MLCOST-20 - Setup budget and use resource tagging to track costs

If you need visibility of your ML cost, set up budgets and consider tagging your notebook instances. Examples of tags include the name of the project, the business unit, and environment (such as development, testing, or production).

Tags are useful for cost optimization and can provide a clear visibility into where money is being spent.

Implementation plan

• Use AWS Budgets to keep track of cost - AWS Budgets helps you track your Amazon SageMaker cost, including development, training, and hosting. You can also set alerts and get a notification when your cost or usage exceeds (or is forecasted to exceed) your budgeted amount. After you create your budget, you can track the progress on the AWS Budgets console.

• Use AWS Cost Explorer - Visualize, understand, and manage your AWS costs and usage over time using AWS Cost Explorer.

• Tagging the resources - Consider tagging your Amazon SageMaker notebook instances and the hosting endpoints. Cost allocation tags can help track and categorize your cost of ML. It can answer questions such as “Can I delete this resource to save cost?”

Documents

• Managing your costs with AWS Budgets

• Using Cost Allocation Tags

• Tagging Best Practices

Blogs

• Optimizing costs for machine learning with Amazon SageMaker

• Automate Cost Control using Service Catalog and AWS Budgets