Docker Sandboxes vs. Containers: Choosing the Right Isolation for AI Agents
Technology news
Docker explains how microVM-based Sandboxes differ from containers for autonomous coding agents, including the limits of shared workspaces and host-side services.
The Difference Between Docker Sandboxes and Containers
Docker has clarified the technical differences between Docker Sandboxes and containers, noting that while they are often conflated, they serve different purposes. On Linux, containers run as isolated processes sharing the host kernel. On macOS and Windows with Docker Desktop, Linux containers instead share the kernel of the Docker Desktop VM, rather than the host operating system kernel. Docker Sandboxes are dedicated microVMs with their own Linux kernel, filesystem, network and Docker Engine.
Why Docker Recommends Sandboxes for Autonomous Agents
Autonomous AI coding agents operate similarly to developers using a laptop, accumulating state over hours by cloning repositories, installing packages, running databases, and building images. Docker argues that these sessions can benefit from persistent state and broader machine capabilities. Containers remain an established choice for packaged applications and services, CI jobs and short-lived tasks.
Furthermore, AI agents often act on unvetted instructions from various sources, such as web pages or files, which poses security risks. Docker positions Sandboxes as a hypervisor-based boundary intended to limit the impact of an agent’s actions. The company describes four pillars:
- Containment: A boundary the model cannot rewrite.
- Control: Visibility into agent actions and the ability to block them.
- Choice: The freedom to swap agents, models, and tools.
- Capacity: Reproducible setups that can scale beyond a single machine.
Limits of Isolation and Shared Resources
The source also explains that an agent can still reach resources deliberately shared with it. The workspace is mounted read-write by default, so the agent can edit or delete project files. Local stdio MCP servers run on the host, and shared skills use a host-side store. Allowed network destinations and other shared services remain within the agent’s reach. The microVM boundary therefore leaves these shared surfaces to be considered when reviewing access.
Choosing the Right Tool
Docker recommends using containers for packaged applications, CI jobs, and short-lived tasks. Docker Sandboxes are recommended for workloads where the agent generates or fetches code at runtime and requires a stronger isolation boundary than a shared kernel. Notably, a sandbox can still run containers within its environment.
To run Docker Sandboxes, a supported hypervisor is required, such as Apple silicon on macOS 14 or later, the Windows Hypervisor Platform, or KVM on supported Ubuntu systems.