The First Ukrainian AI/ML platform –
Everything MLOps needs

ML Cloud is an out-of-the-box, user-friendly and functional ML engineer's workspace, deployed in an accelerated (NVIDIA GPU) AI/ML collective (Tensor Cloud) or private (HTI) cloud.

ML Cloud combines an integrated, pre-configured and self-contained collection of "best of breed" open source software for ML/AI tasks and the world's most powerful NVIDIA H100 / L40s / L4 accelerators.

The ready-to-use ML engineer workspace is a significant lowering of the entry barrier to the world of AI/ML. And the latest NVIDIA tensor accelerators provide unattainable performance for other technologies on the tasks of machine learning and productive inference.

The First Ukrainian AI/ML platform – <br/>Everything MLOps needs

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A cloud-ready platform for AI/ML

A high-performance tensor computing platform for AI/ML based on a private or collective cloud.

State-of-the-art NVIDIA H100 / L40S accelerators combined with an integrated VMware vSphere virtualization stack, VMware Tanzu Kubernetes Grid and NVIDIA AI Enterprise.

An integrated set of "best of breed" open source software as an ML engineer's working environment. De Novo ML Cloud is 2 times cheaper than the prices of hyperscalers and provides 100% predictability of costs.

De Novo ML Cloud is up to 2 times cheaper than the prices of hyperscalers and provides 100% predictability of costs.

What does ML Cloud include?

ML Cloud provides an opportunity

Manage the Machine Learning Lifecycle in Kubeflow

including model development (Kubeflow Notebooks), model training (Kubeflow Pipelines), model usage (KServe). Jupyter Notebook (the main tool in the data science engineer's work) can be created and configured in Kubeflow. Jupyter Notebook can be run with or without GPU access.

Use MLFlow to work with machine learning artifacts:

any files and statistics generated during training, for example: loss function plots, metric logs, sample test images, model checkpoints, optimizer checkpoints, model weights.

Download and save data with MinIO.

It is an open source tool that provides an S3-like interface for working with data.

Work with data markup for computer vision tasks in CVAT,

which integrates with MinIO in order to read datasets (videos, images) uploaded to MinIO. Markup can also be stored next to the dataset on MinIO.

Deploy solutions to markup other data types on demand,

such as a textual data markup tool.

Monitor system status with Grafana.

By default, the user gets access to a set of dashboards. In this way, you can learn about the operation of the entire cluster, the load, available and occupied resources, and much more.

ML Cloud Prices

Prices are for using ML Cloud with NVIDIA GPU-accelerated instances.

Using GPU virtualization technology from VMware and NVIDIA, you can order the H100/L40s/L4 in parts (1/8, 1/4, 1/2, or the whole) to meet your workload needs.

The hourly price is approximate based on 730 hours per month and the exchange rate of 1$ = 41 UAH. Prices are exclusive of VAT.

Payment is made in UAH per month at constant prices without reference to foreign exchange rates.

Card	vGPU	GPU GDDR RAM, GB	vCPU	vRAM, GB	Price GPU + instance, USD/hr	Price GPU + instance, UAH/month
NVIDIA H100	1/8	10	2	24	0,81	24 160
	1/4	20	4	48	1,61	48 320
	1/2	40	8	96	3,23	96 640
	1	80	16	192	6,46	193 280
NVIDIA L40s	1/8	6	2	12	0,32	9 660
	1/4	12	4	24	0,65	19 320
	1/2	24	8	48	1,29	38 640
	1	48	16	96	2,58	77 280
NVIDIA L4	1/4	6	2	12	0,20	6 040
	1/2	12	4	24	0,40	12 080
	1	24	8	48	0,81	24 160

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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.

Products for DevOps and AI/ML

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.

Tensor Cloud with NVIDIA GPUs

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

Hosted Tensor Infrastructure

AI/ML-accelerated Kubernetes with NVIDIA H100 / L40S GPU 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.

The First Ukrainian AI/ML platform – Everything MLOps needs

A cloud-ready platform for AI/ML

What does ML Cloud include?

ML Cloud provides an opportunity

ML Cloud Prices

More about K8s as a Service and AI/ML

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Products for DevOps and AI/ML

The First Ukrainian AI/ML platform –
Everything MLOps needs