sandboxd
Self-hosted AI coding sandboxes: one Linux box becomes a fleet of Docker dev environments with agent CLIs built in.
If you already run a Linux server and need isolated per-agent or per-user workspaces, sandboxd is the cheapest credible route — MIT license, one install command, no per-seat bill. The catch is real: you own the uptime, the host memory, and the upgrades. Teams that want someone else on call should look at Docker Sandboxes or another managed harness instead.
Last checked 16d ago · cite: rightaichoice.com/tools/sandboxd
- AI app-builder product teams running per-user sandboxes
- Agent platform builders needing an isolated workspace per coding agent
- Teams managing per-user or per-branch preview environments
- Cost-conscious teams with an existing Linux server or on-prem box
- Solo developers who just want to run one or two containers
- Teams that want a managed cloud sandbox with zero ops burden
- Users requiring Kubernetes-native orchestration
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Skip sandboxd if you don't want to operate your own Docker host, need managed scaling across many machines, or expect a web-based management UI — this is a self-hosted, CLI-centric tool.
You pay for the server (VPS or on-prem) yourself — at scale, that's the real cost, not the software.
sandboxd is free and open-source (MIT); your only cost is the hardware you run it on. Compared to per-seat SaaS sandbox pricing (often $20+/user/mo), running dozens of sandboxes on a $20 VPS is dramatically cheaper for teams that can self-host. Managed services like Docker Sandboxes offer convenience but at a higher unit cost.
In short
sandboxd — Self-hosted AI coding sandboxes: one Linux box becomes a fleet of Docker dev environments with agent CLIs built in. Best for AI app-builder product teams running per-user sandboxes, Agent platform builders needing an isolated workspace per coding agent, Teams managing per-user or per-branch preview environments. Free to use.
What people actually say about sandboxd — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
6 mentions across 4 sources (Hacker News, YouTube, Product Hunt, GitHub), 28 more we could not attribute · researched Sep 15, 2026.
Weighted by the 34 posts each of 4 sources contributed.
- +One command install on a $20 VPS replaces per-seat managed sandbox SaaS bills.
- +Per-sandbox Docker containers with filesystem and memory limits keep tenants separated.
- +Claude Code and OpenCode CLIs come pre-installed, so agents spawn with zero setup.
- +Idle-to-zero memory with instant wake keeps dozens of sandboxes cheap to run.
- +Traefik handles preview URL routing and TLS automatically for each sandbox.
- −Docker-only isolation raised unresolved HN concerns versus MicroVM-grade boundaries.
- −Default install previews are localhost or sslip.io, not public URLs.
- −No Kubernetes, no HA, no managed scaling — you own the on-call burden.
- −External review data is thin: no Reddit, Stack Overflow, or App Store feedback.
- −SQLite and single-host architecture limits horizontal scale-out.
- • You still pay for the VPS or on-prem hardware — a $20 VPS is the maintainer's own reference point
- • Engineering time to configure public DNS/TLS for previews beyond sslip.io
- • Your own on-call and backup responsibility; no vendor SLA exists
Viability Score
How well maintained and how widely used is sandboxd? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- Per-sandbox Docker containers with filesystem and memory limits
- Pre-installed OpenCode CLI for agentic coding
- Pre-installed Claude Code CLI
- Live preview URLs with automatic routing and TLS via Traefik
- Sandbox idle sleep to zero memory with instant wake
- REST API for create, exec, write files, and streaming
- SSE streaming for real-time command output
- SQLite state management with no external database
- Reconciler converges Docker state after host reboot
- Host-memory pressure reaper for multi-tenant safety
- Custom API provider keys configured per sandbox
- MIT licensed for commercial use
- One-command install (./install.sh)
- Single Go binary orchestrating Docker
- No Kubernetes, no message queue required
About sandboxd
sandboxd turns a single Linux server into a fleet of isolated development environments, each a lightweight Docker container with its own filesystem and memory limits. OpenCode and Claude Code CLIs come pre-installed, so an AI coding agent per sandbox needs zero setup work on your end. The product fits teams running multi-tenant workloads: an AI app-builder SaaS, an agent platform that needs a workspace per coding agent, or per-user and per-branch preview environments. Live preview URLs with automatic routing and TLS are handled by Traefik, and sandboxes idle to zero memory usage before waking on request — which is why dozens of environments can share one $20 VPS or an on-prem box you already own. Under the hood it stays deliberately small: one Go binary orchestrating Docker, Traefik for HTTPS, SQLite for state. No Kubernetes, no external database, no message queue. The MIT-licensed codebase reads in an afternoon, setup is a single ./install.sh, and a REST API handles sandbox creation, command execution, file writes, and SSE result streaming. Sandboxes survive reboots because a reconciler converges Docker state, and a host-memory pressure reaper keeps one runaway tenant from taking down the others. That self-hosted shape sits at an angle to managed options. Docker Sandboxes, launched in August 2026, ships disposable isolated environments for AI agents as a hosted convenience; sandboxd asks you to own the hardware instead, and in exchange your code, data, and API keys never leave it. Different trade: you keep control and pay no per-seat fee, but managed scaling and 24/7 support are not part of the deal.
Behind the Verdict
Pick sandboxd when the machine is already yours. A spare VPS or an on-prem box turns into dozens of isolated environments with per-sandbox memory caps, TLS preview URLs, and agent CLIs preinstalled — no seat pricing, no data leaving your network. We'd reach for it specifically when an agent platform needs a clean workspace per coding agent, or when a product ships per-user and per-branch previews and the per-seat math on managed sandboxes has stopped making sense. Pass when nobody on the team wants to own a Linux host. This is infrastructure you operate — Docker, Traefik, SQLite, a reconciler that has to survive reboots. There's no web UI, so non-technical users are out. If your workloads swing hard or you need a support contract, a hosted option will cost less in engineer hours than it saves in license fees. The closest alternative is Docker Sandboxes, which launched in August 2026 as disposable isolated environments for AI agents. Docker's version removes the ops burden and asks you to trust their infrastructure; sandboxd keeps keys and code on hardware you control and asks you to keep the lights on. OneCLI, the YC-backed open-source agent harness, targets a similar team buyer with a different abstraction — worth a look if you want more opinionated agent plumbing rather than raw sandbox primitives. In practice the architecture choices are the selling point. One Go binary, no Kubernetes, no external database, no queue — small enough that a competent engineer can read the source and patch it. The host-memory reaper is the detail that matters at multi-tenant scale; without something like it, one greedy sandbox starves the rest. Watch the edges. Idle-to-zero works well for bursty preview traffic and poorly for always-hot sessions, and single-host means single point
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Real-world workflow fit
Concrete scenarios for the personas sandboxd actually fits — and what changes day-one when you adopt it.
You run an AI app-builder like Lovable. For each user prompt, you need to spawn an isolated sandbox where an agent writes code and serves a preview URL.
Outcome: On sandboxd, you call the REST API to create a sandbox with pre-installed OpenCode/Claude Code, get an HTTPS preview URL, and stream the output via SSE — all on your own VPS.
Your platform gives each coding agent a separate workspace with its own API keys and filesystem to prevent cross-agent interference.
Outcome: You provision per-agent sandboxes with custom API keys, set memory limits, and rely on the reaper to reclaim idle memory — running many agents safely on one box.
You want per-branch preview environments for your web apps, but you don't want to pay for a managed preview service.
Outcome: You point sandboxd at your repo, each PR gets a sandbox with a unique preview URL, and sandboxes sleep when not accessed — cutting hosting costs.
Use Cases
- Build an AI app-builder backend that live-previews every user's generated app on a shared server
- Give each coding agent an isolated sandbox with its own API keys and filesystem
- Spin per-branch preview environments for web apps that automatically sleep when not accessed
- Hand out disposable coding playgrounds to workshop attendees with resource limits
- Host multiple internal tools on a single VPS, each at its own URL, waking only when used
- Run a prompt-to-app pipeline where a user prompt triggers an agent to write and preview code in seconds
Models Under the Hood
as of 2026-09-01
Limitations
- As self-hosted software, sandboxd requires maintaining a Docker host and managing server resources.
- It does not offer managed scaling across multiple machines or built-in rate limiting per user.
- Preview URLs are only accessible if the host is reachable from the internet.
- For teams that need elastic scale, consider managed solutions like Docker Sandboxes or Superconductor.
as of 2026-08-30
Verification history
We have re-verified sandboxd 8 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 8 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published sandboxd tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Self-Hosted (Open Source)
$0/mo
Ideal for
Teams that already run a Linux server or VPS and want to host multi-tenant AI coding sandboxes at no software cost, keeping full control of code and keys.
What this tier adds
Starting tier: free MIT-licensed software — you pay only for hosting. All features are included; no paid tiers exist.
Where the pricing makes sense
The company stage and team size where sandboxd's pricing actually pencils out — and where peers do it cheaper.
sandboxd is free and open-source (MIT); your only cost is the hardware you run it on. Compared to per-seat SaaS sandbox pricing (often $20+/user/mo), running dozens of sandboxes on a $20 VPS is dramatically cheaper for teams that can self-host. Managed services like Docker Sandboxes offer convenience but at a higher unit cost.
Setup time & first value
How long it actually takes to get something useful out of sandboxd — broken out by persona, not the marketing-page minute.
For a dev ops engineer: under 30 minutes to have a Docker host running sandboxd and your first sandbox live. For an app developer integrating the REST API: a few hours to wire up create/exec/stream calls. For a non-technical user: not applicable — you need shell access.
Switching to or from sandboxd
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- ↗To Docker Sandboxes: If you need managed, ephemeral sandboxes without self-hosting, Docker's new disposable sandboxes could be a drop-in alternative.
- ↗To E2B: If you need a cloud-hosted sandbox runtime with SDKs and managed scaling, E2B is a popular migration target.
- ↗To Superconductor remote sandboxes: For enterprise-grade remote sandboxing with advanced isolation, consider Superconductor's platform.
Integrations
Tutorials & Learning
YouTube returned 6 videos for “sandboxd”, and we withheld 6: 6 could not be judged, because “sandboxd” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about sandboxd.
Official links
Tools that pair well with sandboxd
Common stack mates teams adopt alongside sandboxd, with the specific reason each pairing earns its keep.
Coder
Coder is a self-hosted platform for cloud development environments that governs the AI coding agents and LLM traffic running inside them.
Poolside AI
Open-weight agentic coding models — Laguna XS 2.1 (33B) and Laguna S 2.1 (118B) — built for code that cannot leave your security boundary.
Codeium
Devin Desktop is a free AI coding assistant and agent IDE with unlimited Tab completions and an Agent Command Center for fleets of local
Featured Head-to-Head Comparisons
Sandboxd vs Voyage Ai
If your need is high-accuracy retrieval over dense domain-specific documents (finance, legal, code), Voyage AI's specialized embedding models and rerankers are unmatched, but be prepared for enterprise pricing and sales engagement. If you're building AI agent apps (like Lovable, Bolt) that need isolated, self-hosted sandboxes per user with zero memory overhead, sandboxd's free, open-source model is a no-brainer. These tools solve completely different problems—choose based on whether your bottleneck is retrieval accuracy or sandbox orchestration.
Sandboxd vs Spider Cloud
Spider Cloud is your pick if you need fast, reliable web data extraction for AI agents or RAG pipelines. sandboxd fits if you run an AI app builder product and need to manage many isolated coding environments on your own server. They solve completely different problems; choose based on whether you need data (Spider) or sandboxes (sandboxd).
Sandboxd vs Temporal Ai
Temporal AI and sandboxd serve fundamentally different needs. Temporal AI is the right choice for teams requiring bulletproof durability and orchestration for complex, long-running workflows – think OpenAI or Replit. sandboxd is ideal for product teams that need to manage many isolated coding environments on their own infrastructure, like an AI app builder or agent platform. Evaluate based on whether you need workflow reliability (pick Temporal) or sandbox isolation (pick sandboxd).
Alternatives to sandboxd
View all
Coder
Coder is a self-hosted platform for cloud development environments that governs the AI coding agents and LLM traffic running inside them.
Poolside AI
Open-weight agentic coding models — Laguna XS 2.1 (33B) and Laguna S 2.1 (118B) — built for code that cannot leave your security boundary.
Frequently Asked Questions
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