What is Docker?

Think of Docker as a way to pack up your computer programs and all the stuff they need into a neat, portable box. This box (called a container) can be easily moved and opened on any computer, and it will work exactly the same way every time.

Why Use Docker for Data Pipelines?

1. Consistency: Your data pipeline works the same on your laptop, your colleague’s desktop, and in the cloud.
2. Isolation: Each part of your pipeline is in its own container, so they don’t interfere with each other.
3. Scalability: Need to process more data? Just add more containers!
4. Version Control: You can keep track of different versions of your data pipeline easily.

Docker Basics for Data Engineers

1. Docker Images

• What: A blueprint for your container.
• Think of it as: A recipe for your favorite dish.
• In data pipelines: Each step in your pipeline can have its own image.

2. Docker Containers

• What: A running instance of an image.
• Think of it as: The actual cooked dish from your recipe.
• In data pipelines: Each container is a working part of your pipeline, like data cleaning or analysis.

3. Dockerfile

• What: Instructions to build an image.
• Think of it as: The written recipe.