Run Agents with Guardrails: Isolated Sandboxes Next to Your Models and GPUs

Give agents room to work. Set boundaries on what they can reach.

As agent, evaluation, and reinforcement learning workloads scale, so does the challenge of controlling what their code can access. How do you give each task the environment it needs while keeping execution within your platform’s policies?

Watch this 40-minute on-demand walkthrough of CoreWeave Sandboxes to see how one API connects execution across your CoreWeave Kubernetes Service (CKS) clusters and serverless building on the infrastructure and governance controls you already use. Learn how to isolate workloads, control network access, and scale execution next to your models and GPUs

In this on-demand webinar, you’ll learn:

• What a sandbox is, and how one API places CPU and GPU sandboxes across CKS and serverless
• How to set guardrails once to keep agent requests within policy
• How opt-in spillover sends new sandboxes to serverless when your CKS clusters are full
• How to control network access and preserve the state your agents need between runs
• How to run agents, fan out evaluations, and verify RL rewards at scale

Walk away with a clearer plan for where your agent or evaluation workflow should run and how to launch your first sandbox.