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ExternalAI
AWS Machine Learning Blog

Scaling cloud migrations with agentic AI on Amazon Bedrock AgentCore

Learn how AWS Professional Services uses a multi-agent framework built on Amazon Bedrock AgentCore to automate enterprise cloud migrations end to end. Purpose-built AI agents handle discovery, infrastructure as code generation, portfolio governance, and post-migration operations, reducing IaC development time from weeks to minutes.

Advanced (300)Amazon Bedrock AgentCoreTechnical How-to
AWS Machine Learning BlogRead original
ExternalAI
AWS Machine Learning Blog

AWS vector solutions: Build agentic AI where your data lives

AWS offers a broad portfolio of vector search built directly into the databases and storage services you already use, with no standalone vector database or data migration required. This post covers six purpose-built services, a decision framework for choosing the right engine, and customer proof points for each.

Amazon AuroraAmazon DynamoDBAmazon ElastiCache
AWS Machine Learning BlogRead original
ExternalDevOps
CNCF Blog

Announcing H1 2027 KCDs

Get ready to connect, learn, and innovate right in your backyard. Kubernetes Community Days (KCDs) are officially kicking off for H1! Supported by the Cloud Native Computing Foundation (CNCF), these community-organized events bring open source adopters...

Blog
CNCF BlogRead original
ExternalSoftware Engineering
DZone

When Downtime Means an Unlocked Front Door

Anyone who has carried a pager long enough develops a professional numbness. A queue backs up, a p99 drifts past budget, a deploy does something stupid at 40% rollout. You fix it, you write it up, you go back to sleep. The stakes are real but abstract: revenue per minute, an SLA credit, a churn number on somebody's spreadsheet. That numbness doesn't survive contact with a product people rely on for safety.

DZoneRead original
ExternalAI
NVIDIA Technical Blog

How Generative Recommenders Are Redefining RecSys at Scale

Recommender systems (RecSys) are one of the most ubiquitous machine learning problems in the consumer internet industry yet notoriously difficult to train and... Recommender systems (RecSys) are one of the most ubiquitous machine learning problems in the consumer internet industry yet notoriously difficult to train and serve at scale. The advent of LLMs has inspired a shift from the traditional embedding-similarity-based objective to a generative one, where the goal is to predict the next action

NVIDIA Technical BlogRead original
ExternalCloud
Google Cloud Blog

10 questions every startup should answer before moving to production with their AI prototype

It’s never been easier to start an AI-powered startup on Google Cloud.  You grab an API key from Google AI Studio at breakfast, paste it into Antigravity, and by lunch you’ll have a nascent prototype of your product. But it’s not all one straight line to progress. It's common to bump into these three challenges as you build out your stack: A leaked API key racks up a large bill in 48 hours. A "quick" migration from AI Studio to Gemini Enterprise Agent Platform stalls the roadmap for weeks becaus

AI & Machine LearningStartupsDevelopers & Practitioners
Google Cloud BlogRead original
ExternalCloud
Google Cloud Blog

Google is a Leader in the 2026 Gartner® Magic Quadrant™ for Cloud-Native Application Platforms

We are thrilled to announce that Google has been recognized as a Leader for the third year in a row in the 2026 Gartner® Magic Quadrant™ for Cloud-Native Application Platforms (CNAP). We believe this placement in the Leaders quadrant validates our commitment to providing an accessible, developer-centric platform that accelerates onboarding and supports rapid prototyping across modern workloads. Our vision for an application-centric cloud focuses on enabling developers to prioriti

GKEServerlessApplication Development
Google Cloud BlogRead original
ExternalCloud
Google Cloud Blog

How AlloyDB ScaNN scales vector search to 10 billion vectors

To satisfy the demands of enterprise-grade agentic AI applications, underlying vector databases often struggle to scale effectively as modern use cases can scale to billions of vectors. As a fully managed PostgreSQL-compatible database service, AlloyDB is engineered to handle demanding enterprise workloads. Combining Google's infrastructure with the reliability of commercial databases, it delivers high availability, scalability, and includes a cutting-edge analytical engine, optimal for agentic

AI & Machine LearningDatabases
Google Cloud BlogRead original

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