Docker Sandbox Alternatives for AI Coding Agents

The main Docker Sandboxes alternatives are Beam, E2B, Daytona and Modal Sandboxes, plus self-hosted runtimes such as gVisor and Kata Containers. Docker Sandboxes are free on your own machine, so teams usually switch for the cloud: sessions longer than 24 hours, GPUs, a Python SDK, or Docker inside the sandbox without caveats. If you only need something safer than a plain container, every option here puts a VM or a user-space kernel between the code and the host.

What Docker Sandboxes do, and where they stop

Docker Sandboxes run coding agents such as Claude Code and Codex inside a microVM with its own kernel and its own private Docker Engine. Local sandboxes cost nothing, including for commercial work. Cloud sandboxes run on Docker's infrastructure and bill by the second, but they come with limits that matter for agents that run unattended.

What you get:

• Isolation. Each sandbox is a microVM with its own Linux kernel. The agent can build and run containers against its own Docker daemon, with no access to the host's daemon.
• Local use for free. The sbx CLI and local compute are free. A local sandbox persists until you remove it and can pass through the host's GPU.
• Cloud sizes and prices. Five fixed sizes, from 1 vCPU with 2 GB at $0.07 an hour up to 16 vCPUs with 32 GB at $1.12 an hour. Docker says a paused sandbox costs nothing.
• Policy controls. Network, filesystem and MCP access are deny-by-default, and credentials are injected at the network boundary so the agent never sees them.

Where it stops:

• Session length. A cloud sandbox expires after one hour by default, and extensions can't push expiration past 24 hours from creation.
• Platform status. Cloud sandboxes sit on the Docker Agentic Platform, which Docker's docs mark as experimental.
• No GPU in the cloud. Cloud sandboxes have no access to host hardware, so GPU passthrough works only locally.
• SDK languages. The API ships with a TypeScript SDK. Python and other languages call the REST API directly.
• Docker inside the cloud sandbox. Docker's docs warn that docker exec can reach the sandbox VM's filesystem instead of the target container's. That also affects docker compose exec and healthchecks, so Compose services waiting on service_healthy can stay blocked.

That last point surprises people, because a private Docker Engine is the main reason to pick Docker Sandboxes in the first place.

Docker sandbox vs a Docker container

A Docker container shares the host's kernel, so a kernel exploit inside it can reach the machine it runs on. A Docker sandbox runs the container work inside a microVM with a separate kernel, which is a much stronger boundary for code an AI model wrote. Docker's own architecture docs rank the options the same way.

Docker's comparison, paraphrased:

• Sandbox (microVM): full isolation at the hypervisor, with a daemon of its own. Meant for autonomous agents.
• Container with the Docker socket mounted: partial isolation through namespaces, and the agent shares the host's daemon. Fine for trusted tools.
• Docker-in-Docker: partial isolation, because the outer container runs privileged. Common in CI pipelines.
• Running on the host: no isolation at all.

So if your search started with "is a container safe enough for AI-generated code", the answer is usually no, and the alternatives below all go further than a container. For the background on what a container actually isolates, see what a container really is.

Docker Sandboxes alternatives compared

Beam, E2B, Daytona and Modal all run agent code from an SDK, and they differ on whether Docker runs inside, whether a GPU is available, and how long a session lasts. Beam VMs are the cheapest cloud option per hour in this group and have no session cap; E2B is the closest match to Docker's microVM model with a mature fork API. The table compares one sandbox with 1 vCPU and 2 GiB of memory, computed from each vendor's list rates.

A few notes on reading it. Docker's cloud sizes are fixed pairs, so $0.07 buys exactly 1 vCPU and 2 GB. Modal bills the higher of your request or actual use. Beam sandboxes and VMs are separate products with separate rates, covered below. Beam sandboxes and Modal bill per physical core (2 vCPU); figures are normalized to 1 vCPU.

How to run Docker and Compose inside an agent sandbox

To run Docker inside a sandbox, you need a sandbox with its own kernel or a runtime that supports a nested daemon, plus Docker installed in the image. Docker Sandboxes ship with an engine, Beam VMs have Docker preinstalled, E2B and Daytona need a template or snapshot with Docker in it, and Modal needs its VM runtime.

What each one asks of you:

• Beam VMs: create the VM with --docker-enabled. Docker, Compose and Buildx are already in the image, and images, build cache and volumes survive stop and start.
• Beam sandboxes: pass docker_enabled=True and build the image with Image(...).with_docker(). Host-port remapping isn't supported, so expose the port the service actually listens on.
• E2B: build a template that runs the get.docker.com install script. E2B recommends at least 2 CPUs and 2 GB of RAM.
• Daytona: create a snapshot from a Docker-in-Docker image such as docker:28.3.3-dind, then start sandboxes from it. Daytona recommends at least 2 vCPU and 4 GiB.
• Modal: create the sandbox with runtime="vm" and start dockerd as the entrypoint. GPU sandboxes run only on gVisor, so you can't have Docker and a GPU in the same Modal sandbox.

Here's a Compose stack on a Beam VM. Create the VM once from the CLI:

Or drive the same stack from Python with the SDK's Compose helper:

The --protected flag puts the published port behind Beam's access token, and the URL stays the same after the VM stops and starts. One detail worth knowing: nested containers don't inherit the VM's brokered-secret certificate, so mount /etc/beam/ca-certificates.crt into any container that calls an API with brokered credentials.

The alternatives, one by one

Pick by the job the agent does. Each review below opens with the workload it fits.

Beam: persistent VMs with Docker, and GPU sandboxes

Beam fits teams whose agents need a machine of their own with Docker on it, or code sandboxes with a GPU attached. These are two products, and it helps to keep them apart.

Beam virtual machines are persistent CPU microVMs, each with its own kernel, systemd and a durable root disk. Docker, Compose and Buildx are preinstalled, and the daemon turns on with one flag. Pause keeps RAM and running containers; stop keeps the disk and releases compute; fork copies the filesystem into a new VM. You get SSH through an authenticated tunnel, a browser desktop, and Claude Code and Codex CLIs in the prepared images. VMs are billed per second while running, at $0.0252 per vCPU-hour and $0.0054 per GiB-hour, with no compute charge while stopped or paused. They have no GPUs.

Beam sandboxes are short-lived environments for code execution that boot in seconds. They run as containers, or as microVMs with use_vm=True, and they can attach a GPU with one argument. Docker works inside with docker_enabled=True. Memory snapshots let you fork a running sandbox on supported runtimes.

Where Docker Sandboxes win: local sandboxes are free and run next to your files, and Beam is cloud-only. Beam's runtime, beta9, is open source if you want to self-host it, though the self-hosting guides don't cover VMs. Rates for every product are on the pricing page.

E2B: Firecracker sandboxes with pause and fork

E2B is the closest match to Docker Sandboxes' isolation model. Every sandbox is a Firecracker microVM, and pause, snapshots and fork all keep memory. Pick it for CPU agents that need to branch a running session.

Docker isn't in the default image. You build a template that installs it, and E2B's docs give a working example. Hobby accounts get a one-time $100 credit and 1-hour sessions; Pro costs $150 a month and allows 24 hours, and pausing resets the clock. There are no GPUs. The E2B pricing breakdown covers the plans, and our E2B alternatives guide compares it against a wider field.

Daytona: the widest catalog, containers by default

Daytona offers container, Linux VM, Windows and GPU sandboxes behind one SDK, with SDKs in Python, TypeScript, Ruby, Go and Java. Pick it when you need GPUs and Docker from the same vendor, or a Windows target.

Docker-in-Docker runs from a snapshot built on an official dind image, and Compose works inside it. Sandboxes are containers by default, and memory pause and fork need one of the VM classes. Sandboxes stop after 15 idle minutes unless you turn that off. More detail is in our Daytona alternatives roundup.

Modal Sandboxes: Docker on the VM runtime

Modal suits teams already running inference or training on Modal. Sandboxes run on gVisor or on a VM runtime with its own kernel, and only the VM runtime can run Docker. GPU sandboxes use gVisor and can be preempted, so Docker and GPUs don't mix on Modal.

Every sandbox is capped at 24 hours, and Modal recommends restoring from a snapshot to go longer. Sandboxes bill at three times Modal's list compute rate.

Self-hosted runtimes: gVisor, Kata Containers and Firecracker

If you'd rather keep everything on your own servers, you can harden containers yourself. gVisor intercepts system calls in a user-space kernel, Kata Containers runs each container in a lightweight VM, and Firecracker is the microVM monitor behind AWS Lambda. All three need real operational work: images, networking, scheduling and cleanup are yours to build.

Our guide to self-hosting a code sandbox walks through what that takes, and the stateful sandbox comparison covers which state each managed provider keeps.

How to choose a Docker Sandboxes alternative

Start from what the agent needs that Docker's cloud doesn't give it. Most teams end up with one of these:

• A long-lived machine with Docker and Compose: Beam VMs. No session cap, Docker preinstalled, pause keeps running containers, and the lowest cloud rate in the table.
• Docker plus a GPU in the same sandbox: Beam sandboxes or Daytona.
• Forking a running CPU sandbox, memory included: E2B.
• One vendor for sandboxes and the rest of your ML stack: Modal, if you can live with 24-hour sessions and no Docker on GPU sandboxes.
• An agent on your laptop: stay on Docker Sandboxes. Local use is free and hard to beat.

FAQ

What are the best alternatives to Docker Sandboxes?

Beam, E2B, Daytona and Modal Sandboxes are the main managed alternatives. Beam VMs suit agents that need a persistent machine with Docker, E2B suits CPU agents that fork running sessions, Daytona covers GPUs and Windows, and Modal fits teams already on Modal. gVisor, Kata Containers and Firecracker are the self-hosted route.

Docker Sandboxes vs E2B: which should I use?

Use Docker Sandboxes for agents on your own machine, since local use is free and Docker comes built in. Use E2B for cloud agents that need pause and fork with memory, since every E2B sandbox is a Firecracker microVM with a mature fork API. Neither offers a GPU in the cloud.

Is there an E2B alternative that gives agents full VMs with Docker-in-Docker?

Yes. Beam VMs are full Linux microVMs with their own kernel and systemd, and Docker, Compose and Buildx come preinstalled. Turn the daemon on with --docker-enabled, and Docker's images and volumes survive stop and start. Pause keeps the running containers too.

Are Docker Sandboxes free?

Local Docker Sandboxes are free, including for commercial use. Cloud sandboxes bill compute by the second, from $0.07 an hour for 1 vCPU and 2 GB to $1.12 an hour for 16 vCPUs and 32 GB. Model-provider charges are separate.

Can an AI agent sandbox run Docker Compose?

Yes, on several platforms. Beam VMs and Beam sandboxes have Compose helpers in the SDK, Daytona runs Compose from a Docker-in-Docker snapshot, and E2B can install the Compose plugin in a template. In Docker's cloud sandboxes, Compose runs, but docker compose exec can reach the wrong filesystem and healthchecks can report wrong results.

Is a Docker container secure enough for AI-generated code?

Usually not on its own. A container shares the host kernel, so a kernel exploit can escape it, and mounting the Docker socket hands the agent the host's daemon. A microVM or gVisor sandbox adds a separate kernel or a user-space kernel between the code and the host.

Give your agent a VM with Docker on it

Beam VMs come with Docker and Compose preinstalled, pause with running containers intact, and bill per second only while they run. Create a Beam account and start a VM with beam vm new devbox --docker-enabled.