For more than a decade, TPUs have powered Google’s most demanding AI training and serving workloads. And there is strong demand from customers for Cloud TPUs as well. When running advanced AI workloads, you need to be able to monitor and optimize the efficiency of your training and inference jobs, and swiftly diagnose performance bottlenecks, […]
Announcing a new monitoring library to optimize TPU performance Read More »
As developers and operators, you know that having access to the right information in the proper context is crucial for effective troubleshooting. This is why organizations invest a lot upfront curating monitoring resources across different business units: so information is easy to find and contextualize when needed. Today we are reducing the need for this
Application monitoring in Google Cloud: Bridging manual and AI-assisted troubleshooting Read More »
As organizations race to deploy powerful GPU-accelerated workloads, they might overlook a foundational step: ensuring the integrity of the system from the very moment it turns on. Threat actors, however, have not overlooked this. They increasingly target the boot process with sophisticated malware like bootkits, which seize control before any traditional security software can load
How to enable Secure Boot for your AI workloads Read More »
In this post, we show you how to implement comprehensive monitoring for Amazon Elastic Kubernetes Service (Amazon EKS) workloads using AWS managed services. Amazon EKS offers compelling solutions with EKS Auto Mode and AWS Fargate, each designed for different use cases. This solution demonstrates building an EKS platform that combines flexible compute options with enterprise-grade
Implement monitoring for Amazon EKS with managed services Read More »
Research scientist John Flournoy sits down with Ryan and Eira to dive into the recent research around developer experience, including the nuances of measuring productivity, the potential reasons for variability in developer performance, and the impacts of collaboration and competition on developer efficiency.
How to do your job happier Read More »
The AWS SDK for Java 2.x introduces the Apache 5 SDK HTTP client which is built on Apache HttpClient 5.5.x. This new SDK HTTP client is available alongside our existing SDK HTTP clients: Apache HttpClient 4.5.x, Netty, URL Connection, and AWS CRT HttpClient. To differentiate the use of Apache HttpClient 4.5.x and Apache HttpClient 5.5.x,
Preview Release of the AWS SDK Java 2.x HTTP Client built on Apache HttpClient 5.5.x Read More »
Welcome to the first Cloud CISO Perspectives for July 2025. Today, Sandra Joyce, vice president, Google Threat Intelligence, talks about an incredible milestone with our Big Sleep AI agent, as well as other news from the intersection of security and AI. As with all Cloud CISO Perspectives, the contents of this newsletter are posted to
Cloud CISO Perspectives: Our Big Sleep agent makes a big leap, and other AI news Read More »
Partners have always been central to the Google Cloud ecosystem, becoming more and more instrumental in bringing Google’s AI innovations to enterprises. I am inspired by how partners have already built more than 1,000 agentic use cases across every domain to solve deeply entrenched pain points for our shared customers. The emergence of agentic AI
Shaping the future together with our partners: The potential of agentic AI Read More »
Apache Spark is the cornerstone for large-scale data processing, model training, and inference for AI/ML workloads. Yet, the complexities of environment configuration, dependency management, and MLOps integration can slow you down. To accelerate your AI/ML journey, Dataproc now delivers powerful, ML-ready capabilities for Spark. Available on both Dataproc on Compute Engine clusters and Google Cloud
AI/ML-ready Apache Spark with Dataproc Read More »
Tzafon, a San Francisco-based startup and AI R&D lab, is partnering with Google Cloud to utilize Google’s AI-optimized infrastructure and cloud services, which will help Tzafon deliver automation at large scale. The Tzafon team aims to do this by building systems and models that can support multiple, autonomous AI agents that are capable of working
Tzafon selects Google Cloud to build next generation agentic machine intelligence Read More »
