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Scalable Pixel Streaming

2 posts · May 2026

What this trail covers

CoreWeave enhances its AI infrastructure to support scalable Pixel Streaming applications for Unreal Engine creators. This involves leveraging CoreWeave's high-performance GPU cloud, Kubernetes-native infrastructure, and rapid auto-scaling capabilities to provide a cost-effective and accessible platform for deploying real-time interactive content. The integration with TensorWorks' Scalable Pixel Streaming (SPS) solution aims to simplify deployment and management of these demanding workloads, and CoreWeave's infrastructure is specifically designed for high-performance, compute-intensive workloads served on-demand with high availability, offering responsive auto-scaling and lightning fast spin-up times.

All Coreweave trails
  1. CoreWeave Empowers Real-Time Collaborative Filmmaking with Spire Animation StudiosThis post details how Spire Animation Studios partnered with CoreWeave to build a cloud-native infrastructure for real-time collaborative filmmaking using Unreal Engine. It highlights the use of CoreWeave's virtual workstations with high-end NVIDIA GPUs for individual artists and rendering queues, the ability to scale to hundreds of GPUs for long sequences, and the flexibility of Kubernetes for real-time VM specification changes. The post also discusses Spire's investigation into leveraging USD and NVIDIA GPUs with Pixel Streaming for high-quality previews and the use of CoreWeave's VS API to build a custom dashboard for workstation assignment and management, including short-lived, self-destructing machines for specific tasks.
  2. Scalable Pixel Streaming with TensorWorks on CoreWeaveThis post details the integration of TensorWorks' Scalable Pixel Streaming (SPS) solution with CoreWeave Cloud, enabling Unreal Engine creators to deploy Pixel Streaming applications at scale. It highlights CoreWeave's high-performance GPU cloud, Kubernetes-native infrastructure, and rapid auto-scaling capabilities, specifically mentioning the NVIDIA A40 GPU and its large fleet. The post emphasizes the cost-effectiveness and accessibility of this solution compared to traditional cloud providers, reducing per-user costs by up to 80%. It also provides instructions for a closed beta.