Uvation designs and operates Microsoft Azure environments on top of GPU-dense, AI-optimized infrastructure that spans Azure regions, Uvation AI factories, and modular data centers. This lets you standardize on Azure services while aligning compute growth with realistic power, land, and facility constraints. By integrating Azure with Uvation’s GPU clusters, AI factories, and hybrid connectivity, your teams get a unified control plane for cloud-native apps, AI/ML pipelines, and data-intensive services across the AI infrastructure value chain.
Standardize application deployment on Azure Kubernetes Service (AKS), Azure Virtual Machines, and PaaS services to simplify orchestration, security, and compliance across hybrid environments. Use a common Azure foundation instead of maintaining fragmented stacks in each region or facility.
Package applications once and run them in Azure regions, Uvation AI factories connected through Azure Arc, or edge locations with Azure Stack HCI and Azure Arc-enabled Kubernetes for consistent operations and tooling.
Combine Azure GPU SKUs and autoscaling with Uvation's NVIDIA and AMD GPU infrastructure to dynamically allocate accelerators for AI training, fine-tuning, and inference based on workload requirements. Align GPU placement with power, cooling, and networking constraints in each AI factory or data center.
Integrate Azure Machine Learning, Azure Kubernetes Service, and Azure AI services with Uvation's AI-optimized infrastructure patterns so AI workloads are monitored, optimized, and governed across clouds, factories, and edge sites using your preferred MLOps tooling.
Use Azure autoscale, AKS cluster and node pool scaling, and Spot capacity options to right-size resources and reduce idle capacity across regions. Combine this with Uvation’s modular AI factories to add or remove GPU-dense capacity in line with demand.
Place workloads where they run best, such as Azure regions, Uvation AI factories, modular data centers, or edge sites using Azure policies, Arc, and Kubernetes-native scheduling to balance performance, cost, sovereignty, and data residency.
Leverage Azure enterprise-grade security and compliance capabilities such as Azure Security Center, Defender for Cloud, Key Vault, and managed identities combined with network segmentation, encryption, and RBAC to enforce consistent policies across environments.
Combine Azure with Uvation's sovereign-by-design AI infrastructure patterns, including private connectivity, regional data residency, confidential compute options, and controlled sites for regulated workloads like sovereign AI, defense, and public sector programs.
Azure-aligned deployments on Uvation sites
Run Azure-connected workloads in Uvation AI factories and modular data centers using Azure Arc, Azure Stack HCI, and Azure-compatible reference architectures so on-premises and near-edge capacity operate like an extension of your Azure footprint.
Multi-environment control plane
Centralize policy, configuration, and observability across Azure regions, Uvation AI factories, and edge sites under a single Azure-first control plane, using tools like Azure Monitor, Log Analytics, and Arc to manage resources wherever they live.
Integrated CI/CD and GitOps
Adopt GitOps and enterprise CI/CD with GitHub Actions, Azure DevOps, and Argo CD, connected to Azure Kubernetes Service and Arc-enabled clusters running in Uvation facilities. Standardize pipelines from code to deployment across clouds and AI factories.
High-density GPU clusters for Azure workloads
Deploy Azure-connected workloads onto high-density GPU clusters in Uvation AI factories, engineered for LLM training, fine-tuning, and latency-sensitive inference. Use Azure-native services to orchestrate jobs while Uvation provides the underlying power, cooling, and rack-level design.
Support for NVIDIA and AMD accelerators
Run AI workloads on NVIDIA H100-class and AMD Instinct MI300-class accelerators, and other GPUs validated for Azure and hybrid deployments, tuned for high-bandwidth, low-latency interconnects in Uvation data centers.
MLOps and Azure AI integration
Extend Azure Machine Learning and Azure AI services to manage the lifecycle of predictive and generative models across Uvation’s AI factories, GPU clusters, and Azure regions
Zero-trust security patterns
Apply zero-trust architectures using Azure-native identity and security services plus Uvation’s network segmentation, workload isolation, and hardened sites for sensitive AI deployments. Integrate with your existing identity providers and key management practices for end-to-end control.
Advanced networking and connectivity
Leverage Azure ExpressRoute, private peering, and high-bandwidth interconnects to link Azure regions with Uvation AI factories and data centers, supporting cross-site replication, low-latency training, and distributed inference. Use software-defined networking and traffic engineering to steer AI workloads to the optimal site.
Storage, observability, and logging
Connect Azure storage services and enterprise storage platforms in Uvation facilities, and gain deep observability with Azure Monitor, Log Analytics, and integrated logging and metrics for containers, GPUs, and services.
See how Uvation architects and deploys a production-grade Azure environment on AI-optimized infrastructure, then layers in CI/CD, GitOps, and security policies to create a standardized path from source code to running workloads.
Walk through GPU-aware capacity planning, autoscaling, and hybrid governance across Azure regions, data centers, and AI factories to see how Azure can serve as the control plane for your AI infrastructure footprint.
Day-to-day management of network infrastructure for reliability.
Operational management of on-premise datacenters for availability and efficiency.
