Runtime Roundup: VM Sandboxes, Multi-node clusters, and more

Modal announced several infrastructure features at its inaugural Runtime conference aimed at supporting AI agents, large-scale machine learning, and production inference. VM Sandboxes provide agents with isolated full Linux virtual machines capable of running Docker, databases, development servers, graphical environments, simulators, and kernel-level workloads, and are already used by companies including Linear, Legora, and Snorkel. Sandbox Sidecars add co-located but isolated containers for securely handling credentials, proxies, and trusted logic while keeping communication local and low-latency. Modal Clusters, now generally available through the `@modal.clustered` decorator, enable coordinated multi-container jobs for workloads such as training and serving trillion-parameter models, with users including Decagon, 1x, and Runway. Sticky Sessions preserve application state by routing a client back to the same running container, supporting seamless reconnections for real-time applications such as voice-model serving. Endpoint Candidates, currently in private beta for selected customers, allow teams to mirror production traffic to alternative inference configurations and evaluate quality, latency, throughput, and cost before promotion to production.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.