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What is NVIDIA DOCA?

NVIDIA DOCA is a robust platform designed to maximize the capabilities of NVIDIA BlueField DPUs and NVIDIA ConnectX SuperNICs, particularly for agentic AI environments. It presents a comprehensive collection of SDKs, libraries, production-ready microservices, drivers, management utilities, and orchestration frameworks that streamline the development and oversight of accelerated infrastructure services, which include networking, AI-focused storage, cybersecurity, observability, and lifecycle management. By leveraging DOCA, developers can effectively offload, accelerate, and isolate infrastructure tasks, allowing host computing resources to be freed up for a variety of AI services and applications. The networking features encompass virtual switching, packet processing, multi-tenant isolation, sophisticated traffic management, RDMA acceleration, and software-defined networking functionalities. In the realm of storage, DOCA is equipped to handle KV cache infrastructure, NVMe over Fabrics, storage virtualization, and software-defined storage services, promoting a seamless integration of various storage solutions. Furthermore, the utilization of DOCA not only boosts operational efficiency but also enhances the flexibility required for managing sophisticated infrastructure. This adaptability is crucial as organizations increasingly rely on advanced technology to meet their dynamic operational demands.

What is MayaScale?

Develop a comprehensive NVMe over Fabrics shared storage solution using MayaScale that facilitates the incorporation of directly attached NVMe resources into a cohesive storage pool. This system allows for dynamic allocation of NVMe namespaces to clients seeking superior performance with low latency. After their requirements are met, clients can easily return NVMe storage to the collective pool, effectively addressing the common challenges of over-provisioning and wasted NVMe resources often seen in direct-attached architectures. The architecture is network-agnostic, utilizing RDMA for on-premises setups and standard TCP for cloud-based environments, which enhances its adaptability. Clients are able to connect to genuine NVMe devices through a standard NVMe driver stack, eliminating the necessity for proprietary drivers. Configuring and deploying an NVMe over Fabrics SAN infrastructure at rack scale in a data center can be accomplished by integrating various NVMe devices through RDMA-compatible links, such as ROCE, iWARP, or Infiniband. Moreover, in public cloud scenarios, users can take advantage of NVMe over Fabrics via the conventional TCP/IP protocol, removing the need for specific RDMA hardware or SRIOV virtualization. This forward-thinking approach not only maximizes resource efficiency but also ensures consistent high performance across different deployment landscapes, making it a versatile choice for modern storage solutions. Ultimately, this innovative design paves the way for improved scalability and flexibility in data management strategies.

Media

Media

Integrations Supported

NVIDIA Open Agent Safety Platform

Integrations Supported

AWS Marketplace
Amazon
Amazon RDS
Google Cloud Platform
Microsoft Azure
MongoDB
MySQL Workbench
Oracle Cloud Infrastructure FastConnect
Red Hat CloudForms

API Availability

Has API

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS
On-Prem

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Webinars

Training Options

Documentation Hub
Webinars
On-Site Training

Company Facts

Organization Name

NVIDIA

Date Founded

1993

Company Location

United States

Company Website

www.nvidia.com/en-us/networking/products/software/doca/

Company Facts

Organization Name

ZettaLane Systems

Date Founded

2018

Company Website

www.zettalane.com/maya-nvmeof-linux-rdma-tcp.html

Categories and Features

Agentic AI

Not specified

Categories and Features

Block Storage

Not specified

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