Cloud Computing

Cloud Run has long provided developers with a straightforward, opinionated platform for running code. You can easily deploy request-driven web applications using Cloud Run services, or execute run-to-completion batch processing with Cloud Run jobs. However, as developers build more complex applications, like pipelines that process continuous streams of data or distributed AI workloads, they need

In modern microservices architectures, configuration management remains one of the most challenging operational concerns. Two gaps emerge as organizations scale: handling tenant metadata that changes faster than cache TTL allows, and scaling the metadata service itself without creating a performance bottleneck. Traditional caching strategies force an uncomfortable trade-off: either accept stale tenant context (risking incorrect

In today’s global economy, data is a strategic asset. For many organizations — particularly those in highly regulated industries and the public sector — the ability to innovate with AI is often balanced against the rigorous requirements of data sovereignty, residency, and operational autonomy. We are proud to announce that Google Cloud has been named

In the world of AI/ML, data is the fuel that drives training and inference workloads. For Google Kubernetes Engine (GKE) users, Cloud Storage FUSE provides high-performance, scalable access to data stored in Google Cloud Storage. However, we learned from customers that getting the maximum performance out of Cloud Storage FUSE can be complex. Today, we

Today, at the Apache Iceberg Summit in San Francisco, we are announcing the preview of read and write interoperability between BigQuery and Iceberg-compatible engines, including Trino, Spark, and others in Apache Iceberg tables in Google-managed Iceberg REST Catalog. With this new capability, you get the benefits of enterprise-grade native storage for your lakehouse without sacrificing

Building and serving models on infrastructure is a strong use case for businesses. In Google Cloud, you have the ability to design your AI infrastructure to suit your workloads. Recently, I experimented with Google Kubernetes Engine (GKE) managed DRANET while deploying a model for inference with NVIDIA B200 GPUs on GKE. In this blog, we

Claude Mythos Preview, Anthropic’s newest and most powerful model, is now available in Private Preview to a select group of Google Cloud customers, as part of Project Glasswing.  The availability of Claude Mythos Preview on Vertex AI underscores our commitment to offer our customers access to models from frontier AI labs. Combined with the enterprise-grade