Managing Model Lifecycle in Amazon Bedrock
This article explains how to manage the lifecycle of models in Amazon Bedrock, including the three lifecycle states, planning migrations with the new extended access feature, and strategies to transition applications to newer models without disruption.
Why it matters
Effectively managing the lifecycle of AI models is critical for maintaining operational AI applications as the underlying technology rapidly evolves.
Key Points
- 1Bedrock has three model lifecycle states: active, deprecated, and archived
- 2The new extended access feature allows planning migrations to newer models
- 3Strategies to transition applications to newer models without disruption
Details
Amazon Bedrock is a managed service that provides access to large language models (LLMs) for building AI applications. As these models evolve over time, it's important to manage the lifecycle to ensure application continuity. The article discusses the three lifecycle states in Bedrock - active, deprecated, and archived. It explains how the new extended access feature allows you to plan migrations to newer models, giving you time to update your applications. The article also provides practical strategies to transition your applications to newer models without disrupting your end-users, such as gradually migrating a subset of traffic or using feature flags.
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