Remove Lambda Remove Scalability Remove Serverless
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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. By switching to serverless, you pay for the usage. These stacks should have a minimal number of dependencies.

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From Code to Cloud: AWS Lambda CI/CD with GitHub Actions

Perficient

Introduction: Integrating GitHub Actions for Continuous Integration and Continuous Deployment (CI/CD) in AWS Lambda deployments is a modern approach to automating the software development lifecycle. After this, open AWS Lambda and create a function using Python with the default settings. In our case, we are using ap-south-1.

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

AWS Machine Learning - AI

Before processing the request, a Lambda authorizer function associated with the API Gateway authenticates the incoming message. After it’s authenticated, the request is forwarded to another Lambda function that contains our core application logic. The code runs in a Lambda function. Implement your business logic in this file.

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

AWS Machine Learning - AI

Organizations typically can’t predict their call patterns, so the solution relies on AWS serverless services to scale during busy times. Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability.

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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

Semantic routing offers several advantages, such as efficiency gained through fast similarity search in vector databases, and scalability to accommodate a large number of task categories and downstream LLMs. These embeddings are then saved as a reference index inside an in-memory FAISS vector store, which is deployed as a Lambda layer.

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Serverless NLP: Implementing Sentiment Analysis Using Serverless Technologies

Dzone - DevOps

In this article, I will discuss building a sentiment analysis tool using AWS serverless capabilities and NLTK. I will be using AWS lambda to run sentiment analysis using the NLTK -vader library and AWS API Gateway to enable this functionality as an API. Before we dive in, ensure that you have the following:

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

AWS Machine Learning - AI

The solution presented in this post takes approximately 15–30 minutes to deploy and consists of the following key components: Amazon OpenSearch Service Serverless maintains three indexes : the inventory index, the compatible parts index, and the owner manuals index.

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