Daytona Cloud - AI Agent Infrastructure

The headline number is speed. Daytona starts a sandbox in under 90 milliseconds from code to execution, which is faster than the multi-second cold starts of standard containers and VMs. That difference matters at scale. When you're provisioning tens of thousands of sandboxes, milliseconds per run turn into hours across a batch, so agents stay responsive instead of waiting on a queue.

Sandboxes run indefinitely and keep their state, so they're built for long-running tasks rather than one-shot jobs. You can save a sandbox as a snapshot and restore it later, which makes every run reproducible. That's what separates Daytona from a plain code runner: an agent can pause work, come back and pick up exactly where it left off, across sessions.

Each sandbox has its own kernel, filesystem and network stack, so code runs in full isolation rather than sharing a host. Daytona Secrets keeps plaintext credentials outside the sandbox and swaps them in at network egress, so an agent can call an API without ever holding the real key. For teams handling regulated data, that separation is often the reason to pick this over running code directly.

You control sandboxes programmatically rather than through a dashboard. There are official SDKs for Python, TypeScript, Ruby, Go and Java, plus a REST API and a command-line tool. Operations cover the whole lifecycle: creating and deleting sandboxes, filesystem CRUD, process and code execution, Git operations and runtime config. An LSP server is built in, so editors get completion and diagnostics inside the sandbox.

Daytona can hand an agent a full desktop, not just a shell. Computer Use sandboxes come in Linux (Ubuntu), Windows and macOS flavors, each with programmatic control and root-level access. MacOS instances are useful for iOS build and test work, while Windows covers desktop-specific automation. This is the piece that lets an agent click, type and navigate a real OS the way a person would.

Daytona stays compatible with the tooling teams already use. Sandboxes are built on OCI and Docker, so you can run off-the-shelf Docker images without wrappers, run Docker inside a Daytona sandbox, and drop in a Dockerfile or a Compose file. A declarative image builder lets you create snapshots straight from the SDK, with no CLI step, no manual upload and no registry to manage.

Sandboxes deploy in regions close to your agents, with options such as US East, US West, EU Central, EU West and India. Running near the workload cuts latency for agents that call into a sandbox on every step. Volumes let agents share data across sandboxes without breaking isolation, which keeps multi-step pipelines from copying the same files over and over.