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Trade routes of the digital age: How data gravity shapes cloud strategy

CIO

However, as companies expand their operations and adopt multi-cloud architectures, they are faced with an invisible but powerful challenge: Data gravity. The challenge of data gravity in a multi-cloud world The adoption of multi-cloud strategies has transformed the way enterprises manage their IT workloads.

Strategy 164
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How a Serverless Architecture Can Help You Secure Cloud-Native Applications

Tenable

Cybersecurity teams often struggle with securing cloud-native applications, which are becoming increasingly popular with developers. The good news is that deploying these applications on a serverless architecture can make it easier to protect them. What is serverless? How can serverless help? Here’s why.

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Implementing Serverless Node.js Functions Using Google Cloud

Toptal

Serverless computing is an architecture style in which the code is executed in a cloud platform where we don’t need to worry about the hardware and software setup, security, performance, and CPU idle time costs. It means no configuration is required to run the code.

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

AWS Machine Learning - AI

This solution showcases how to bridge the gap between Google Workspace and AWS services, offering a practical approach to enhancing employee efficiency through conversational AI. Finally, the AI-generated response appears in the user’s Google Chat interface, providing the answer to their question.

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Leveraging Serverless and Generative AI for Image Captioning on GCP

Xebia

Leveraging Serverless and Generative AI for Image Captioning on GCP In today’s age of abundant data, especially visual data, it’s imperative to understand and categorize images efficiently. TL;DR We’ve built an automated, serverless system on Google Cloud Platform where: Users upload images to a Google Cloud Storage Bucket.

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Understanding Retrieval-Augmented Generation (RAG) on Google Cloud Platform (GCP)

Xebia

Jeroen will take you along RAG applications, and their implementations on Google Cloud Platform (GCP). Managed Approach – Use integrated services like Vertex AI Search, which handles retrieval and answer generation, simplifying system architecture. It allows you to insert data unseen to the model before.

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Extend large language models powered by Amazon SageMaker AI using Model Context Protocol

AWS Machine Learning - AI

We will deep dive into the MCP architecture later in this post. Using a client-server architecture (as illustrated in the following screenshot), MCP helps developers expose their data through lightweight MCP servers while building AI applications as MCP clients that connect to these servers.