Cloud Computing

Introduction The landscape of software supply chain security has undergone a significant shift. Recent campaigns demonstrate that sophisticated threat actors are systematically targeting the engineering lifecycle by compromising trusted security and programming tools. These intrusions reveal three key tactics: Attackers target trusted security scanners, utility libraries, and AI developer tools to exploit the elevated privileges […]

The availability of resources for AI workloads can be challenging across the industry, especially accelerators. This can slow your AI workload deployment if it’s built around a specific type of accelerator. The concept of fluid compute allows you to design your AI deployment with several options based on available resources that can fit your use

Google Cloud has become the platform of choice for startups building AI.  Our uniquely complete stack — including a choice of first- and third-party compute and models; our platform for building and managing agents; and our products for securing AI workloads — has emerged as the single most important driver of this growth and it

True elasticity has long been the holy grail of cloud-native engineering. And while Kubernetes has revolutionized resource management, workloads that run sporadically (e.g., batch processors, event-driven workers, and development environments) still consume compute resources while they wait for work, driving up costs. We’re addressing this head-on in Google Kubernetes Engine (GKE) 1.37 with a native

Earlier this year, we announced native support for Google Kubernetes Engine (GKE) custom metrics. This milestone allowed you to scrap external adapters and instead collect autoscaling metrics directly from your pods. By routing these metrics straight to the Horizontal Pod Autoscaler (HPA), we cut metrics reading latency down to 5 seconds. Today, we are excited

In real-time streaming, every millisecond counts.  For example, at 30 frames per second (fps), developers have a strict frame budget of just 33.3 ms (and only 16.6 ms at 60 fps) to ingest camera frames, run neural segmentation, apply shaders, and composite output. Exceeding that budget by even a fraction of a millisecond leads to

For years, the workday looked remarkably consistent. Employees logged into devices, opened browsers and toggled across a dozen disconnected applications. Users acted as the bridge between apps, copying from one tab and pasting into another. Now, agentic workflows that are faster and allow employees to be even more productive are on the rise. Employees take