What is scale-out?

In AI infrastructure, scale-out means expanding cluster capacity by adding more network-connected servers, racks or nodes, typically within a data center or campus.

Unlike scale-up, which expands a tightly coupled system, scale-out grows the distributed compute cluster through additional networked elements.

Why is scale-out important?

As AI models and datasets grow, organizations need larger compute clusters. Scale-out architecture provides a practical way to add capacity while maintaining flexibility.

As node counts increase, network bandwidth, latency and congestion become increasingly important to overall cluster performance.

Key considerations

• Network scalability
• Consistent performance across large clusters
• Traffic engineering and congestion management
• Low-latency communication between nodes
• End-to-end network validation and visibility

Learn more

Learn how EXFO helps validate fiber and high-speed connectivity in AI-driven data centers.