Daytona
Open-source infrastructure for securely running AI-generated code in isolated sandboxes that start in milliseconds, with SDKs for Python, TypeScript, and other languages, persistent snapshots, and an optional managed cloud.
Open the source and read safety notes before installing.
Safety notes
- Daytona is purpose-built to execute arbitrary, AI-generated code; only run untrusted code inside its isolated sandboxes, never on the host.
- Each sandbox has its own kernel, filesystem, and network stack, but sandboxes can make outbound network requests unless network limits are configured.
- Sandboxes support computer use, Git operations, and command execution; scope what an agent can do and review declarative builder configurations before use.
- Self-hosting runs runner compute nodes and Docker services that need elevated host privileges; isolate the deployment from production systems.
- Persistent snapshots retain sandbox filesystem state across sessions, which can preserve secrets or sensitive files written during execution.
Privacy notes
- Using the managed cloud sends your code, files, and execution data to Daytona-operated infrastructure; review their terms before processing sensitive data.
- The platform emits OpenTelemetry metrics, log streaming, and audit logs that can capture command output and activity.
- API keys grant access to your sandboxes and organization; store them as secrets and never commit them to source control.
- Self-hosting keeps execution data on your own infrastructure but you become responsible for log retention, access control, and isolation.
Prerequisites
- A Daytona Cloud account and API key for the managed service, or self-hosted infrastructure for the open-source platform.
- Python 3.8+ for the `daytona` SDK or Node.js 18+ for the `@daytona/sdk` TypeScript SDK.
- Docker and Docker Compose to run supporting services (PostgreSQL, Redis) when self-hosting.
- Nix with flakes enabled or a devcontainer-compatible editor for local development of the platform itself.
Schema details
- Install type
- copy
- Troubleshooting
- No
- Scope
- Source repo
- Website
- https://www.daytona.io
- Pricing
- open-source
- Disclosure
- editorial
- Application category
- DeveloperApplication
- Operating system
- macOS, Windows, Linux
Full copyable content
## Overview
Daytona is open-source infrastructure for securely executing AI-generated code.
It provides sandboxes described as full composable computers with complete
isolation — a dedicated kernel, filesystem, network stack, and allocated vCPU,
RAM, and disk — that spin up in well under a second.
It is aimed at agent builders who need a safe place to run untrusted or
model-generated code at scale. You interact with sandboxes through SDKs, a REST
API, and a CLI, and with humans through a dashboard, web terminal, SSH, and VNC.
Daytona is released under AGPL-3.0; a managed cloud with usage-based pricing is
also available for teams that do not want to self-host.
## Features
- Isolated sandboxes with millisecond start times and per-sandbox kernel,
filesystem, and network stack.
- Persistent snapshots for stateful agent operations across sessions.
- SDKs for Python (`pip install daytona`) and TypeScript
(`npm install @daytona/sdk`), plus Ruby and Go.
- REST API and CLI for programmatic and scripted control.
- Built-in Git operations, LSP support, computer use, and MCP server
integration.
- Organization governance: API keys, audit logs, and billing controls.
## Use Cases
- Give a coding agent a safe sandbox to run and test generated code.
- Execute untrusted user-submitted code without exposing host systems.
- Provide reproducible, snapshot-backed environments for long-running agents.
- Self-host execution infrastructure to keep code and data on your own systems.
## Disclosure
Editorial listing. No paid placement or affiliate relationship. Daytona's core
platform is open source (AGPL-3.0); the managed cloud is a separate paid,
usage-based service.About this resource
Overview
Daytona is open-source infrastructure for securely executing AI-generated code. It provides sandboxes described as full composable computers with complete isolation — a dedicated kernel, filesystem, network stack, and allocated vCPU, RAM, and disk — that spin up in well under a second.
It is aimed at agent builders who need a safe place to run untrusted or model-generated code at scale. You interact with sandboxes through SDKs, a REST API, and a CLI, and with humans through a dashboard, web terminal, SSH, and VNC. Daytona is released under AGPL-3.0; a managed cloud with usage-based pricing is also available for teams that do not want to self-host.
Features
- Isolated sandboxes with millisecond start times and per-sandbox kernel, filesystem, and network stack.
- Persistent snapshots for stateful agent operations across sessions.
- SDKs for Python (
pip install daytona) and TypeScript (npm install @daytona/sdk), plus Ruby and Go. - REST API and CLI for programmatic and scripted control.
- Built-in Git operations, LSP support, computer use, and MCP server integration.
- Organization governance: API keys, audit logs, and billing controls.
Use Cases
- Give a coding agent a safe sandbox to run and test generated code.
- Execute untrusted user-submitted code without exposing host systems.
- Provide reproducible, snapshot-backed environments for long-running agents.
- Self-host execution infrastructure to keep code and data on your own systems.
Disclosure
Editorial listing. No paid placement or affiliate relationship. Daytona's core platform is open source (AGPL-3.0); the managed cloud is a separate paid, usage-based service.
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