Look Mom, We're in the Cloud.

This flow is a simple linear workflow that verifies your AWS configuration. The start and end steps will run locally, while the hello step will run remotely on AWS batch. After configuring Metaflow to run on AWS, data and metadata about your runs will be stored remotely. This means you can use the client to access information about any flow from anywhere.

You can find the tutorial code on GitHub​

Showcasing:

• ​AWS Batch and the @batch decorator.

• Using the Client API to access data artifacts generated remotely in a local notebook.

• ​@retrydecorator.

Before playing this episode:

1. python -m pip install notebook

2. This tutorial requires access to compute and storage resources on AWS, which can be configured by

   1. Following the instructions here or

   2. Requesting a sandbox.

To play this episode:

1. cd metaflow-tutorials

2. python 05-helloaws/helloaws.py run

3. jupyter-notebook 05-helloaws/helloaws.ipynb

4. Open helloaws.ipynb in your remote Sagemaker notebook