Daytona

Overview

Daytona is a runtime for executing AI-generated code and agent workflows in isolated sandboxes. It suits teams building code execution into AI products or developer tools. Its APIs, network controls and broad integration options are compelling; usage-based costs and tier-gated VPN access call for careful planning.

Key features

Daytona says it creates sandboxes in under 90 milliseconds, a useful target for interactive agent workflows and other workloads that need quick execution. Isolated runtimes are designed to contain generated code, with AI evaluations, code interpreters, coding agents and data analysis among its stated use cases. Speed and isolation address important execution needs, but neither removes the need to manage runtime charges.

Execution APIs support process execution, filesystem operations and Git integration, with built-in language-server protocol support. SDK examples cover Python, TypeScript, Ruby, Go and Java. The CLI supports macOS, Linux and Windows, while the MCP server documentation names Claude, Cursor and Windsurf. This range gives teams several integration paths; it is most useful when those interfaces fit an existing stack.

Network controls include IPv4 CIDR and domain allow lists, the option to block all outbound traffic, and chained outbound proxies. Organization-scoped secrets are encrypted at rest; sandboxes receive opaque placeholders, with plaintext substituted only for allowed HTTPS hosts. These controls help teams restrict what sandboxed code can reach and how secrets are exposed. VPN connections support Tailscale, OpenVPN and Netbird, but require Tier 3 or higher, which makes them a tier-dependent option rather than a baseline capability.

Daytona supports Dockerfile workspace configuration, multiple VCS hosts, prebuilds, persistent storage, GPU workspaces, JetBrains support and self-hosting. Its Trust Center lists GDPR, HIPAA, SOC 2, ISO/IEC 27001, SOC 2 Type 1 and SOC 2 Type 2 compliance materials. Support may be provided through email, Slack, in-app chat, video support or community forums.

Pricing

Daytona uses a freemium model with free access and a free trial. The Start-ups plan is free, billed in credits, with up to $50k in credits at no charge. That can suit startups seeking credits for early use, though credit-based access is not the same as a fixed allowance of ongoing compute.

Pay-as-you-go pricing is usage-based and billed per second. Rates are vCPU $0.0504/h, Memory $0.0162/h, Storage $0.000108/h and Windows $0.0858/vCPU/h. The first 5 GiB of storage is free, and $200 in free compute is included; GPU rates vary by model and preemptible or on-demand use. A separate Pay-as-you-go plan also identifies 5 GiB of free storage before storage charges. These terms make the entry cost approachable, but variable compute, memory, storage and GPU use can make costs harder to forecast than a fixed subscription.

Enterprise pricing is custom pricing and includes larger limits, SSO, audit logs and BYOC. It is the better fit for organizations that need those controls and capacity; smaller teams that do not need them can start with credits or usage-based access. The published plans do not state seat limits or a trial length.

Platforms

Daytona lists API, Linux, macOS, self-hosted, web and Windows support. The cross-platform CLI and self-hosting option suit teams that need different development environments, while API access is central to programmatic execution.

Who it's for

Daytona is a strong fit for teams building AI agents, code interpreters or evaluation pipelines that need isolated execution, API control and configurable outbound access. Its SDK range, persistent storage and prebuilds also suit teams connecting sandboxes to established development workflows. It is less suited to buyers who need a predictable flat price or VPN connectivity below Tier 3.

Pros and cons

• Pros: Fast sandbox creation and isolated execution target responsive, safer AI-code workflows.
• Pros: Process, filesystem and Git APIs, five SDK languages and named agent integrations give teams multiple integration routes.
• Pros: Network rules and constrained secret injection provide practical controls for limiting sandbox access.
• Cons: Usage-based compute, memory, storage and variable GPU rates require cost monitoring.
• Cons: VPN connections require Tier 3 or higher, so teams cannot assume they are included at entry levels.

Alternatives

E2B is worth considering for teams that prioritize an Apache-2.0-licensed runtime they can self-host; its Hobby plan includes a $100 one-time usage credit. Choose Daytona instead when its named SDKs, MCP integrations or network controls better match the workflow.

Docker Desktop may suit developers who want a familiar container-focused tool with a free Docker Personal plan for one user, one Scout-enabled repository, 100 Docker Hub pulls per hour and one private repository. Daytona is the closer fit when the goal is an API-controlled runtime for AI-generated code.

Northflank is an option for teams whose needs center on always-on compute, with its free Sandbox plan including two services, one database and two cron jobs. Choose Daytona when isolated AI-code execution and its execution APIs are the priority.

microsandbox offers a free plan with five vCPU-hours, 20 memory GiB-hours, 20 disk GiB-hours and up to three sandboxes, each capped at one vCPU and 512 MiB memory. It may fit tightly bounded sandbox use; Daytona offers a broader set of named APIs, SDKs and network controls.

ANY.RUN has a free Community plan and supports Android, API, iOS, Linux, macOS, web and Windows. crun is a free Linux and self-hosted OCI container runtime. Sandboxie Plus is a Windows option with a free personal-use plan. Firejail is a free Linux desktop-focused project for readers seeking a community tool.

For more options, browse Sandbox Software, Cloud Development Environments or Coding Playgrounds.

Verdict

Choose Daytona if you are building AI workflows that need isolated, fast code execution, programmatic control and configurable network restrictions. Its main advantage is the combination of execution APIs, integrations and security controls; its main drawback is that usage-based charges need active budgeting and VPN access is tier-gated. Teams seeking predictable fixed pricing or entry-level VPN connectivity should look elsewhere.