Governing ML lifecycle at scale: Best practices to set up cost and usage visibility of ML workloads in multi-account environments
CAT
1 min read
Cloud costs can significantly impact your business operations. Gaining real-time visibility into infrastructure expenses, usage patterns, and cost drivers is essential. To allocate costs to cloud resources, a tagging strategy is essential. This post outlines steps you can take to implement a comprehensive tagging governance strategy across accounts, using AWS tools and services that provide visibility and control. By setting up automated policy enforcement and checks, you can achieve cost optimization across your machine learning (ML) environment.
Originally appeared here:
Governing ML lifecycle at scale: Best practices to set up cost and usage visibility of ML workloads in multi-account environments
