Embedding Identity in Cloud Fabric with SPIFFE and Envoy

54% of cloud waste stems from a lack of cost visibility. Not over-provisioning. Not bad architecture. Visibility. You can't optimize what you can't see. And you can't see what you haven't instrumented. The good news: teams already using OpenTelemetry for performance monitoring are closer to solving this than they think. Source: Anodot / Finout 2026 Cloud Statistics #OpenTelemetry #FinOps #CloudCost #Observability

A California city believed their cloud environment was secure. Their SOC didn't have the visibility they thought it did. So they made a move most municipalities won't consider: out of Azure Government, into a smarter architecture. Zero downtime. Full compliance. And a foundation now built for AI. Swipe through to see how they did it.

"Building AI in the cloud? Make sure it’s secure first. 🔒 Natalie Godec, Senior Cloud Architect and Google Developer Expert, will be joining the Full Stack & Cloud Stage to explore what it truly means to build secure AI and cloud systems. In her talk, ��Secure By Design: Architecting your cloud and AI workloads from the perspective of infosec”, Natalie explains why you can’t “vibe-code” security. From infrastructure decisions to deployment pipelines, she will break down the essential principles of securing cloud workloads end-to-end - helping developers design systems that are resilient, scalable, and protected from day one. Join her on the Full Stack & Cloud Stage. 📍 Meet us at Romexpo, B1 Pavilion. 📅 June 3rd- 4th, 2026. 🎟️ Tickets available now: https://bit.ly/4pGgZa9

For over 25 years, I’ve been building systems across data, cloud, and enterprise environments. One thing has remained consistent. Documents are everywhere, but actually understanding them is still difficult. Most enterprise systems were built to store and manage files with access and control, but not to make the information truly usable. Even when data is extracted, it often sits disconnected from how work actually gets done. That gap is what led us to the start of Solarion AI. The goal is simple: make enterprise documents structured and usable in real workflows.

🏡 Partnering with Google Cloud, Fifth Dimension built a real estate operating system that connects disparate data sources into a single, consistent view. And with unified data as the foundation, Fifth Dimension’s AI agent Ellie can execute complex workflows with full context across the firm’s portfolio, not just the documents an analyst had time to manually assemble. Learn how Fifth Dimension helps real estate professionals do more of what they love — and less of what drains them. 🙌🏽 https://google.smh.re/5RCi

🏡 Partnering with Google Cloud, Fifth Dimension built a real estate operating system that connects disparate data sources into a single, consistent view. And with unified data as the foundation, Fifth Dimension’s AI agent Ellie can execute complex workflows with full context across the firm’s portfolio, not just the documents an analyst had time to manually assemble. Learn how Fifth Dimension helps real estate professionals do more of what they love — and less of what drains them. 🙌🏽 https://google.smh.re/5RAZ

Unstructured data is growing fast and traditional storage models aren’t keeping up. If you're managing hybrid cloud environments, object storage is key to controlling costs and supporting AI workloads. Get WEI's practical breakdown: https://lnkd.in/eU428RdR

Over the last 10 years I’ve worked on projects running across all three major clouds, as well as private/on-premise. One question always comes up: which cloud should we choose? Top 3 questions that most of the times decide fast: 1. Where the data should live Existing cloud agreements is most of the times preferred, if cost or other limitations do not exist. In EU we also introduce a few more policies (data residency) 2. Operational simplicity The best architecture is not the most sophisticated one. It’s the one the team can operate reliably day to day. If 100% have experiece with Azure, I can't choose AWS. 3. Cost predictability Not just raw cost, but how predictable it is when usage grows. Usually analyze 2-3 scenarios and agree on the possible deltas. Each provider has strengths, but the right choice is rarely about the technology alone. It’s mostly about the context in which the customer operates. Same with AI providers. Is just another tool linked to the cloud. #cloud

🏡 Partnering with Google Cloud, Fifth Dimension built a real estate operating system that connects disparate data sources into a single, consistent view. And with unified data as the foundation, Fifth Dimension’s AI agent Ellie can execute complex workflows with full context across the firm’s portfolio, not just the documents an analyst had time to manually assemble. Learn how Fifth Dimension helps real estate professionals do more of what they love — and less of what drains them. 🙌🏽 https://google.smh.re/5RES

You don't need a massive LLM for every task. Per-token pricing doesn't scale. And the teams who've been building ML solutions for years already know this. I wrote up why owning your inference stack — on-device, on-prem, or self-hosted in the cloud — is becoming and should be the default. It's the on-prem to cloud playbook, replayed in reverse. The more you own, the better the economics get. The hardware and models are evolving fast. Time to rethink the architecture. https://lnkd.in/gPghn8PQ Views are my own.