What is sandbox as a service?
A definition, a disambiguation, and a checklist. If you are evaluating providers rather than looking for a specific product, start here — and if you already know you want a disposable VM behind an API, the product page is the shorter route.
The term means three different things
Before comparing anything, work out which industry's vocabulary a vendor is using. The three senses are unrelated technically, and a search for the phrase returns all of them mixed together.
1. Regulatory or partner sandbox (fintech, healthcare)
A supervised environment with mock data and a constrained API surface, where a firm can trial a product before or during authorisation. The "sandbox" is a compliance and data-access construct. Nothing about it concerns code isolation.
2. Malware analysis sandbox (security)
An instrumented detonation environment where a suspicious file is executed and its behaviour recorded — syscalls, network callbacks, filesystem changes. The isolation exists to enable observation. The product is the report, not the machine.
3. Developer compute sandbox (infrastructure)
An isolated machine, created on demand through an API, in which you run code that should not run anywhere else: model-generated scripts, user submissions, an agent's shell session. The isolation exists to bound damage, and the machine is disposable. This is the sense used throughout this site, and the rest of this page is about it.
What the developer-compute version actually provides
On-demand creation
A machine exists because you asked for one a moment ago, not because it was provisioned last quarter. The unit of consumption is a sandbox, not a server, and the API call is the whole provisioning process.
An isolation boundary you did not build
Containers, microVMs or full VMs, plus the guard rails around them: unprivileged execution, blocked metadata endpoints, network egress policy. Building this correctly is possible and is a substantial ongoing commitment.
Guaranteed teardown
Every sandbox has an expiry that the platform enforces, plus reconciliation for machines that outlive their record. Without this, "disposable" is an intention rather than a property, and the failure mode is a bill.
Usage-shaped billing
You are paying for minutes of runtime rather than reserved capacity. That is the economic argument for the category: spiky, unpredictable workloads are exactly what reserved infrastructure handles badly.
How to evaluate a provider
Six questions separate offerings in this category. They are all answerable from public documentation, and a vendor who cannot answer one plainly has told you something.
- Where is the isolation boundary? Container on a shared kernel, or a virtual machine with its own? For adversarial code the distinction is the whole argument, because it determines whether a kernel bug is contained or shared.
- Is a machine ever reused between customers? "Reset" and "destroyed" are different guarantees. Ask which one applies.
- Is there a floor? Plan fees, minimum commitments and per-seat charges determine whether a low-volume workload is viable at all. Metered rates look cheap until a subscription is required to unlock the limits you need.
- What are the real limits? Maximum sandbox lifetime, concurrent sandboxes, output size, disk. These decide whether a workload fits, and they are frequently tier-gated.
- Who guarantees teardown? If cleanup depends on your code calling delete, a crash in your orchestrator becomes an invoice. A platform-enforced timeout is the property you want.
- What is measured versus marketed? Startup latency in particular: ask whether a quoted number is a warm-pool hit or a cold provision, and what happens when the pool is empty. Numbers published with their conditions are worth more than smaller numbers published without.
And the honest counter-question
Should you buy this at all? If you run your own cluster and the code is yours, a container you already operate is cheaper and lower-latency. The category earns its margin in exactly two situations: the code is genuinely adversarial and you do not want to own that boundary, or the load is spiky enough that reserved capacity is mostly idle. Both describe agent and user-submitted-code workloads well, which is why the category grew alongside them.
Where this service sits
One dedicated VM per sandbox, 3 fixed sizes, prepaid credit billed per started minute with no plan fee, three REST endpoints and an MCP server. A sandbox lives at most 24 hours and is destroyed at expiry whether or not you call delete. The overview has the product detail; pricing has the rate card; limits has the measured numbers.
Questions
Is sandbox as a service the same as a regulatory sandbox?
No, though they share the word. In fintech, a "sandbox" is usually a regulatory or partner environment: a supervised setting with mock data and a controlled API surface where a firm can test a product without full authorisation. In security, a sandbox is a detonation environment for suspected malware. In developer infrastructure — the sense used on this site — it is an on-demand isolated machine for running code. The three have almost nothing in common technically, so check which one a vendor means before comparing them.
How is it different from CI?
CI is triggered by an event and runs a pipeline you defined in advance. A sandbox is created by an API call, at arbitrary times, and runs whatever you decide once it exists. That difference matters most for agents and user-submitted code, where the workload is not known until runtime. CI runners can be pressed into this role, but you inherit queueing behaviour, a config file per job shape, and an isolation model built for your own trusted code.
Why not just run containers myself?
Often you should — if you already operate a cluster and the code you run is your own, a container is cheaper and closer to hand. The calculation changes when the code is adversarial, because a shared kernel makes an unprivileged kernel bug a cross-tenant event, and when the workload is spiky, because idle capacity you keep warm for occasional agent runs is pure cost. Buying it means paying a margin to avoid operating a pool, a reconciler and an isolation boundary.
What should I check before committing?
Whether isolation is per-VM or per-container; whether machines are ever reused across customers; whether there is a plan fee or a floor; whether idle sandboxes bill; what the maximum lifetime and concurrency are; whether teardown is guaranteed by the platform or by your code remembering to call delete; and what happens to your data when a sandbox ends. Ask for measured startup numbers rather than marketing ones.
How is this service positioned within that category?
Narrowly, and deliberately. One VM per sandbox, three sizes, one flat hourly rate billed by the second, a small REST API with a filesystem, and an MCP server. No GPUs, no Windows, no persistent workspaces, no published SDKs yet, and a 24 hours maximum lifetime. If your requirements sit outside that, another provider in the category will fit better — the E2B and Daytona comparisons say where.
Evaluate it against your checklist
Every answer above is checkable in the docs. $${SIGNUP_BONUS} of credit lets you verify the rest by running your own workload.