Processing millions of user reviews in real-time, under strict latency and cost constraints, is no easy task. Trustpilot has been doing exactly that with custom machine learning since long before large language models (LLMs) were cool. Now, as the company transitions its core stack to generative AI, here is a look at how we teamed up to build a high-volume streaming pipeline using fine-tuned Gemma models. Powering deep review intelligence at scale Trustpilot’s core business relies on delivering

AI & Machine LearningCustomers

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ExternalCloud

Google Cloud Blog1 Jun 2026

The fully-managed Remote MCP Server for AlloyDB is now Generally Available

AI agents possess incredible reasoning capabilities and can perform increasingly complex actions. But the reliability of agentic outcomes depends entirely on the quality of the context they can access — context that is frequently locked away in operational databases. To bridge this gap, we are excited to announce the Remote Model Context Protocol (MCP) Server for AlloyDB is now generally available. The Model Context Protocol (MCP) is an open-source standard that gives LLMs a secure, consistent

AI & Machine LearningData Analytics

Google Cloud BlogRead original

ExternalCloud

Google Cloud Blog1 Jun 2026

Modeling a digital twin of a food supply chain using BigQuery Graph

The example of a growing restaurant Imagine you are running a restaurant chain. You just can't physically feel and touch things to know how your business operates. You need tools and a digital replica of your business to sense the health of the business for you. The friction of growth Growth creates a unique kind of friction that spreadsheets simply weren't built to solve: The bullwhip effect: Small downstream demand shifts swell into upstream inventory tidal waves. SOP drift: Tiny departures fr

BigQueryDatabasesData Analytics

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ExternalCloud

Google Cloud Blog1 Jun 2026

Introducing the GKE standby buffer: Improve node startup times without blowing your budget

Application owners and platform engineers have long faced a difficult choice: spend excessively by over-provisioning to guarantee quick startups, or minimize costs but endure slow cold starts. We are excited to announce a solution to this compromise: Google Kubernetes Engine standby buffers. This builds on the launch of GKE active buffers earlier this year, a native version of the Kubernetes CapacityBuffers API that makes it easy to provision readily available capacity to handle traffic spikes,

GKEContainers & Kubernetes

Google Cloud BlogRead original

ExternalCloud

Google Cloud Blog1 Jun 2026

What Google Cloud announced in AI this month

Editor’s note: Want to keep up with the latest from Google Cloud? Check back here for a monthly recap of our latest updates, announcements, resources, events, learning opportunities, and more. We’ve had a busy month! Between announcing Gemini Spark and Gemini 3.5 at Google I/O – and unveiling Google AI Threat Defense, our latest AI-powered cybersecurity solution, we had a lot to share with Google Cloud customers. Keeping up with the latest news takes time, so we gathered the most important ann

Google CloudAI & Machine Learning

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ExternalObservability

Grafana Blog1 Jun 2026

Tempo 3.0 release: a new architecture for scale and lower TCO, TraceQL metrics GA, and more

Tempo started with a simple goal: make distributed tracing easier to run at scale. As tracing adoption has grown, however, so have the challenges, including higher data volumes, more complex architectures, and increasing demand for real-time insights directly from traces. Over the last year, we’ve been evolving Tempo’s architecture to meet that moment. And today, we’re sharing the results of those efforts with the release of Tempo 3.0. The latest major release of the open source distributed trac

Grafana BlogRead original

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