Paths/MLOps Engineer/ML Pipelines / Your First Pipeline
Containerize the Pipeline
Turn the pipeline into a runnable image. Building it yourself is how you learn why images — not laptops — are the unit of execution in MLOps.
Validator
⏱ 0:00
IDLE — checks run live as you type commands; submit when done
01Requirements
live checks- A Dockerfile exists in ~/pipeline-img○
- An image pipeline:v1 is built○
- A container from pipeline:v1 is running○
02Walkthrough
1 of 7 revealed- 01
Create the build directory
A docker build always needs a build context — a directory holding the Dockerfile.
mkdir ~/pipeline-img - 6 locked · each failed submit reveals one
03Stuck?
0 of 3 revealedTake a hint without losing the lab — each one points at the thing to look at, not at the answer.
04AI Tutor
guides, never solvesTell me what you're stuck on — I'll nudge, not solve. Which requirement are you looking at?
04Notebook
saved locally in this browserlearner@lab — docker:24
Session is disposable
↑/↓ recalls commands · Ctrl+Enter submits · type help for the command list