Daytona

Daytona is an agent-native sandbox infrastructure platform that spins up isolated code execution environments in under 90ms — with optimized configurations hitting 27ms cold starts — eliminating the 2–5 second Docker delays that compound into 30+ second overhead across a typical 15-tool-call agent loop. What Is Daytona? Agent-Native Sandbox Infrastructure Explained Daytona is a managed sandbox platform purpose-built for AI agents — it provides isolated, stateful compute environments that agents can spin up, execute code in, snapshot, fork, and destroy without managing container lifecycle manually. Unlike generic cloud VMs or developer-oriented cloud IDEs, Daytona is engineered around the agent execution model: fast cold starts, persistent state between tool calls, and native SDK support for Python, TypeScript, Ruby, and Go. Founded in 2023 by Ivan Burazin, Vedran Jukic, and Goran Draganic — the team that built Codeanywhere, one of the earliest cloud development platforms — Daytona raised a $24M Series A in February 2026 led by FirstMark Capital, with Pace Capital, Upfront Ventures, Datadog, and Figma Ventures participating. Customers include LangChain, Turing, Writer, SambaNova, and Fortune 100 enterprises. The platform reached $1M forward revenue run rate in under three months after launch, then doubled that figure six weeks later — a trajectory that validates the market need for agent-native compute infrastructure beyond what general-purpose Docker-based tooling provides. ...

On April 15, 2026, OpenAI shipped Agents SDK v2 with seven native sandbox providers baked directly into the framework — Blaxel, Cloudflare, Daytona, E2B, Modal, Runloop, and Vercel. That single release turned sandbox selection from a niche infrastructure decision into a routine engineering choice that every AI agent team now has to make. Three providers dominate early conversations: E2B, Daytona, and Blaxel. Each is production-ready, each has native SDK integration, and each is built around a fundamentally different runtime model. This article breaks down exactly where they diverge, which workload profile each one is optimized for, and how to pick the right one without running a month of expensive benchmarks. ...