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Gartner defines hybrid AI infrastructure as offerings that address the need to enable AI and machine learning (ML) workloads across enterprise data centers, colocation and the edge, and public cloud. The offerings include a combination of compute, storage and networking components, along with the requisite enablement tooling, middleware and libraries. Infrastructure and operations (I&O) leaders can use these solutions to deploy AI in the most strategic location for their needs, whether on-premises, at the edge or in the cloud.
Low latency and lossless networking with high throughput, including near-range networks for data transfer between AI accelerators and/or CPUs (e.g., NVLink and NVLink Switch)
Data processing and preparation of data for model training and inference
Automated aspects of building, deploying and maintaining AI/ML models
High-throughput, low-latency and high-capacity storage to support the large datasets and high-speed data transfers necessary to keep graphics processing units (GPUs) engaged with large quantities of data
Integration of AI/ML libraries (e.g., PyTorch, Keras, CUDA)
Tools enabling the deployment and operation of AI/ML workloads (e.g., InstructLab)
Security, including encryption, access controls and compliance
High-speed, lossless networks interconnecting AI servers (e.g., InfiniBand, RDMA over Converged Ethernet [RoCE])
Ability to support workloads on-premises, at the edge and within a public cloud hyperscaler
High computational demands
Packaging, deploying and managing the excursion of AI/ML training and model inference, as well as fine-tuning the operation
Red Hat AI is a platform that accelerates AI innovation and reduces the operational cost of developing and delivering AI solutions across hybrid cloud environments. It delivers cost-effective solutions with optimized models and efficient inference, simplifies integration with private data, and accelerates delivery of agentic AI on a scalable, flexible platform.
Red Hat AI allows organizations to manage and monitor the lifecycle of both predictive and gen AI models at scale, from single-server deployments to highly scaled-out distributed platforms. The platform is powered by open source technologies and a partner ecosystem that focuses on performance, stability, and GPU support across various infrastructures.
Dell AI solutions software enables organizations to deploy, manage, and scale artificial intelligence workloads in various environments, including on-premises, cloud, and edge infrastructures. The software supports data preparation, model training, and inference through integrated tools and frameworks that facilitate the development and operationalization of AI models. It provides resources for automating AI lifecycle management, streamlining data processing, and enhancing workflow efficiency. Dell AI solutions software addresses the business problem of integrating AI into existing IT ecosystems to accelerate decision-making, optimize operations, and derive insights from large data sets. The software also supports security and governance requirements to meet enterprise standards in AI deployment.
AI Data Center Networking is a software offered by Juniper Networks designed to manage and optimize data center network infrastructure. The software automates network configuration, monitoring, and troubleshooting processes to support the deployment of artificial intelligence and high-performance computing workloads. It provides features such as advanced network telemetry, visibility into network traffic, and high-throughput connectivity to address the demands of modern data centers. The software enables policy-driven network management, scalability, and rapid provisioning to help organizations handle large-scale workloads and dynamic resource allocation. It aims to solve business challenges related to network complexity, efficiency, and reliability in environments running data-intensive applications.
Hitachi iQ is an AI and machine learning infrastructure solution suite that includes all the components necessary to build a fully functioning AI and machine learning infrastructure including accelerated compute, high-speed networking, scalable high-performance storage, and a full management software stack. Hitachi iQ offers several models with a variety of configurations delivering up to 14 exabytes of capacity and delivering 80+ GBs/sec to each GPU. The Hitachi iQ with NVIDIA DGX BasePOD certified reference architecture and Hitachi iQ with NVIDIA HGX offerings are designed for performance and scale while Hitachi iQ M Series offers modular solutions with a flexible infrastructure that offers a balanced approach to performance and cost. Hitachi iQ provides unified access to data across data centers, remote sites, and public clouds with explainability, lineage, data accuracy, security, and traceability.
Infinia is a software designed to deliver high-performance data storage and management capabilities for organizations handling large-scale workloads. The software provides features such as data tiering, seamless data movement, advanced metadata operations, and support for diverse protocols, enabling efficient data access across high-performance computing and artificial intelligence environments. Infinia addresses challenges related to managing, scaling, and securing vast amounts of unstructured data by offering centralized control, automated data placement, and monitoring tools. The software is built to support multiple storage tiers including flash, disk, and cloud storage, aiming to optimize resource utilization and reduce operational complexity in enterprise data environments.
Mirantis k0rdent AI enables Enterprises and Service Providers to provision multi-tenant AI-ready infrastructure and core services - all within a single integrated offering that reduces time-to-market for new AI-powered products.
Trusted, Composable, Sovereign AI Infrastructure: Complete control over data residency, security & regulatory compliance in on-prem, hybrid, or edge deployments.
Accelerate Time-to-Value: Operationalize GPUs the same day hardware arrives with rapid provisioning using declarative templates.
Multi-Tenancy and Isolation at Scale: Hard multi-tenancy with isolation at GPU, VM, and Kubernetes layers for efficient resource sharing.
Seamless Lifecycle Management: Unified control plane for managing bare metal, virtualization, Kubernetes clusters, and AI services.
Broad Ecosystem: Supports NVIDIA, AMD, Intel GPU technologies, and a curated catalog of AI/ML & observability tools.
Flexible Deployment: From dedicated bare metal to virtualized on-prem to public clouds
Nutanix Cloud Platform (NCP) is a software-defined hybrid cloud platform with centralized management for apps and data anywhere, including edge locations and private data centers to public clouds, while maintaining sovereignty, security, and performance. NCP delivers VM and container-based architectures, an enterprise AI platform, and resilient, automated operations with data simplicity and control, including disaster recovery, networking, and security, Day2 operations.
This service may contain translations provided by Google. Google disclaims all warranties related to the translations, express or implied, including any warranties of accuracy, reliability, and any implied warranties of merchantability, fitness for a particular purpose and noninfringement. Gartner's use of this provider is for operational purposes and does not constitute an endorsement of its products or services.
