Multi-cloud orchestration for AI workloads: tools, patterns, and a unified control plane

Multi-cloud orchestration for AI workloads involves the coordination of various AI operations, such as training, inference, and deployment, across multiple cloud providers like AWS, GCP, Azure, and others, ensuring consistent governance and operational standards. The complexity arises from each cloud's distinct identity and access management (IAM), networking, and deployment models, making it difficult to maintain uniform governance and secrets management without a unified control plane. Northflank offers a solution with a control plane that deploys into existing cloud accounts, providing consistent governance, role-based access control (RBAC), secrets management, and audit logging across all environments. This approach supports GPU workloads, microVM sandbox isolation, and seamless CI/CD pipelines, ensuring a consistent developer experience. Multi-cloud environments often emerge organically due to variations in GPU availability, compliance requirements, and team preferences, rather than through strategic planning. Northflank's platform aims to simplify the management of these environments, emphasizing a developer-friendly experience to prevent teams from bypassing governance controls.

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