Daytona
Daytona is a Secure and Elastic Infrastructure for Running AI-Generated Code
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What is Daytona?
Daytona is a secure and elastic infrastructure platform designed specifically for running AI-generated code and powering AI agent workflows. It provides full composable computers called sandboxes that offer complete isolation with a dedicated kernel, filesystem, network stack, and allocated vCPU, RAM, and disk. Sandboxes spin up in under 90ms from code to execution and support Python, TypeScript, JavaScript, Ruby, Go, and Java.
Key features include lightning-fast infrastructure with sub-90ms sandbox creation, separated and isolated runtime for zero-risk execution of AI-generated code, massive parallelization for concurrent AI workflows, and programmatic control through File, Git, LSP, and Execute APIs. The platform offers environment snapshots for saving, restoring, and resuming agent workflows instantly, stateful design for long-running tasks, volumes for shared data across sandboxes, and Computer Use support for Linux, macOS, and Windows virtual desktops. Daytona provides SSH access, VS Code Browser integration, and web terminal access for human-in-the-loop debugging and oversight.
Daytona is built for AI engineers, developers building coding agents, AI research teams, and organizations deploying AI-generated code at scale. It's optimized for LLMs, agents, and evals, supporting data analysis, data visualization, reinforcement learning for agents, and computer use workflows. The platform is open-source under GNU AGPL, offers customer-managed compute options, and meets enterprise compliance standards including HIPAA, SOC 2, and GDPR.
The platform serves companies like SambaNova, LangChain, Prosus, and Sentry, with agents at these organizations using Daytona for secure code execution. It supports multiple SDKs (TypeScript, Python, Ruby, Go, Java), a RESTful API with OpenAPI spec, and CLI for Mac/Linux and Windows.
Daytona pricing
Pricing model: Freemium
Daytona uses pay-as-you-go usage-based pricing with $200 in free compute credit included at sign-up (no credit card required). Per Hour pricing: vCPU at $0.0504/h, Nvidia H100 GPU at $3.95/h, Nvidia RTX PRO 6000 at $3.03/h, Memory at $0.0162/GiB/h, Storage at $0.000108/GiB/h (first 5GB free). Per Second pricing: vCPU at $0.000014/s, H100 at $0.001097/s, RTX PRO 6000 at $0.000842/s, Memory at $0.0000045/GiB/s, Storage at $0.00000003/GiB/s. Volume discounts unlock as usage scales. Startups can get up to $50k in free credits through the Startup Program. Enterprise plans with on-premise or customer-managed compute are available via sales contact with custom pricing. Billing is per second or per hour with no minimum runtime commitment, and bandwidth costs are included with no hidden transfer fees.
Daytona pros
- Sub-90ms sandbox creation from code to execution
- Complete isolation with dedicated kernel, filesystem, and network stack
- Zero risk to infrastructure when executing AI-generated code
- Pay-as-you-go pricing with $200 free compute credit included
- Supports Python, TypeScript, JavaScript, Ruby, Go, and Java
- Multiple SDKs available: TypeScript, Python, Ruby, Go, Java
- Environment snapshots for saving and restoring agent workflows instantly
- Built-in LSP support with multi-language completion and real-time analysis
- Native Git integration with secure credential handling
- GPU support including Nvidia H100 and RTX PRO 6000
- Computer Use support for Linux, macOS, and Windows virtual desktops
- SSH access, VS Code Browser, and web terminal for human oversight
- Open-source under GNU AGPL with transparent codebase
- Customer-managed compute option for enhanced security
- Meets HIPAA, SOC 2, and GDPR compliance standards out of the box
- Docker/OCI compatibility - use any Docker image without modification
- Docker-in-Docker support for running containers inside sandboxes
- Volumes enable shared data across sandboxes without breaking isolation
- Low-latency sandboxes in multiple regions: Frankfurt, London, Washington DC, Oregon, India
- Startup program offers up to $50k in free credits
Daytona cons
- Primarily focused on AI agents rather than traditional development workflows
- Learning curve for developers new to sandbox-based infrastructure
- GPU instances are expensive at $3.95/hour for H100
- Storage pricing applies after first 5GB free tier
- No dedicated mobile app for management
- Self-serve checkout requires API key setup before estimating costs
- Limited documentation on advanced enterprise features without sales contact
- Per-second billing requires careful monitoring to avoid unexpected costs
Frequently asked questions about Daytona
What is Daytona and how does it enable AI?
Daytona is a secure and elastic infrastructure platform for running AI-generated code and agent workflows. It provides full composable computers called sandboxes with complete isolation, dedicated kernel, filesystem, network stack, and allocated resources. Sandboxes spin up in under 90ms and run code in Python, TypeScript, JavaScript, Ruby, Go, and Java. Agents and developers interact programmatically through SDKs, API, and CLI, enabling safe execution of AI-generated code with zero risk to infrastructure while supporting massive parallelization for concurrent AI workflows.
How does Daytona ensure the safe execution of AI-generated code?
Daytona provides separated and isolated runtime protection with each sandbox having complete isolation, a dedicated kernel, filesystem, and network stack. Sandboxes run on customer-managed compute in your cloud or on-prem with no shared compute and no cross-tenant risk. The platform executes AI-generated code with zero risk to your infrastructure through this full isolation, and offers human-in-the-loop access via SSH, VS Code Browser, and web terminal for debugging and oversight without breaking autonomy.
What are AI Sandboxes and how do they enhance agentic AI workflows?
AI Sandboxes are full composable computers provided by Daytona with complete isolation, dedicated kernel, filesystem, network stack, and allocated vCPU, RAM, and disk. They enhance agentic AI workflows by spinning up in under 90ms from code to execution, offering unlimited persistence where sandboxes can live forever, supporting environment snapshots for saving/restoring/resuming agent workflows instantly, and providing stateful design built for long-running tasks and persistent agents. Volumes allow agents to access shared data across sandboxes without breaking isolation.
How can I integrate Daytona into my existing development stack?
Integration starts by creating an account at the Daytona Dashboard using email/password or connecting Google/GitHub, then generating an API key from the Dashboard. Install the Daytona SDK for TypeScript, Python, Ruby, Go, or Java to interact with sandboxes programmatically. The platform offers a RESTful API with OpenAPI spec, Toolbox API with OpenAPI spec, and CLI for Mac/Linux and Windows. You can manage sandbox lifecycle, perform filesystem operations, execute processes and code, and configure runtime. Daytona integrates with Claude, OpenCode, Codex, LangChain, and supports native Git operations with GitHub, GitLab, and Bitbucket.
What security measures does Daytona implement for AI development?
Daytona implements multiple security measures: complete sandbox isolation with dedicated kernel/filesystem/network stack, customer-managed compute option where sandboxes run in your cloud or on-prem with no shared compute, open-source transparency under GNU AGPL allowing verification of every line of code with no black boxes, enterprise compliance meeting HIPAA, SOC 2, and GDPR standards out of the box, granular permission controls for filesystem operations, and secure credential handling for Git integration. SSH access is secure and safe, and the platform provides full auditability through its transparent codebase.
Can I Run My Own Instance of Daytona?
Yes, Daytona supports running your own instance through customer-managed compute options. Sandboxes run on isolated, customer-managed compute in your cloud or on-premises, with Daytona providing the control plane. This ensures no shared compute and no cross-tenant risk. The platform is open-source under GNU AGPL, allowing you to verify the codebase. Enterprise plans are specifically designed for businesses requiring on-premise setup, available through sales contact with custom pricing.
What programming languages does Daytona support?
Daytona officially supports Python, TypeScript, JavaScript, Ruby, Go, and Java for running code in sandboxes. The platform provides SDKs for all these languages: TypeScript SDK, Python SDK, Ruby SDK, Go SDK, and Java SDK. Sandboxes can run any code in these languages with built-in LSP support providing multi-language completion and real-time analysis. The platform also supports OCI/Docker compatibility, allowing you to use any Docker image to create a sandbox, which extends language support beyond the native options.
How does the pay-as-you-go pricing work?
Daytona bills per second or per hour with no minimum runtime commitment. You sign up for a free trial with no credit card required and receive $200 in free compute credit. Pricing is usage-based across 6 SKUs: vCPU ($0.0504/h or $0.000014/s), Memory ($0.0162/GiB/h or $0.0000045/GiB/s), Storage ($0.000108/GiB/h with first 5GB free, or $0.00000003/GiB/s), and GPU options (H100 at $3.95/h or $0.001097/s, RTX PRO 6000 at $3.03/h or $0.000842/s). Bandwidth costs are included with no hidden transfer fees. Volume discounts unlock as usage scales, and you can spin up sandboxes in milliseconds and shut them down just as fast, paying only for what you use.
What is Computer Use in Daytona?
Computer Use provides secure virtual desktops (Linux, Windows, macOS) that you can control with code. It allows agents to use the computer like a human would with full programmatic access and isolated environments. Linux (Ubuntu) offers a desktop with full root access ready for automation, development, and testing. macOS provides desktop instances for iOS development and testing, perfect for mobile app automation. Windows offers full desktop with programmatic control ideal for Windows-specific automation, testing, and development workflows. All threeOperating systems are deployable as isolated sandboxes with complete programmatic control.
How do environment snapshots work in Daytona?
Environment snapshots allow you to save, restore, and resume any agent workflow instantly. The stateful environment snapshots enable persistent agent operations across sessions, making Daytona ideal for AI agent architectures. Sandboxes are stateful by design and run indefinitely, built for long-running tasks and persistent agents. You can snapshot a sandbox at any point (e.g., Snapshot v32 with Node.js 18.0), and later restore it to exactly that state, preserving the filesystem, memory state, and running processes. This enables agents to continue workflows where they left off without reinitialization.