Cloud Computing

Today, we are excited to announce fully managed tiered storage for Spanner, a new capability that lets you use larger datasets with Spanner by striking the right balance between cost and performance, while minimizing operational overhead through a simple, easy-to-use, interface. Spanner powers mission-critical operational applications at organizations in financial services, retail, gaming, and many […]

Written by: Dhanesh Kizhakkinan, Nino Isakovic Executive Summary This blog post presents an in-depth exploration of Microsoft’s Time Travel Debugging (TTD) framework, a powerful record-and-replay debugging framework for Windows user-mode applications. TTD relies heavily on accurate CPU instruction emulation to faithfully replay program executions. However, subtle inaccuracies within this emulation process can lead to significant

Fraud detection is a critical challenge for call centers, they need to provide a seamless customer experience while protecting the organization from fraudulent activities. Traditionally, call centers have relied on agents to manually screen calls, which can be time-consuming and expensive. Alternatively, companies might force customers to authenticate themselves every time they call, leading to

Kubernetes, the container orchestration platform, is inherently a complex, distributed system. While it provides resilience and scalability, it can also introduce operational complexities, particularly when troubleshooting. Even with Kubernetes’ self-healing capabilities, identifying the root cause of an issue often requires deep dives into the logs of various independent components. At Google Cloud, our engineers have

AI Hypercomputer is a fully integrated supercomputing architecture for AI workloads – and it’s easier to use than you think. In this blog, we break down four common use cases, including reference architectures and tutorials, representing just a few of the many ways you can use AI Hypercomputer today.  Short on time? Here’s a quick

Today, we’re announcing built-in performance monitoring and alerts for Gemini and other managed foundation models – right from Vertex AI’s homepage. Monitoring the performance of generative AI models is crucial when building lightning-fast, reliable, and scalable applications. But understanding the performance of these models has historically had a steep learning curve: in the past, you