scalability. Please note that these are high-level insights and for more detailed understanding, you should refer to the Prefect documentation and tutorials.