Operations | Monitoring | ITSM | DevOps | Cloud

The regulatory landscape governing UK sovereign cloud security has shifted more dramatically in the past 12 months than in the preceding decade. New legislation, tightened procurement frameworks, and an intensifying cyber threat environment are collectively raising the compliance floor for organizations running cloud workloads in the UK.

Sovereignty is one of those words that gets stretched until it means almost nothing. Vendors apply it to any infrastructure with a UK data center, regardless of who owns the parent company or which jurisdiction's courts govern the contract. For a developer running a personal project, that ambiguity is probably fine. For a fintech under FCA oversight, an NHS trust processing patient data, or a legal firm handling privileged communications, it isn't.

In India, data sovereignty has moved from a technical detail to a boardroom priority, and in some industries, a non-negotiable requirement. Over the past few years, India’s regulatory environment has evolved quickly.

March signified a very important period for the Konstruct team, where we were able to focus on something we’ve heard consistently from teams: reduce the time to value without compromising control. In the previous post, we walked through how Konstruct 0.1–0.3 established the core platform model, introduced templates, and expanded GitOps into something that can represent both infrastructure and applications. With 0.4, we’re taking a more opinionated step forward.

The UK’s Competition and Markets Authority (CMA) has now set out its latest actions under the Digital Markets Competition Regime (DMCR), following its multi-year Cloud Services Market Investigation. While the regulator has now expanded its focus into business software ecosystems, we must not lose sight of the core issue: the entrenched dominance within the UK's cloud infrastructure.

Back in 2016, Jonathan Ross founded Groq, the AI chip startup, which went on to enter a non-exclusive licensing agreement with NVIDIA for Groq’s inference technology (as part of a $20 billion deal). The name ‘Groq’ is commonly confused with X (formerly Twitter)’s Grok, which was launched in 2023 as a Gen AI chatbot. As demand for real-time AI continues to grow, inference has become one of the most important and expensive parts of the machine learning lifecycle.

While GPUs remain among NVIDIA's flagship products, they also offer a range of other compute products beyond the dedicated graphics cards for which they are known. If you are unfamiliar with the words DGX or HGX, this blog is for you. Throughout this blog, we will cover what these terms mean in practice and when you should be using them.

For seven years, I've watched the same pattern. An organization decides it needs a platform and assigns two of its best engineers. They estimate it will take three months, but eighteen months later, they're still integrating ArgoCD with their secrets manager, still debugging Crossplane providers, and still arguing about how to structure the GitOps repo. What’s happened is they’ve built something that works for one team and can't be repeated for a second.

Every year, NVIDIA GTC offers a glimpse into the future of computing. But this year felt different. The conversations from the past few days point to something bigger than faster GPUs or larger models. The industry is shifting its mindset entirely. GTC 2026 made it clear that the goalposts for AI haven't just moved, they’ve been uprooted. We’re past the point of talking about "faster chips." Everything points to a total shift in the industry's DNA.

This blog is based on the webinar, “AI panel: The next wave of AI technology”. You can watch the full recording by clicking here! The pace of AI innovation is reshaping research, business, and everyday life. However, as breakthroughs in Large Language Models (LLMs) and high-performance computing accelerate, they bring new technical challenges around scale, efficiency, and reliability.