英博云AI算力

Overview

EBCloud AI Computing Power is a GPU intelligent computing cloud platform launched by EB Digital Technology, aimed at universities, enterprises, and research institutions, providing computing services for AI training, development, and deployment. The platform adopts a K8S Native architecture, balancing Kubernetes-native capabilities with the ease of use of a cloud platform, and supports users in building AI development environments, training tasks, and containerized applications with GPU resources at a lower barrier.

Its core features lie in providing a resource control experience close to bare metal, while also using its self-developed DICP (Dynamic Isolation Control Plane) to allocate independent API Server and CRD spaces to users, strengthening security isolation in multi-tenant scenarios. For teams that need multi-machine training, experimental environment setup, teaching and research, and enterprise-grade AI application deployment, this type of platform has strong adaptability.

Main Features

• GPU Container Service

  • Provides fully managed Kubernetes container management capabilities
  • Supports deploying workloads without purchasing nodes yourself
  • Can be used together with capabilities such as parallel file storage and block storage

• Development Machine Environment

  • Provides development machine instances for AI R&D
  • Pre-installs mainstream deep learning frameworks and development toolchains
  • Supports creation and management through the page or K8S commands

• Cluster Management

  • Visual creation and management of Kubernetes clusters
  • Supports connecting to and operating clusters through kubectl
  • Suitable for flexible scheduling of mixed GPU/CPU cluster resources

• High-Performance Storage

  • Supports shared storage and block storage
  • Uses IB networks and the RDMA protocol to connect storage and computing nodes
  • Suitable for high-throughput scenarios such as large model training

• Security Isolation

  • Achieves tenant-level isolation based on DICP technology
  • Provides independent control-plane resource spaces for different users
  • Improves resource and data security

• Multiple Billing Models

  • Supports on-demand, annual and monthly subscription, bidding, reservation, and other models
  • Convenient for flexible selection based on training cycles and budget

Product Pricing

The official website shows that the platform supports methods such as pay-as-you-go and monthly billing, and some zones launch phased pricing promotions based on GPU models. The latest captured information shows:

• 3090 Zone (Southwest Zone 1)
• Limited-time 33% off
• Single card as low as ¥1.11
• Supports flexible billing by usage / monthly subscription

Actual prices will vary depending on GPU model, region, resource specifications, and promotion period. It is recommended to refer to the following official website page:
https://www.ebcloud.com/chn_zu3hgw9a

Frequently Asked Questions

Which users is it suitable for?

It is suitable for university labs, research teams, AI startups, and enterprise users with needs for model training, inference deployment, course teaching, or containerized R&D that require GPU computing power.

Does it support Kubernetes-native usage?

Yes. The platform emphasizes a K8S Native experience and can be managed through the console, or operated together with methods such as kubectl and SSH.

Can it be used for large model training or multi-machine training?

Yes. The platform provides mixed GPU + CPU computing power, parallel storage, and high-speed networking capabilities, making it suitable for multi-GPU collaborative training and large-scale distributed task scenarios.

Does it provide a development environment?

Yes. Users can create development machines and use pre-installed deep learning frameworks and toolchains for model development, debugging, and experimentation.