Cloud Computing

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 […]

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

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

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

We are excited to announce LlamaIndex integration for Gen AI Toolbox for Databases (Toolbox). We launched Toolbox in beta last month and are thrilled to continue building on that momentum. Gen AI Toolbox for Databases is an open-source server that streamlines the development and management of sophisticated generative AI tools that can connect to databases.

Software development teams are under constant pressure to deliver at an ever-increasing pace. As sponsors of the DORA research, we recently took a look at the adoption and impact of artificial intelligence on the software development lifecycle. The research shows that more than 75% of developers are relying on AI in their daily responsibilities. With