At Google Cloud, we’re committed to providing the most advanced, secure, and private infrastructure for the most demanding AI workloads, and partnering with a broad and diverse range of organizations to help them meet their AI workload needs. We are thrilled to collaborate with Apple on its expanded Private Cloud Compute (PCC) systems announced this week at WWDC 2026. Working…
Google Cloud
https://cloud.google.com/blog/ · 23 posts · history since 2026 · active
Yesterday
Dashboards have long served as a primary way for organizations to extract insights from data, but they can fall short in agile environments: Dashboards aren’t interactive and don’t allow you to ask follow-up questions. This forces users to step outside their workflows or turn to data analysts to get the answers they need. Today, we are introducing Looker dashboard agents…
Introduction Mandiant and Google Threat Intelligence Group (GTIG) have identified an active compromise and extortion campaign attributed to UNC6240 (ShinyHunters) targeting Oracle PeopleSoft application infrastructure. The activity was observed between May 27, 2026, and June 9, 2026 and is consistent with the exploitation of CVE-2026-35273, a critical remote code execution vulnerability (CVSS 9.8) in the Environment Management component. The exploitation…
Look at any builder's prompt history and you'll see a collection of highly specific, sometimes chaotic, one-off prompts. We use AI to debug a single error message, refactor a messy email, or generate a quick boilerplate. If you sit down with people who consistently ship high-quality work, you'll find something interesting. They aren't just improvising. They have a set of…
10 Jun
From foundational ETL and analytics to the frontier of generative AI, Apache Spark serves as the architectural backbone for global data processing. However, as data volumes scale, the trade-off between performance and infrastructure costs can be a limiting factor for growth. In the agentic era, where autonomous agents can trigger thousands of concurrent, multi-hop queries, this performance bottleneck directly dictates…
TL;DR: Antigravity 2.0: A desktop app to orchestrate multiple autonomous agents working in parallel across independent projects. Antigravity CLI: A terminal interface designed for command-line workflows and headless execution. Antigravity IDE: An editor for developers who want to write code directly alongside an agent. Antigravity SDK: A Python library for building and deploying your own custom agents that use the…
9 Jun
Claude Fable 5, Anthropic’s latest frontier model, is now generally available on Google Cloud. This launch is the latest proof point of our ongoing commitment to bring the industry's latest models straight to our Agent Platform. Claude Fable 5 brings the best of Anthropic model capabilities to all customers, with strong safeguards designed to make it safe for general use.…
The public sector has reached a critical inflection point. For years, organizations have explored what’s possible through isolated AI pilots and experimentation. Today, the question has shifted to “what creates impact?” where the focus is no longer on hypotheticals, but on achieving real productivity gains, improving services and outcomes, and advancing your mission - right now. Meeting this moment requires…
As generative AI moves from experimental pilots to massive production environments, the efficiency of your infrastructure becomes the ultimate differentiator. One way to get the most out of it and minimize costly accelerator idle time is to leverage the Google Kubernetes Engine (GKE) Inference Gateway, which intelligently routes generative AI workloads based on real-time model server metrics. Instead of relying…
As enterprise storage footprints scale to billions of objects, AI applications and agentic workloads are fundamentally shifting the role of storage from a passive repository to the foundation of the data platform. This is driven by a surge in unstructured model data and the billions of actions performed on those objects, including session logs and audit trails. To manage this…
How do you prove the business value of generative AI to your teams? Technology and finance leaders need to show the clear business value of AI projects to secure ongoing funding. While measuring return on investment (ROI) is a key part of validating your technical strategy, long-term success ultimately depends on building the organizational systems and culture needed to make…
To defend against the growing range of AI-accelerated threat actors, organizations need to be able to respond faster to outpace the adversary. Recently, we announced Google AI Threat Defense, an automated security system designed to help you continuously monitor for and stop AI-powered threats before they can impact your business. Based on Google’s own approach to today’s threats and vulnerability…
8 Jun
In clinical informatics, every second counts. For Alcidion, a global leader in smart health solutions, the mission is simple but critical: use technology to reduce cognitive load for clinicians and present the right information at the right time to save lives. Whether it’s managing patient flow in an emergency department or ensuring a patient is in the correct ward to…
5 Jun
Want to know the latest from Google Cloud? Find it here in one handy location. Check back regularly for our newest updates, announcements, resources, events, learning opportunities, and more. Tip: Not sure where to find what you’re looking for on the Google Cloud blog? Start here: Google Cloud blog 101: Full list of topics, links, and resources. aside_block <ListValue: []>…
Written by: Chad Reams, Tufail Ahmed, Keith Knapp, Ashley Frazer, Tyler McLellan Introduction From January through May 2026, Mandiant identified a financially motivated data theft extortion campaign executed by the threat cluster UNC3753 (also tracked as "Luna Moth," “Chatty Spider,” and "Silent Ransom Group") targeting dozens of organizations across professional, legal, and financial services in the United States. UNC3753 leverages…
4 Jun
At Google Cloud, our goal is to let you run large-scale analytical and data science workloads with maximum efficiency so you can process big data pipelines, machine learning, and ETL tasks. We recently announced that the Dataproc service is now Managed Service for Apache Spark, reflecting our deep integration with the Agentic Data Cloud. To support the diverse architectural needs…
June 1 - June 5 Beyond the Query: Powering AI Agents with Bigtable, Firestore & Memorystore Discover the latest advancements in Google Cloud's NoSQL Database portfolio, including Bigtable, Firestore, and Memorystore. This series is designed for a broad audience: whether you are exploring these databases for the first time or are an existing user looking to leverage the new capabilities…
While building AI agents locally using Google’s Agent Development Kit (ADK) is an excellent way to prototype, production-ready agents require a robust, scalable infrastructure. For developers looking to move beyond simple instances and into the world of managed container orchestration, Google Kubernetes Engine (GKE) Autopilot offers the perfect balance of flexibility and ease of use. In this tutorial, I will…
3 Jun
Whether you use it for data preparation, real-time interactive queries, AI model training, or something entirely different, running Apache Spark at scale is demanding — you shouldn’t have to manage the underlying infrastructure too. Late last year, we announced the general availability (GA) of our serverless Managed Service for Apache Spark runtime version 3.0, prioritizing speed, simplicity, and reliability. Since…
2 Jun
Google Cloud Storage (GCS) is a foundational component of the modern agentic tech stack and the preferred home for unstructured data at scale. As enterprises deploy agents in production, the critical focus has shifted to turning data into context and building secure, standardized integrations to access context. This is the core of smart storage: making unstructured data inherently agent-ready by…
Many data engineers spend significant time managing compatibility and getting best performance across multiple analytics engines. To help solve this pain point, we are excited to announce gcs-analytics-core, a new open-source Java library designed to centralize and accelerate analytics optimizations for Google Cloud Storage (GCS). With this, you get the flexibility to select your preferred analytics engine while achieving high…
At Google Cloud Next, we announced the preview of graph algorithms with Spanner Graph, bringing Google Research’s state-of-the-art graph mining capabilities natively to your database. These graph intelligence capabilities can help you derive valuable insights from graph data faster, cheaper, and at scale. Enterprises are increasingly leveraging graph technologies to uncover complex relationships in data for use cases such as…
What happens when your workload fails in one region but you need access to service? This is a common case for availability and uptime. With recent enhancement to the Kubernetes ecosystem and capabilities like Dynamic Resource Allocation (DRA) and Inference Gateway. I decided to experiment with these capabilities in Google Cloud for a simple test using an AI inference workload.…