Cloud Computing

Implement event-driven invoice processing for resilient financial monitoring at scale

Processing high volumes of invoices efficiently while maintaining low latency, high availability, and business visibility is a challenge for many organizations. A customer recently consulted us on how they could implement a monitoring system to help them process and visualize large volumes of invoice status events. This post demonstrates how to build a Business Event

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Understand why your metrics moved with contribution analysis in BigQuery ML, now GA

The key to effective data-driven decision making is quickly processing and extracting insights from large amounts of data. However, doing this efficiently and at scale is a challenge.  Imagine a retail scenario where you’re trying to identify the highest performing promotions by analyzing sales data across products, stores, locations, and a large customer base, in

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Inside Infinity Learn’s AI Tutor, powered by Google Cloud

Late-night study sessions, complex equations, and immense pressure: for millions of students in India, the IIT JEE Main exam and NEET for medical colleges are critical gateways for their futures. Exam success hinges on intricate reasoning within physics, chemistry, mathematics, zoology, and botany. These students require a clear, step-by-step understanding of the topics, not just

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Multi-cloud AI made easier: Aiven for AlloyDB Omni now generally available

Building modern, data-driven applications requires a database that can handle transactional, analytical, and vector search workloads, especially as AI and machine learning become increasingly vital. You need a solution that scales, maintains compliance, delivers consistent performance, and that doesn’t require constant re-architecting. Whether you’re building transactional, translytical, or generative AI applications across one or multiple

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From LLMs to image generation: Accelerate inference workloads with AI Hypercomputer

From retail to gaming, from code generation to customer care, an increasing number of organizations are running LLM-based applications, with 78% of organizations in development or production today. As the number of generative AI applications and volume of users scale, the need for performant, scalable, and easy to use inference technologies is critical. At Google

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Deploy to ARM-Based Compute with AWS Deploy Tool for .NET

We’re excited to announce that the AWS Deploy Tool for .NET now supports deploying .NET applications to select ARM-based compute platforms on AWS! Whether you’re deploying from Visual Studio or using the .NET CLI, you can now target cost-effective ARM infrastructure like AWS Graviton with the same streamlined experience you’re used to. Why deploy to

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