Cloud Computing

Google Cloud Next 25 Partner Summit: Session guide for partners

Partner Summit at Google Cloud Next ’25 is your opportunity to hear from Google Cloud leaders on what’s to come in 2025 for our partners. Breakout Sessions and Lightning Talks are your ticket to unlocking growth, mastering AI, and conquering the cloud marketplace. Sign-up today to secure your seat in one of the 40+ exclusive

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Vertex AI Search and Generative AI (with Gemini) achieve FedRAMP High

In the rapidly evolving AI landscape, security remains paramount. Today, we reinforce that commitment with another significant achievement: FedRAMP High authorization for Google Vertex AI Search and Generative AI on Vertex AI. This follows our announcement earlier this week where we shared that Gemini in Workspace apps and the Gemini app are the first generative

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Build richer gen AI experiences using model endpoint management

Model endpoint management is available on AlloyDB, AlloyDB Omni and Cloud SQL for PostgreSQL. Model endpoint management helps developers to build new experiences using SQL and provides a flexible interface to call gen AI models running anywhere — right from the database. You can generate embeddings inside the database, perform quality control on your vector

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Vector similarity search for Cloud SQL for MySQL is now GA

If you used the internet today, you’ve probably already benefited from generative AI. Whether it helped you get your work done faster, research home repairs, or find the perfect gift, gen AI is transforming how we get things done. These generative AI experiences use searches against vector embeddings — multi-dimensional representations of data’s meaning —

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Announcing BigQuery repositories: Git-based collaboration in BigQuery Studio

Modern data teams want to use Git to collaborate effectively and adopt software engineering best practices for managing their data pipelines and analytics code. But most tools used by data teams don’t offer integration with Git version control systems, making a Git workflow feel out of reach. This forces users to copy and paste code

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Harvesting hardware: Our approach to carbon-aware fleet deployment

When it comes to managing the infrastructure and AI that powers Google’s products and platforms – from Search to YouTube to Google Cloud – every decision we make has an impact. Traditionally, meeting growing demands for machine capacity means deploying new machines and that has an associated embodied carbon impact. That’s why we’re working to

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Master architecture decision records (ADRs): Best practices for effective decision-making

Architecture decision records (ADRs) help you document and communicate important process and architecture decisions in your engineering projects. Based on our experience implementing over 200 ADRs across multiple projects, we’ve developed best practices that can help you streamline your decision-making processes and improve team collaboration. In this post, you’ll learn: How to implement ADRs in

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Pilot light with reserved capacity: How to optimize DR cost using On-Demand Capacity Reservations

For digital enterprises to remain competitive, resilience is essential for maintaining reliability and building customer trust. End users expect applications to be available 24 hours a day, leading companies to develop increasingly sophisticated methods to provide continuous operation of critical services. Some companies, such as financial services companies, have to meet regulatory requirements such as

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Using RDMA over Converged Ethernet networking for AI on Google Cloud

All workloads are not the same. This is especially the case for AI, ML, and scientific workloads. In this blog we show how Google Cloud makes the RDMA over converged ethernet version 2 (RoCE v2) protocol available for high performance workloads. Traditional workloads Network communication in traditional workloads involves a well-known flow. This includes: Movement

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