Documentation – OpenMetal Cloud

The four distinct Intel Xeon generations running across OpenMetal’s bare metal and hosted private cloud lineup, what actually changes between them beyond core count, and which generation fits which kind of workload, including where confidential computing eligibility depends on generation and hardware configuration together.

We look at why shared, allocation-based HPC access becomes a real operational problem for life sciences computational research, what changes on dedicated infrastructure that you administer yourself, and how to structure a transition that scales up gradually rather than requiring a large upfront commitment.

We break down how AWS’s Enterprise Discount Program, Azure’s Enterprise Agreements, and GCP’s Workload Agreements actually work, why the discount comes attached to a real financial commitment rather than just usage-based savings, and what that commitment structure costs an enterprise that outgrows or under-uses it.

We walk through a real worked example for sizing a private cloud cluster before committing to a contract, covering how to translate your VM count into node count, why redundancy and replication overhead eat into your raw numbers, and where network bandwidth becomes the limiting factor as a cluster grows.

We break down what Terraform and Ansible each actually do differently, why the overlap between them confuses newcomers, and a practical framework for deciding which one to reach for, or whether you need both, when automating a private cloud deployment.

We look at the real case for using S3-compatible object storage as a default backend, where that approach genuinely breaks down on latency, how serious platforms solve it with a caching layer rather than abandoning object storage entirely, and how to make the same call on a Ceph-based cluster.

We look at the real timing constraint behind real-time bidding auctions, why shared cloud infrastructure quietly eats into that budget through virtualization and cross-zone network hops, and where dedicated bare metal removes that variance directly.

NVIDIA AI Enterprise (NVAIE) is a support and integration product, and knowing that up front settles most of the buying decision. It does not unlock faster GPUs or a private

An account-intelligence system that pre-embeds ten million companies into a resident vector index, and one that dispatches agents to research those same companies live on demand, look like the same

We look at why a company’s production data residency doesn’t automatically cover its CI/CD pipeline, what GitHub Actions actually offers EU-based teams today, and how self-hosting runners on Amsterdam hardware closes that gap directly.

We look at why attack surface management and cyber-risk scanning companies, businesses that scan large swaths of the public internet as their core product, run into trouble on hyperscaler infrastructure, what actually needs to be true about a provider’s acceptable use policy and IP allocation to support this workload, and how that differs from running an internal penetration testing lab.

On latency-bound inference, the Model FLOPs Utilization your optimization stack can actually hold is capped by who else shares the box, not by the kernel that runs on it. Sustained

Runway Intelligence is OpenMetal’s executive insight series for late-stage startups and their investors, exploring how cloud economics, infrastructure design, and operational strategy shape valuation, margins, and time to exit.  A

We walk through the real total cost of building your own dense storage server for off-site backup and archival data versus renting equivalent capacity, covering drive costs in today’s market, the parts of total cost of ownership that don’t show up on a parts list, and how Ceph’s approach to redundancy compares to a single chassis.

We work through the actual cost crossover between GitHub-hosted Actions runners and self-hosted runners on dedicated bare metal, using GitHub’s current 2026 rates, correct a common misconception about a self-hosted runner fee that never took effect, and cover what a self-hosted build pipeline needs beyond just cheaper compute.

We compare three dedicated server providers commonly considered for Proxmox VE hosting, OpenMetal, Hetzner, and OVHcloud, across real hardware specs, current pricing, storage architecture, and support model, so you can match the provider to your actual workload rather than just the sticker price.

We break down what the EU Cyber Resilience Act’s vulnerability reporting obligations actually require starting September 2026, why the tight reporting clock is fundamentally an infrastructure visibility problem, and where dedicated infrastructure and controlled build pipelines make that clock achievable.

Intel TDX confidential VMs run on OpenMetal dedicated bare metal hardware today, available on on XL v5, with OpenStack Nova orchestration slated for after Hibiscus.

We look at why post-quantum cryptography has moved from a research topic to a binding compliance deadline, why “harvest now, decrypt later” makes this an infrastructure problem today rather than a future one, and why crypto-agile key management needs hardware you control directly.

We look at what the GENIUS Act actually requires of payment stablecoin issuers, why reserve tracking, redemption, and transaction monitoring systems need dedicated and auditable infrastructure rather than shared platforms, and where that requirement does and doesn’t touch broader blockchain infrastructure.

A first-party FP4 checkpoint moves GPU selection from memory capacity to native tensor-core format support, and inverts the usual verdict. Based on the Inkling-Small.

On OpenMetal v5, one memory decision buys Intel TDX eligibility, full DDR5-6400 bandwidth, and SGX enclave headroom. XL v5 ships ready.

Claude is closed-weight and cannot run on your own hardware, but you can self-host the entire application and data plane around it on OpenMetal. Here is how.

Gemini is closed and cannot run on your own hardware, but you can self-host the entire application and data plane around it on OpenMetal. Here is how.

GPT is closed-weight and cannot run on your own hardware, but you can self-host the entire application and data plane around it on OpenMetal. Here is how.

Claude, GPT, and Gemini cannot run on hardware you own, but you can self-host the entire stack around them on OpenMetal. Here is what is actually possible.

We look at why financial services firms accumulate large, long-lived data retention and audit archive requirements, why hyperscaler storage pricing works against that access pattern specifically, and how a large-scale Ceph cluster handles the same requirement with predictable costs and full control.

We answer a specific legal question that general Singapore sovereignty content doesn’t: whether US CLOUD Act jurisdiction reaches infrastructure physically hosted in Singapore, how that’s separate from Singapore’s own PDPA framework, and what that means if you’re evaluating a US-owned infrastructure provider for APAC deployment.

We explain why AI agents that execute code need microVM-level isolation, why that isolation requires direct hardware access that public cloud VMs can’t provide, and how self-hosting a Firecracker or Kata sandbox on dedicated bare metal compares to managed platforms like E2B on cost and control.

We explain what Intel TDX confidential computing actually protects, confirm which hardware configuration delivers it in our Amsterdam data center today, and walk through why pairing TDX with EU data residency matters for regulated workloads.

Coding-agent fleets hit dedicated-GPU break-even at ~5-10M tokens/month or 15-25% utilization. Why metered per-token billing punishes the agent workload.

We compare Amsterdam against Frankfurt, Dublin, and Paris as EU infrastructure locations, covering network connectivity, latency to key regions, and data residency considerations, then explain why Amsterdam is where OpenMetal actually operates.

Neocloud became a capital-and-power race, leaving sustained mid-market inference underserved. Why predictable cost, not GPU count, is the defensible position.

We break down the real difference between data residency and data sovereignty, why many “sovereign cloud” claims from US-owned providers don’t hold up under scrutiny, and what EU-based infrastructure can and can’t actually guarantee.

We look at why Azure’s egress fees are no longer the sharpest lock-in mechanism, and walk through the specific managed services (Azure Functions, Cosmos DB, Service Bus, Logic Apps, Azure AD B2C / Entra External ID) that actually make leaving Azure hard, including the one place Azure is more open than either AWS or GCP, and the one place it’s arguably worse.

Prefill is compute-bound, decode is memory-bandwidth-bound. Why splitting inference into two purpose-fit GPU pools beats one uniform fleet.

After weights load, the HBM left over is your KV-cache budget. Why the H200’s 141GB buys more context and concurrency than a 94GB H100.

Map MongoDB, Redis, Kafka, ClickHouse, and Kubernetes workers to OpenMetal SKUs by the resource each role saturates, then size the failure domain.

Check out what’s new with OpenMetal Central and our cloud management and control capabilities in July 2026.

We look at why Google Cloud’s egress fees are no longer the sharpest lock-in mechanism, and walk through the specific managed services (Cloud Functions, Firestore, Cloud Spanner, Pub/Sub, Cloud Workflows, Identity Platform) that actually make leaving Google Cloud hard, including where GCP’s lock-in profile is genuinely different from AWS’s.

We look at why AWS egress fees are no longer the lock-in mechanism people think they are, and walk through the specific managed services (Lambda, DynamoDB, Step Functions, EventBridge, SQS/SNS, Cognito, API Gateway) that actually make leaving AWS hard.

Yes, Llama 3.3 70B runs on a single OpenMetal H200 at FP8 with full 128K context. See the VRAM fit math, KV-cache budget, and vLLM setup.

An ordered Day-2 playbook for a single-tenant H200: full root and IPMI, owning the CUDA stack, boot-data isolation, and a node-bounded blast radius.

The operator trust problem in MEV block building has a hardware solution. This article explains why Intel TDX has become the substrate of choice for confidential block building, and what bare metal adds that cloud TDX doesn’t.

Planning a private cloud project? Organizing well from the start can prevent expensive and time-consuming delays. Our guide explains why hosted private cloud projects stall across migration and day two operations and shows how to prevent delays with better planning, architecture, ownership, and operational readiness.

OpenMetal XL v5 keeps 64 cores but changes node, memory, I/O, power, AMX, and TDX readiness. Where v5 wins, and the one spec that regresses.

OpenMetal XL v5 vs XL v4: same 64 cores, but v5 adds 33% memory bandwidth, more PCIe lanes and drive bays, and CPU-side AI; v4 keeps more L3 cache.

A skimmable breakdown of the main business and technical drivers pushing companies from public cloud to hosted private cloud, covering cost control, compliance, performance, and operational control.

Healthcare AI workloads carry the same HIPAA obligations as any system touching PHI. This article covers what the 2026 Security Rule update requires from AI infrastructure, why vector embeddings count as PHI, and how dedicated private cloud simplifies the compliance documentation burden.

Hyperscaler credits are worth taking, but the architecture built during the subsidized period determines your real cost when billing starts. This covers the credit lifecycle, which decisions create long-term cost exposure, and when private infrastructure makes sense for AI startups in production.