Remove Examples Remove Lambda Remove Scalability
article thumbnail

Streamlining Workflows with Feature Branches and Logical Stacks

Xebia

This blog explores how to optimize feature branch workflows, maintain encapsulated logical stacks, and apply best practices like resource naming to improve clarity, scalability, and cost-effectiveness. This example applies to the more traditional lift and shift approaches. Simple: In the example, we needed an RDS instance.

article thumbnail

Create a generative AI–powered custom Google Chat application using Amazon Bedrock

AWS Machine Learning - AI

With this solution, you can interact directly with the chat assistant powered by AWS from your Google Chat environment, as shown in the following example. Before processing the request, a Lambda authorizer function associated with the API Gateway authenticates the incoming message.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

For example, a marketing content creation application might need to perform task types such as text generation, text summarization, sentiment analysis, and information extraction as part of producing high-quality, personalized content. An example is a virtual assistant for enterprise business operations.

article thumbnail

Build a video insights and summarization engine using generative AI with Amazon Bedrock

AWS Machine Learning - AI

We walk through the key components and services needed to build the end-to-end architecture, offering example code snippets and explanations for each critical element that help achieve the core functionality. Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability.

article thumbnail

Track, allocate, and manage your generative AI cost and usage with Amazon Bedrock

AWS Machine Learning - AI

Without a scalable approach to controlling costs, organizations risk unbudgeted usage and cost overruns. This scalable, programmatic approach eliminates inefficient manual processes, reduces the risk of excess spending, and ensures that critical applications receive priority.

article thumbnail

Enhance customer support with Amazon Bedrock Agents by integrating enterprise data APIs

AWS Machine Learning - AI

Although the principles discussed are applicable across various industries, we use an automotive parts retailer as our primary example throughout this post. The Lambda function runs the database query against the appropriate OpenSearch Service indexes, searching for exact matches or using fuzzy matching for partial information.

Lambda 115
article thumbnail

Create generative AI agents that interact with your companies’ systems in a few clicks using Amazon Bedrock in Amazon SageMaker Unified Studio

AWS Machine Learning - AI

Lets look at an example solution for implementing a customer management agent: An agentic chat can be built with Amazon Bedrock chat applications, and integrated with functions that can be quickly built with other AWS services such as AWS Lambda and Amazon API Gateway. Give the project a name (for example, crm-agent ).