Sagemaker Studio Problem

We are sorry to hear that you are experiencing performance issues with your current set up of Amazon SageMaker Studio. Amazon SageMaker offers a broad set of ML capabilities used by tens of thousands of customers to access and analyze data, and build, train, and deploy high-quality ML models

https://aws.amazon.com/sagemaker/data-scientist/

If you're facing performance issues with SageMaker Studio, here are a few things you can try:

1.SageMaker Studio allows you to choose different instance types with different capabilities and performance. Consider selecting an instance type that provides the right requirements for your workload. Instances with higher CPU, memory, and GPU specifications may offer improved performance.

2. Lifecycle Configurations: Lifecycle Configurations are shell scripts triggered by Amazon SageMaker Studio lifecycle events, such as starting a new Studio notebook. You can use Lifecycle Configurations to automate customization for your Studio environment. This customization includes installing custom packages, configuring notebook extensions, preloading datasets, and setting up source code repositories. (https://docs.aws.amazon.com/sagemaker/latest/dg/studio-lcc.html)

3. AWS Region: Regions closer to your location or regions with better availability of resources may provide improved results.

4. Resource Management: Save costs by automatically shutting down idle resources within Amazon SageMaker Studio (https://aws.amazon.com/blogs/machine-learning/save-costs-by-automatically-shutting-down-idle-resources-within-amazon-sagemaker-studio/)

Thanks