#Gemini
21 articles filed under this tag
Google Cloud Blueprint: Predictable AI spend in BigQuery: Introducing cost management — How Does It Work?
Architectural Thesis: The generative AI functions in BigQuery ( AI.GENERATE , AI.IF , AI.CLASSIFY , AI.SCORE , and more) bring large language models (LLMs) directly into your SQL, so a single query can classify millions of support tickets or score each product... Real-World Field Use Cases: 1. High-Throughput Enterprise...
Google Cloud Blueprint: Gemini 4 Argon available on Google Cloud, built to help solve your — How Does It Work?
Architectural Thesis: Last week we announced that Gemini Enterprise has evolved to make it even simpler to get work done, and introduced the Gemini agent , your new universal agent for work. It's always on and ready to answer your questions. It will write code... Real-World Field Use Cases: 1. High-Throughput Enterprise...
Google Cloud Blueprint: Welcome to Gemini at Work 2026: Introducing the Gemini agent — How Does It Work?
Architectural Thesis: Editor’s note: This article is adapted from Thomas Kurian’s keynote address at Gemini at Work 2026. It includes a number of announcements: Gemini , a single, universal agent for work that answers your questions, handles your knowledge... Real-World Field Use Cases: 1. High-Throughput Enterprise...
Google Cloud Blueprint: Cloud CISO Perspectives: Sticking to security fundamentals in the AI — How Does It Work?
Architectural Thesis: Welcome to the first Cloud CISO Perspectives for August 2026. Today, Chris Betz explains why the AI era makes it more important than ever to lean into security fundamentals. As with all Cloud CISO Perspectives, the contents of this... Real-World Field Use Cases: 1. High-Throughput Enterprise Workloads...
Google Cloud Blueprint: FinOps for the AI era: New flexible billing and cost controls — How Does It Work?
Architectural Thesis: Editor's note: A product image was updated after initial publication. As AI takes on more complex work, business leaders face a new challenge: enabling rapid innovation using agents while protecting their margins and budgets. To get a real... Real-World Field Use Cases: 1. High-Throughput Enterprise...
Google Cloud Blueprint: Why your startup needs open models alongside frontier APIs — How Does It Work?
Architectural Thesis: Every week, I talk with founders who are building at an unbelievable pace. Teams are moving from inception to product-market fit faster than ever, with foundation models wired deeply into their core product workflows. Yet as startup... Real-World Field Use Cases: 1. High-Throughput Enterprise Workloads...
Google Cloud Blueprint: The three things today's hottest startups are looking for in their AI — How Does It Work?
Architectural Thesis: 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... Real-World Field Use Cases: 1. High-Throughput Enterprise...
Google Cloud Blueprint: Reimagining work: How Pythian’s internal AI playbook delivers customer — How Does It Work?
Architectural Thesis: When Pythian rolled out Google Cloud’s Gemini Enterprise across our 500-person company in 27 countries, the goal was simple: use our own company as a proving ground to discover how enterprise AI actually delivers ROI. What we found changed... Real-World Field Use Cases: 1. High-Throughput Enterprise...
Google Cloud Blueprint: What’s new in AI infrastructure and orchestration in August — How Does It Work?
Architectural Thesis: Welcome back to What’s new in AI infrastructure and orchestration this month , a collection of product updates, how-tos, customer stories, research and other resources about all the AI compute, networks, storage, frameworks, and... Real-World Field Use Cases: 1. High-Throughput Enterprise Workloads...
Getting started with Mantis, our open-source bug finding-and-fixing harness — How Does It Work in Production?
<div class="block-paragraph_advanced"><p><span style="vertical-align: baseline;">AI models have clearly proven their ability to discover and exploit vulnerabilities without much, if any, human assistance. To help defenders gain the advantage with AI, we built Real-World Field Use Cases: 1. High-Throughput Production...
Agentic FinOps on Google Cloud: Automating Cloud Spend Accountability at Scale — How Does It Work in Production?
How enterprise engineering teams deploy Agentic FinOps architectures using Google ADK and Gemini on Google Cloud to automate BigQuery billing anomaly detection and cloud spend accountability at scale.
Cloud CISO Perspectives: Autonomous AI Threat Detection and Enterprise Defense on GCP — How Does It Work?
Welcome to the first Cloud CISO Perspectives for September 2026. Sandra Joyce shares the latest details on Google visibility into how attackers use AI and how enterprise security teams use autonomous defenses to stop them. Real-World Field Use Cases: 1. High-Throughput Enterprise Workloads: Isolating P99 tail-latency and...
Google Cloud Media Delivery at Scale: Serving Billions of Concurrent IPL Requests — How Does It Work in Production?
For the millions of fervent fans of the Indian Premiere League (IPL), being able to count on a flawless live streaming cricket experience is never up for debate. For Airtel, producing league TV broadcasts with some of the world's most massive concurrent viewer Real-World Field Use Cases: 1. High-Throughput Enterprise...
Google Cloud Blueprint: Spanner Migrations and Automating Dual-Write with Antigravity CLI — How Does It Work?
Architectural Thesis: When Google's Finance Engineering team needed to modernize their legacy data layer, they chose Spanner , a globally distributed, strongly consistent, multi-model database with high availability capabilities. But migrating to Spanner... Real-World Field Use Cases: 1. High-Throughput Enterprise Workloads...
Google Cloud Blueprint: Google is a Leader in the 2026 Gartner® Magic Quadrant™ for Enterprise — How Does It Work?
Architectural Thesis: We are excited to share that Gartner has named Google a Leader in its inaugural 2026 Magic Quadrant for Enterprise AI Assistants . In this comprehensive evaluation of top enterprise AI assistant vendors, Gartner placed Google in the... Real-World Field Use Cases: 1. High-Throughput Enterprise Workloads...
Cloud SQL PostgreSQL 17 + pgvector: Hybrid HNSW Indexing at 10,000 QPS
Combining relational ACID guarantees with sub-10ms semantic vector retrieval over Unix domain sockets in Cloud Run.
Cloud Storage FUSE Gen 2: Zero-Redeploy Content Lakes for Next.js 15
Eliminating daily Docker rebuilds by mounting GCS buckets directly into Cloud Run with gRPC metadata caching.
BigQuery Physical Storage Billing: Achieving 8x Compression on Telemetry Tables
Step-by-step FinOps migration blueprint from logical active/long-term bytes to physical compressed storage with time-travel tuning.
Vertex AI Context Caching: Cutting Enterprise LLM Inference Costs by 75%
Production patterns for caching massive system prompts, RAG corpora, and multi-turn conversation prefixes in Gemini.
Google Cloud Enterprise AI: Production Multi-Agent Systems with ADK
Deep-dive into enterprise agent governance, Vertex AI grounding, and zero-cold-start Cloud Run serverless deployment.
The Architect's Dilemma: Deconstructing the Myth of the 'Sleeping Giant' (The Google Story)
Why the narrative that Google was caught asleep by the AI wave is a convenient fiction—and how a 25-year arc from Noam Shazeer's 2001 PHIL project to TPUs, Transformers, and Gemini solved the ultimate Innovator's Dilemma.