Modal Rebuilt Infrastructure for Million-Sandbox Support
The platform now enables 50,000 sandbox creations per second to better serve intensive AI workloads.
Updated on Sept. 23, 2026 in Data Centers
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Modal has redesigned its infrastructure to support 1 million concurrent sandboxes by shifting away from centralized scheduling. This new architecture allows for massive parallelization of AI training and inference tasks.
Why it matters
Traditional container platforms often struggle with scaling because they rely on centralized coordination and strongly consistent state. By distributing scheduling, Modal avoids the linear growth limits that typically constrain Kubernetes-based algorithms.
The system achieves a median startup-to-code time of under 0.5 seconds. Testing confirms the Redis-based worker state stream remains viable for a fleet of over 100,000 worker nodes.
The players
Modal
Modal is a technology company that develops cloud infrastructure platforms specifically designed for AI workloads like model training and inference.
The details
The platform replaces a single scheduler with a parallel fleet where each worker node maintains its own local resource availability as the source of truth. Workers interact with scheduling servers using remote procedure calls, ensuring the system can handle tens of thousands of creations per second.
Timeline
September 23, 2026: The infrastructure update was formally announced.
The Tech Race
Modal's departure from centralized scheduling architectures highlights a growing industry trend toward de-bottlenecking compute orchestration. This move marks a departure from traditional Kubernetes scheduling algorithms that struggle to keep pace with modern AI demand.
Developers using the platform will see significantly faster startup times for AI inference and training tasks due to the reduced latency in sandbox creation. These improvements allow for more complex workloads to be executed concurrently without traditional resource queuing delays.
The takeaway
Scaling massive AI infrastructure requires moving away from the bottleneck of centralized state management. Developers should prioritize distributed architectures when designing systems that need to burst to millions of active tasks.
Further reading
For more on evolving infrastructure requirements, visit the Data Centers section.
Source note: This article includes information reported by InfoQ.
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