Sagemaker Jupyter notebook


What are the advantages of using SageMaker jupyter instance instead of running it locally? Is there a special integration with SageMaker that we lose it if we do not use Sagemaker jupyer instance?

demandé il y a 4 ans447 vues
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Some useful points:

  • The typical arguments of cloud vs local will apply (as with e.g. Cloud9, Workspaces, etc): Can de-couple your work from the lifetime of your laptop, keep things running when your local machine is shut down, right-size the environment for what workloads you need to do on a given day, etc.
  • SageMaker notebooks already run in an explicit IAM context (via assigned execution role) - so you don't need to log in e.g. as you would through the CLI on local machine... Can just run sagemaker.get_execution_role()
  • Pre-built environments for a range of use-cases (e.g. generic data science, TensorFlow, PyTorch, MXNet, etc) with libraries already installed, and easy wiping/reset of the environment by stopping & starting the instance - no more "environment soup" on your local laptop.
  • Linux-based environments, which typically makes for a shorter path to production code than Mac/Windows.
  • If you started using SageMaker Studio, then yes there are some native integrations such as the UIs for experiment tracking and endpoint management/monitoring; easy sharing of notebook snapshots; and whatever else might be announced over the next couple of weeks.
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