Yes, but there are 2 limitations for our use case.
Sagemaker Jupyter is running on single EC2 instance and all notebooks are stored on the disk of that EC2 instance. If that instance dies for some reason, you can't access your Jupyter and all runbooks are gone.
Sagemaker is optimized for ML/Data science experiments. There is absolutely nothing that helps with DevOps use cases. Simple things like polling cloud watch graphs in Jupyter can be painful without some library help.
I am solving both these with nurtch.com
It's a cluster Jupyter setup with S3 as backend for storing Notebooks. I built a Rubix library that makes performing DevOps tasks easy in the notebook: docs.nurtch.com/en/latest/rubix-li...
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Yes, but there are 2 limitations for our use case.
Sagemaker Jupyter is running on single EC2 instance and all notebooks are stored on the disk of that EC2 instance. If that instance dies for some reason, you can't access your Jupyter and all runbooks are gone.
Sagemaker is optimized for ML/Data science experiments. There is absolutely nothing that helps with DevOps use cases. Simple things like polling cloud watch graphs in Jupyter can be painful without some library help.
I am solving both these with nurtch.com
It's a cluster Jupyter setup with S3 as backend for storing Notebooks. I built a Rubix library that makes performing DevOps tasks easy in the notebook: docs.nurtch.com/en/latest/rubix-li...