Hosted Tensor Infrastructure for AI/ML with NVIDIA GPU

Hosted Tensor Infrastructure (HTI) - Kubernetes accelerated for AI/ML with NVIDIA GPU tensor cores on private cloud (Hosted Private Infrastructure / HPI).

The platform combines the world's most powerful tensor accelerators NVIDIA H200 NVL, H100, L40S, L4, A100 NVL and an integrated technological stack based on VMware vSphere, VMware Tanzu Kubernetes Grid and NVidia AI Enterprise. Tensor accelerators provide unattainable performance for other technologies on the tasks of machine learning and productive inference.

Meanwhile, private cloud as a service (HPI) provides a physically isolated and secure VMware vSphere virtual infrastructure that is exclusively used by the customer. HTI inherits all the advantages of HPI and flexibly adapts to business requirements, has extended functionality and provides the possibility of deep integration with its own infrastructure, including the possibility of installing the complex on the customer's territory.

Get a powerful and reliable platform for AI/ML that provides 100% cost predictability, combining the benefits of cloud and on-premise infrastructure, cost-effectiveness and significantly reducing time from idea to implementation in the world of AI/ML.

Hosted Tensor Infrastructure for AI/ML with NVIDIA GPU

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Advantages of the HTI cloud platform

Industry-leading NVIDIA H200 NVL, H100, L40S, L4, A100 NVL Tensor Processors

accelerate training of large models and dramatically increase the productivity of ML engineering teams.

GPU virtualization technology from VMware and NVIDIA

allows you to flexibly distribute accelerators (including 1/2, 1/4, 1/8) between different projects and ensure a zero maintenance window for productive inference.

An industrial-class Kubernetes environment with commercial support

based on VMware Tanzu and NVIDIA AI Enterprise allows an MLOps engineer to create working environments for ML engineers without being distracted by purely infrastructure issues.

Full compliance with Ukrainian legislation

If you need a KSZI - you will get a KSZI.

More about K8s as a Service and AI/ML

Watch the video: Kubernetes as a service in De Novo clouds

In the era of container development, our specialists have created several tools for convenient creation and management of container virtualization clusters based on VMware Tanzu Kubernetes Grid in De Novo clouds.

Download the presentation: Kubernetes as a service in De Novo clouds

VMware Tanzu Kubernetes Grid Kubernetes cluster orchestration platform for DevOps and developers in De Novo's private and public cloud.

Watch the video: Cloud for AI/ML with NVIDIA GPU

Learn more about De Novo's high-performance tensor computing platform for AI/ML based on private and public cloud.

Download the presentation: Cloud for AI/ML with NVIDIA GPU

High performance tensor computing platform for AI/ML based on private and collective cloud.

Download the presentation: ML Cloud - a convenient environment for the work of an ML engineer

The presentation provides a detailed description of the technological components of ML Cloud, their advantages and conveniences for the ML engineers.

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Products for DevOps and AI/ML

AI Studio

A ready-made environment where you can create your own applications with generative AI, test them, and safely connect them to business processes. The platform supports a low-code/no-code approach

Tensor Cloud with NVIDIA GPUs

Kubernetes as a Service Accelerated NVIDIA GPU H200 NVL, H100, A100 NVL, L40S, L4 with tensor cores to run artificial intelligence and machine learning (AI/ML) workloads

Hosted Tensor Infrastructure

AI/ML-accelerated Kubernetes with NVIDIA GPU H200 NVL, H100, A100 NVL, L40S, L4 with Tensor Cores on Hosted Private Infrastructure (HPI)

Kubernetes as a Service

A modern platform for orchestrating industrial-grade Kubernetes clusters in the public cloud. The functionality and usability of KaaS is similar to managed Kubernetes services from hyperscalers

Hosted Container Infrastructure

PaaS platform for orchestrating Kubernetes clusters based on VMware Tanzu Kubernetes Grid in a private cloud. The functionality and usability of KaaS is similar to "managed Kubernetes" services from hyperscalers

ML-Cloud is a cloud platform for ML engineers

A ready-made, user-friendly and functional ML engineer's working environment, which is deployed in an accelerated (NVIDIA GPU) for AI/ML tasks in a collective (Tensor Cloud) or private (HTI) cloud