Documentation – OpenMetal Cloud

Tired of slow model training and unpredictable cloud costs? Learn how to build a powerful, cost-effective MLOps platform from scratch with OpenMetal’s hosted private and bare metal cloud solutions. This comprehensive guide provides the blueprint for taking control of your entire machine learning lifecycle.

Learn how media companies can deploy OpenAI Whisper on a private GPU cloud for large-scale, real-time transcription, automated multilingual subtitling, and searchable archives. Ensure full data sovereignty, predictable costs, and enterprise-grade security for all your content workflows.

Learn how to improve confidential computing performance using Intel TDX, bare metal, and GPU passthrough without sacrificing security.

If you’re looking to simplify your multi-cloud strategy, combining Kubernetes with OpenStack is a powerful approach. OpenStack provides the core infrastructure-as-a-service (IaaS), and Kubernetes orchestrates your containerized applications on top of it, giving you a consistent platform everywhere. This guide gives you a straightforward look at how to plan, build, and manage a multi-cloud network using these two technologies.

Discover how IT teams can deploy BioGPT on OpenMetal’s dedicated NVIDIA GPU servers within a private OpenStack cloud. Learn strategic best practices for compliance-ready setups (HIPAA, GDPR), high-performance inference, cost transparency, and in-house model fine-tuning for biomedical research.

Discover an in-depth comparison of Apache CloudStack vs. OpenStack for migrating from VMware. Technical buyers will learn about architectural differences, VMware integration strategies, migration utilities (virt-v2v, MigrateKit, Coriolis), and how OpenMetal’s managed private cloud on OpenStack can accelerate your transition with predictable pricing and SLA-backed support.

Explore how MicroVMs deliver fast, secure, and resource-efficient horizontal scaling for modern workloads like serverless platforms, high-concurrency APIs, and AI inference. Discover how OpenMetal’s high-performance private cloud and bare metal infrastructure supports scalable MicroVM deployments.

Frustrated by a Cinder volume that won’t attach? We’ve got you. This guide breaks down the common causes like incorrect volume states, backend config errors, and network glitches. Learn to troubleshoot and fix these attachment failures with practical CLI commands and preventative tips.

Struggling with an outdated, expensive legacy data warehouse like Oracle, SQL Server, or Teradata? This article offers Data Architects, CIOs, and DBAs a practical, phased roadmap to modernize by migrating to open source solutions on OpenMetal. Discover how to achieve superior performance, significant cost savings, elastic scalability, and freedom from vendor lock-in.

Explore CephFS metadata management in depth. This guide explains how CephFS separates metadata, uses Metadata Servers (MDS) with active-active setups, journaling, and caching for fast, scalable, and reliable POSIX-compliant storage. Understand its benefits for private clouds, HPC, and more.

Mistral is OpenStack’s workflow automation service that simplifies cloud operations by turning manual tasks into automated workflows. Learn about how it works and how you can get started using it to help boost efficiency and resource management in cloud environments.

Learn how to configure external networks in OpenStack Neutron. This guide walks through creating networks, subnets, routers, and floating IPs. Learn to secure connections, ensure high availability, and tune performance for reliable public access to your cloud.

Learn how to deploy confidential computing workloads on bare metal using Intel TDX, OpenMetal servers, and secure infrastructure best practices.

Learn how to enable Intel SGX and TDX on OpenMetal’s Medium, Large, XL, and XXL v4 servers. This guide covers required memory configurations (8 DIMMs per CPU and 1TB RAM), hardware prerequisites, and a detailed cost comparison for provisioning SGX/TDX-ready infrastructure.

Dynamic Workload Consolidation is a proven strategy for reducing energy consumption and operational costs in private cloud environments. By intelligently managing your resources, you improve server utilization, cut down on wasted power, and contribute to a more sustainable IT operation.

We’re diving into OpenStack Monasca and Datadog, comparing them as monitoring tools for private cloud environments. Picking one comes down to your organization’s way of working, your team’s skills, and your overall cloud strategy. We’ll get into how they work, benefits and challenges, their ideal use cases, and when you may want to use them together.

OpenStack-based hosted private clouds offer MSPs an exceptional opportunity to provide their clients with a high-performance, secure, and cost-effective cloud solution. By leveraging the flexibility of OpenStack, MSPs can fine-tune performance, reduce costs, and deliver customized solutions that align with client needs.

Choosing to build on open foundations is a strategic investment in flexibility, control, and future innovation. By tapping into the power of the open source ecosystem, organizations can build data lakes and lakehouses that are powerful and cost-effective today, and also ready to adapt to the data challenges and opportunities of tomorrow.

A quick list of some of the most popular Hugging Face models / domain types that could benefit from being hosted on private AI infrastructure.

Discover how cloud resellers can offer scalable on-demand GPU services for AI/ML by leveraging OpenMetal’s Private GPU Servers. Learn about GPU time-slicing, MIG, virtualization strategies, and industry trends driving growth—plus key business benefits and real-world use cases.

Explore asynchronous replication in OpenStack clouds for improved application performance, cost savings, and flexible disaster recovery. Learn its benefits, common use cases with Cinder and Swift, conceptual setup, and key considerations like managing RPO and resource usage for a resilient deployment.

Explore how OpenMetal’s transparent private cloud pricing model helps organizations eliminate surprise bills, cut data egress costs, and avoid licensing fees. With average real-world savings of over 50%, fixed monthly pricing, and open-source foundations, it’s a smarter alternative to public cloud.

Thinking about segmenting your private cloud network? This guide explains how it makes things safer and faster. We cover the pros, the challenges (like complexity and cost), plus useful techniques like VLANs and bonding. Get helpful tips so you can plan and manage it successfully.

Learn to deploy Ceph RGW in OpenStack for scalable S3 and Swift-compatible object storage. Covers installation, configuration, quotas, Keystone integration, integrating Glance images and Cinder backups, performance monitoring and tuning, advanced multi-site replication, lifecycle rules, encryption, and tagging.

Discover how OpenMetal delivers performance and flexibility through tiered cloud storage options. Learn the pros and use cases of direct-attached NVMe, Ceph-based high availability block storage, and scalable, low-cost erasure-coded object storage—all integrated into OpenStack.

Discover the power of the OpenMetal Large v4 Storage Server with dual Intel Xeon Silver 4510 CPUs, 720TB HDD storage, 76.8TB NVMe flash, and 512GB DDR5 RAM. Perfect for building high-performance, scalable, and resilient storage clusters for cloud, AI/ML, and enterprise data lakes.

A practical guide into OpenStack multi-tenant environments. Understand the underlying architecture, component interactions (Keystone, Nova, Neutron), configuration steps for secure tenant isolation, resource quota management, and more advanced tips for security and performance tuning.

Many AI startups default to public cloud and face soaring costs, performance issues, and compliance risks. This article explores how private AI infrastructure delivers predictable pricing, dedicated resources, and better business outcomes—setting you up for success.

A crypto trading firm deployed blockchain infrastructure on bare metal to run Solana validator workloads with low latency and full control.

Nova logs are key for OpenStack troubleshooting and health. Understand common API, compute, network, and login errors. Learn to read logs (timestamps, severity, modules) and use tools like ELK/Monasca. Implement good log management for faster issue resolution and a stable environment.

A Web3 team deployed blockchain infrastructure on bare metal and Ceph storage to scale decentralized workloads and cut storage costs.

In a recent live webinar, OpenMetal’s Todd Robinson sat down with Emrul Islam from Kasm Technologies to explore how container-based Virtual Desktop Infrastructure (VDI) and infrastructure flexibility can empower teams tackling everything from machine learning research to high-security operations.

We’re thrilled to announce a significant step in our global journey: OpenMetal is officially launching a brand new data center location in Singapore!

Learn about major 2025 SOC 2 compliance trends like AI monitoring, zero-trust, DevSecOps, and threat response. Find out how to stay compliant and secure both this year and in the future.

With the new OpenMetal Private AI Labs program, you can access private GPU servers and clusters tailored for your AI projects. By joining, you’ll receive up to $50,000 in usage credits to test, build, and scale your AI workloads.

As blockchain technology moves beyond cryptocurrency, more companies are running blockchain workloads on bare metal to meet growing demands for speed, security, and control. This post explores how it works, why it matters, and where it’s already being used in real-world industries.

Ceph is a distributed storage system designed for scalability, high availability, and data durability. It manages data across clusters using robust replication strategies and a well-defined consistency model. This article talks about Ceph’s replication strategies, write processes, consistency guarantees, and failure recovery mechanisms.

GPU Servers and Clusters are now available on OpenMetal—giving you dedicated access to enterprise-grade NVIDIA A100 and H100 GPUs on fully private, high-performance infrastructure.

Cold start latency becomes a visible and impactful factor in private environments and can slow down AI inference, especially when infrastructure is deployed on-demand to optimize resource usage or reduce costs. Learn causes, impacts, and how to reduce delay for faster, reliable performance.

Discover how machine learning and data analytics teams could accelerate training, inference, and data pipelines using OpenMetal’s infrastructure. This example setup combines a Large v3 Cloud Core with high-capacity Storage v3 servers, NVMe speed, and 95th percentile egress pricing.

The OpenMetal Large v1 Storage Server features dual Intel® Xeon® Silver 4210R CPUs, 12x 12TB HDDs, and 4x 1.92TB NVMe SSDs—ideal for scalable, high-capacity storage and Ceph-based clusters.

Automating backups in OpenStack is crucial for managing large-scale deployments efficiently while reducing risks of human error. Here are the 8 top tools that help streamline OpenStack backup processes for consistent data protection and quick recovery.

Intel Advanced Matrix Extensions (AMX) is an instruction set designed to improve AI inference performance on CPUs. It enhances the execution of matrix multiplication operations—a core component of many deep learning workloads—directly on Intel Xeon processors. AMX is part of Intel’s broader move to make CPUs more viable for AI inference by introducing architectural accelerations that can significantly improve throughput without relying on GPUs.

Struggling with OpenStack Neutron networking issues? This guide gives you practical steps to identify and resolve common problems like connectivity failures, VLAN misconfigurations, DNS/DHCP issues, and more.

Modern GPU technologies offer multiple methods for sharing hardware resources across workloads. Two widely used approaches are Multi-Instance GPU (MIG) and time-slicing. Both methods aim to improve utilization and reduce costs, but they differ significantly in implementation, performance, and isolation.

When comparing GPU costs between providers, the price of the GPU alone does not reflect the total cost or value of the service. The architecture of the deployment, access levels, support for GPU features, and billing models significantly affect long-term expenses and usability.

As demand for AI and machine learning infrastructure accelerates, hardware decisions increasingly affect both model performance and operational costs. The NVIDIA A100 and H100 are two of the most widely adopted GPUs for large-scale AI workloads. While both support advanced features like Multi-Instance GPU (MIG), they differ significantly in performance, architecture, and use case suitability.

The demand for GPU compute resources has expanded alongside the growth of AI and machine learning workloads. Users today have multiple pathways to access these resources depending on their requirements for cost, control, and performance. This article breaks down three common tiers of AI compute services, their advantages, and trade-offs.

Explore real-world solutions to AI deployment challenges—from managing secure, container-based environments to scaling GPU infrastructure efficiently. Learn how Kasm Workspaces and OpenMetal enable secure collaboration, cost control, and streamlined experimentation for AI teams.

Discover the OpenMetal Large v3 Storage Server, featuring 12x18TB HDDs, customizable NVMe flash options up to 15.36TB per drive, and the Intel Xeon Silver 4314 processor. Ideal for Ceph-based clusters, it delivers scalable performance, hot-swappable flexibility, and enterprise-grade storage.