I can create SageMaker Notebook instance from aws sagemaker create-notebook-instance --notebook-instance-name test-123
but I can't find a similiar CLI command to create a "SageMaker Studio" instance?
Thanks
SageMaker Studio is a web-based IDE for machine learning, with multiple components. At its core, Studio consists of a Domain and a list of user profiles. Each user profile can contain multiple "apps" which can host notebook instances, among other features.
See Onboard to Amazon SageMaker Studio for details. Each of these can be created through the CLI, such as -
create-domain
create-user-profile
create-app
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Currently I am developing a model in AWS Sagemaker Studio. In Sagemaker there are multiple options for running model, like notebook instance, sagemaker studio etc, to schedule a task in notebook instance, it is known that we need to use AWS lambda for that. But I can't see an documentation on how to run scheduled job on AWS Sagemaker Studio.
Need suggestion on this. I know this is not a good question based on StackOverflow guidance like showing some code, but the problem itself is a bit new one, with a newer solution like AWS Sagemaker Studio.
A new feature allows you to Operationalize your Amazon SageMaker Studio notebooks as scheduled notebook jobs
The sample notebooks for SageMaker Distributed training, like here: https://github.com/aws/amazon-sagemaker-examples/blob/main/advanced_functionality/distributed_tensorflow_mask_rcnn/mask-rcnn-scriptmode-s3.ipynb rely on the docker build . and docker push . commands, which are not available or installable in Amazon SageMaker Studio.
Are there alternatives of these notebooks that are compatible with the SageMaker Studio?
SageMaker Studio does not support Docker, since the Studio apps are containers themselves. You can use the SageMaker Docker Build tool to build docker images from Studio (uses CodeBuild in the backend). See the blog Using the Amazon SageMaker Studio Image Build CLI to build container images from your Studio notebooks and the Github repo for details.
If I write a script to train and deploy a machine learning model on AWS SageMaker notebook or create a Project using AWS SageMaker Studio, when I try to list all the resources used, using boto3, the information extracted has no pattern linking the resource information to the notebook/project.
boto3.client('sagemaker').list_models()
The boto3 api returns all resource information associated with my account and region. Is there a way to link these info (Models, endpoints, TrainingJobs, ProcessingJobs etc) to the Sagemaker Notebook/ Studio Project they were created in?
When using SageMaker Projects in SageMaker Studio, one of the advantages you get is all the child resources of that Project - models, endpoints, pipelines are tagged with the project-id. You can use SageMaker's search API with a tag filter to list all resources in SageMaker that are tagged with your project id.
we have dotnet core website hosted on AWS EC2 (windows server 2019), now we want to setup CI/CD using AWS services only.
Is there any way to do it ?
There is so much documentation around this area that a simple google search returns plethora of links. A simple place to start is the AWS documentation on DevOps https://aws.amazon.com/devops/
Then there is a specific AWS service for pipelines called (guess what) AWS CodePipeline
https://aws.amazon.com/codepipeline/
DotNet Core specific documentation is also covered by AWS https://aws.amazon.com/quickstart/architecture/dotnet-core-cicd/
and if you ever want to move to AWS Lambda, then there's an article for that as well: https://aws.amazon.com/blogs/devops/automated-ci-cd-pipeline-for-net-core-lambda-functions-using-aws-extensions-for-dotnet-cli/
Here is a link that can help you. When you are the Create Deployment Group, chose EC2 on Premise. Make sure your agent is installed on your EC2 which it should be by default if your OS image is new.
enter link description here
I am going through the boto3 documentation here: https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/emr.html#EMR.Client.create_studio
but I cannot see any sort of create/delete notebook for EMR studio. Only create/delete studio.
How can I create a emr-studio-notebook that preloads a notebook deployed somewhere on S3 via boto3?
Create/delete notebook(Workspace) operations can only be performed using EMR Studio UI and there are no CLI/SDK available for them as of today. You can create Workspace from EMR Studio and upload your existing notebook file via JupyterLab UI.