OpenNebula-Waldur Integration: A New Self-Service Paradigm for Federated AI Infrastructure

随着欧洲对主权云、高性能计算（HPC）和AI工厂的投资持续增长，基础设施管理平台的可互操作性和自助服务能力成为关键需求。近日，OpenNebula Systems与OpenNode宣布完成OpenNebula与Waldur的技术集成，为联邦化AI基础设施提供了一站式管理方案。

事件背景

OpenNebula是欧洲被广泛采用的AI基础设施管理平台，专注于私有云和边缘环境下的AI工作负载编排。Waldur则由OpenNode及其合作伙伴开发，是一个开源的云和HPC管理平台，已作为EuroHPC联合平台的核心技术之一，连接欧洲多个超算设施和新兴AI工厂。此次集成将OpenNebula的资源管理能力与Waldur的自助服务门户和联邦功能结合，使用户能够通过统一的Waldur Marketplace在多个OpenNebula实例中自助配置和管理AI训练与推理工作负载。

技术解析

该集成的核心在于两层：底层由OpenNebula负责各站点的虚拟化、GPU调度和存储管理；上层由Waldur提供统一的服务目录、用户管理、计费（可选）和跨站点编排。用户无需了解每个数据中心的底层细节，即可像使用公共云一样从目录中选择虚拟机镜像或AI模型模板，一键部署到指定的联邦站点。这种架构本质上是为“AI工厂”和“Gigafactory”（大规模AI计算中心）设计的云管理平台，支持多站点资源池化、自动化生命周期管理和联邦身份认证。

• 关键技术特性：
• 多站点统一管理：Waldur可连接多个OpenNebula实例，实现跨数据中心资源集中可见。
• 自助服务：用户通过Web门户请求资源，无需IT管理员手动操作。
• AI工作负载原生支持：可直接部署AI框架（如PyTorch、TensorFlow）预配置镜像，并利用GPU分区功能。
• 数字主权：所有组件均为开源，数据和工作负载留在欧洲境内，避免非欧洲供应商锁定。

企业影响分析

• 对于HPC中心、AI工厂、电信运营商和中大型企业，该方案带来直接收益：### Cost Impact
• Reduced operational expenses: Managing multiple sites through a unified platform lowers the learning and maintenance costs of multiple management tools.
• Improved resource utilization: Federated scheduling automatically assigns tasks to resource-rich sites, avoiding local resource waste.
• Avoidance of vendor lock-in: Based on open-source technology, enterprises can independently extend or replace components, resulting in lower total cost of ownership over the long term.

Operational and Deployment Impact - Simplified multi-site operations: IT teams monitor all sites through a single pane of glass, making failover and resource migration more efficient. - Accelerated AI application deployment: Researchers and engineers can quickly obtain development environments through a self-service portal, reducing wait times. - Compliance advantages: Data remains within the EU, meeting GDPR and sovereign cloud regulatory requirements.

Potential Challenges - Requires operational capabilities for open-source platforms; small and medium-sized enterprises may need to rely on professional service providers. - Integration with existing CI/CD or MLOps toolchains requires additional effort.This integration reflects three major trends in the AI infrastructure landscape: 1. From Silos to Federations: AI computing resources are moving from standalone clusters to cross-regional interconnection, making federated management platforms a necessity. 2. Self-Service as the Norm: Whether in public or private clouds, users expect to use internal AI computing power as easily as they use AWS. 3. Digital Sovereignty Driving Innovation: Europe, through open-source, interoperable, and federated technologies, aims to build a complete ecosystem in the AI era that does not rely on non-European vendors.

In the future, the AI Gigafactory concept will drive even larger-scale aggregation of computing power, but management complexity will rise exponentially. Open, composable architectures like OpenNebula + Waldur may become the de facto standard for sovereign AI infrastructure.