Use Kubernetes Operators for new inference capabilities in Amazon SageMaker that reduce LLM deployment costs by 50% on average

This article discusses new inference capabilities in Amazon SageMaker that can help reduce large language model (LLM) deployment costs by 50% on average. It introduces the use of Kubernetes Operators for these new capabilities, allowing users to deploy and manage LLMs on SageMaker through Kubernetes.

Specifically, the article covers:

• How AWS Controllers for Kubernetes (ACK) work, using Amazon S3 as an example
• Key components of the new inference capabilities, including inference components
• Solution overview for deploying Dolly v2 7B and FLAN-T5 XXL models on SageMaker using inference components and Kubernetes Operators
• Prerequisites and steps for creating, updating, and deleting inference components via Kubernetes
• Availability and pricing details for the new inference capabilities
• Conclusion highlighting the benefits of using Kubernetes Operators for LLM deployment on SageMaker