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Articles from stack8s on sovereign AI, hybrid cloud architecture, and practical GPU economics.

08 Apr 20267 min read

Which GPU for Your LLM Model? A Practical Buying Guide

Picking a GPU for an LLM sounds simple until you hit the real variables. Model size, context length, user count, response speed, and budget all pull in different directions. That's why there isn't one best GPU for every LLM workload. For many teams, VRAM matters more than peak compute, because if the model doesn't fit in memory, nothing else matters. This guide is for technical and budget owners alike. Start with the job you need to run, then work back to the hardware. Start with the workloa

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18 Mar 20265 min read

AI Grid Orchestration for Telcos with stack8s

AI Grid with stack8s - podcast0:00/117.21× Telcos no longer run AI in one neat data centre. They run it across towers, central offices, regional sites, and cloud zones. That spread creates a hard problem: how do you manage all of it as one platform without losing control of latency, cost, GPUs, or data rules? That is where AI Grid Orchestration fits. It places workloads where they make the most sense, then keeps policy, scaling, and recovery aligned across the estate. NVIDIA AI Grid Orchestrat

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12 Mar 20263 min read

Build a System That Lasts..Stop Building AI Agents

I keep seeing founders burn weeks building shiny AI agents, then wonder why nothing sticks. The bottom line is simple: most "agents" don't create durable value, they create moving parts. When the model changes, the tool changes, the prompt breaks, and the whole thing wobbles. I'm not saying automation is bad. I'm saying the lasting part usually isn't an agent at all. It's the plain, boring stuff you can reason about, review, version, and hand over to a team without a long meeting. Why I'm sce

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11 Mar 20266 min read

GPT-OSS-120B inferencing: which GPUs make sense to host it in 2026?

Running GPT-OSS-120B in production sounds like a pure compute problem. In practice, it's a memory problem first, then everything else. DevOps teams want predictable latency and clean scaling. CTOs want a platform choice that won't stall delivery. CFOs want a cost line they can defend. GPT-OSS-120B is a 117B-parameter Mixture-of-Experts model, yet only about 5.1B parameters are active per token. That lowers compute compared with dense 120B models, but it doesn't magically remove VRAM pressure. W

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11 Mar 20268 min read

H100 SXM5 vs H100 PCIe vs H100 NVL: real differences and best use cases

If you're pricing an AI cluster in March 2026, the names can feel like a trap. H100 SXM5, H100 PCIe, and H100 NVL all say "H100", so they must behave the same, right? In practice, the module, power limit, memory bandwidth, and GPU-to-GPU links change what you can build, how fast it trains, and how much the rack costs to run. This guide keeps it practical for DevOps, CTOs, CFOs, cloud users, AI analytics teams, and researchers. You'll see what stays the same (Hopper features), what changes (pack

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10 Mar 20269 min read

OpenClaw in the Enterprise: What's Behind the Stir, and What It's For Beyond a Personal Assistant

New GPUs land every quarter. Another CLI appears. Then someone suggests a new "standard stack", and your team's week disappears into setup work. That's why OpenClaw is getting so much attention in 2026. It isn't another chatbot tab. It's an open-source agent you can run on your own machine or a server, and it can take actions, not just answer questions. In practice, it can read a message in Slack, run an approved command, pull a report from an API, store an artefact, then post the result back w

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02 Mar 20265 min read

Addressing Sovereignty with the stack8s Unified Control Plane

If you can't choose where a workload runs, do you really control it? That's the heart of sovereignty, and it's now a live issue for more than security teams. DevOps leads, CTOs, CFOs, researchers and AI teams all face the same problem. Data, models and apps now sit across public clouds, edge sites and on-prem systems. That brings speed, but it also brings legal exposure, rising spend and weaker control. stack8s Unified Control Plane offers a practical middle path. It gives teams one way to man

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03 Dec 202519 min read

The Sovereign Cloud-Native Blueprint: Architecting a Vendor-Agnostic, Kubernetes-Based AI and Compute Platform

Sovereign Cloud Blueprint Kubernetes and AI0:00/308.361× The Strategic Mandate for Sovereign AI & Compute 1.1 The Decoupling Imperative The global digital economy is increasingly reliant on advanced compute resources, particularly for emerging workloads like Artificial Intelligence (AI). This reliance has driven organizations toward centralized hyperscaler cloud providers, inadvertently creating significant strategic vulnerabilities. The present architectural imperative is defined by the ne

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21 Aug 20253 min read

Bridging HPC and AI/ML: Integrating Slurm with MLOps Platforms

The Convergence Challenge Over the past decade, enterprises have invested heavily in High Performance Computing (HPC) infrastructure to tackle complex scientific problems. These organizations have built sophisticated systems using Slurm to schedule massively parallel jobs across large clusters equipped with accelerated hardware. Now, as AI/ML workloads demand similar computational resources for deep learning model training, enterprises are seeking ways to leverage their existing HPC investments

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