Cloud Computing

Announcing the AWS Digital Sovereignty Well-Architected Lens

As organizations accelerate cloud adoption, meeting digital sovereignty requirements has become essential to build trust with customers and regulators worldwide. The challenge isn’t whether to adopt the cloud—it’s how to do so while meeting sovereignty requirements, using a multidisciplinary approach. Even though requirements vary by geography, organizations commonly address them through technical and operational controls

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How Artera enhances prostate cancer diagnostics using AWS

This post was co-written with Hariharan Ananthakrishnan from Artera. Artificial intelligence (AI) and machine learning (ML) are transforming cancer diagnosis and treatment, enabling faster and more accurate decisions for patients. One company at the forefront of this transformation is Artera, a precision medicine company developing an AI-powered platform for cancer treatment planning. The U.S. Food

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Introducing Google Cloud Vertex AI Extensions for .NET

In October 2024, Microsoft announced the Microsoft.Extensions.AI.Abstractions and Microsoft.Extensions.AI libraries for .NET. These libraries provide the .NET ecosystem with essential abstractions for integrating AI services into .NET applications from various providers such as Open AI, Azure, Google. Today, we’re happy to announce the Google.Cloud.VertexAI.Extensions library. This is the Vertex AI implementation of Microsoft.Extensions.AI. This library

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BigQuery AI Hackathon: Celebrating Innovation and a Look at What’s New

aside_block <ListValue: [StructValue([(‘title’, ‘DISCLAIMER’), (‘body’, <wagtail.rich_text.RichText object at 0x7f377a87f280>), (‘btn_text’, ”), (‘href’, ”), (‘image’, None)])]> The BigQuery AI Hackathon, a six-week event that concluded on September 22, 2025, brought together thousands of developers from across the globe to build innovative solutions using BigQuery’s cutting-edge AI capabilities. With 5,350 entrants and 277 submissions, the hackathon was

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Accelerate GKE cluster autoscaling with faster concurrent node pool auto-creation

We’re excited to announce concurrency in Google Kubernetes Engine (GKE) node pool auto-creation, to significantly reduce provisioning latency and autoscaling performance. Internal benchmarks show up to an 85% improvement in provisioning speed, especially benefiting heterogeneous workloads, multi-tenant clusters, workloads that use multiple ComputeClass priorities, and large AI training workloads, by cutting deployment time and enhancing

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