Elastic scaling

A feature of Polkadot 2.0 that enables parallel processing of rollup blocks on multiple Polkadot cores.

What is Elastic Scaling?

Elastic scaling is a core upgrade in Polkadot 2.0 that improves how rollups use the network’s shared resources. Instead of being limited to one core per rollup, elastic scaling allows rollups to access multiple cores as needed. This gives them the flexibility to handle increased traffic or larger workloads without sacrificing speed or reliability.

The idea is similar to cloud computing, where systems can use more resources on demand. In Polkadot’s case, those resources are time slots on the Polkadot Chain that allow rollups to produce and verify blocks. Elastic scaling helps the network grow without creating bottlenecks and ensures that applications built on Polkadot remain fast and scalable.

How does elastic scaling work?

In Polkadot 2.0, cores are the fundamental units of execution that rollups use to finalize blocks. With elastic scaling, the system introduces a scheduler that dynamically assigns available cores to rollups based on demand. This parallel execution model means that multiple rollups can share cores or use more than one at a time, depending on their activity level.

Cores are no longer tied to specific rollups. Instead, they are treated as a shared pool. The scheduler allocates them based on availability and usage patterns, allowing the network to adapt fluidly to changing conditions. This makes Polkadot more efficient and able to support a wider range of use cases.

What is the benefit of elastic scaling?

• Improved flexibility: Rollups can access multiple execution cores based on demand, rather than being limited to one.
• Greater efficiency: Applications can process more transactions in parallel, enhancing throughput.
• Reduced wait times: Dynamic resource allocation helps minimize congestion during high-traffic periods.
• Simplified chain launches: Developers don’t need to worry about pre-allocating fixed resources.
• Real-time scaling: Resources adjust automatically to usage, supporting growth seamlessly.
• No compromise on performance: Speed and responsiveness are maintained even as demand increases.