What is a MicroVM sandbox?
A MicroVM sandbox is a lightweight virtual machine backed by a hypervisor such as Cloud-Hypervisor and designed to start in milliseconds and run a single workload in hardware-isolated form. Unlike containers, each MicroVM has its own kernel, which makes them safer for running untrusted or AI-generated code. They’re commonly used for AI agents, code execution, serverless functions, and CI/build workloads. CPU-only Tensorlake sandboxes are MicroVMs.What are Tensorlake Sandboxes?
Tensorlake Sandboxes are isolated MicroVMs that boot in hundreds of milliseconds, with memory and filesystem preserved across suspend and resume. You can use them to run agent harnesses, execute tool calls, or as VMs for coding agents, builds, and IDEs.How are Tensorlake Sandboxes isolated?
Each CPU-only sandbox is a MicroVM backed by Cloud-Hypervisor. Sandboxes provide hardware-level isolation rather than container-level isolation, so untrusted or AI-generated code can run safely without sharing a kernel with other workloads.How fast does a Tensorlake Sandbox start?
Tensorlake creates a fresh sandbox in single-digit milliseconds; OS boot then completes in a few hundred milliseconds. At peak load, the scheduler creates hundreds of sandboxes per second. See Architecture for how this differs from Kubernetes pod creation.How do I create a Tensorlake Sandbox?
Create one on demand from the CLI or the SDK. Passimage, cpus, and memory to control the runtime.
What can I run inside a Tensorlake Sandbox?
Anything the OS supports. Common workloads include:- Agent harnesses and tool calls
- LLM-generated or untrusted code
- Browser automation and computer use
- Builds, tests, and CI workloads
- Long-running processes and PTY sessions
- Networking and tunnels
Is Tensorlake compliant with HIPAA and SOC 2?
Yes. Tensorlake is HIPAA and SOC 2 Type II compliant, supports EU data residency, and offers zero data retention.How are Tensorlake Sandboxes different from Docker containers?
CPU-only Tensorlake sandboxes are MicroVMs, which means each sandbox has its own kernel and hardware-level isolation. Docker containers share the host kernel: faster to start, but weaker isolation for running untrusted or AI-generated code. Tensorlake also provides built-in suspend/resume and snapshots, which aren’t part of the standard Docker runtime. If you have an existing Dockerfile, Tensorlake can build a sandbox image from it. See Build and Import Images.Why would I use a sandbox if agents can already run on my laptop?
A laptop works for developing agents and running one or two interactively. It becomes the bottleneck when agents need to run unattended, in parallel, or against untrusted code:- Isolation: an agent that installs packages, modifies files, or runs LLM-generated code does it inside its own MicroVM, not on your machine.
- Persistence: sandbox state (filesystem and memory) survives suspend and resume, so long-running work doesn’t depend on your laptop staying open.
- Reproducibility: each sandbox starts from a defined image, not from whatever happens to be installed locally.
- Snapshot and fork: checkpoint an agent’s environment and fork parallel workers from it, which a single machine can’t do.
- Scale: going from one agent to dozens means creating more sandboxes, not buying more hardware.
How is Tensorlake different from running Claude Code with git worktrees?
Git worktrees let you check out several branches of a repository side by side, so a coding agent like Claude Code can work on multiple tasks at once on your machine. The isolation is at the source-code level: every worktree shares your laptop’s OS, dependencies, processes, and network. Tensorlake Sandboxes isolate the entire execution environment. Each sandbox is a MicroVM with its own filesystem, processes, and dependencies, and can be suspended, resumed, snapshotted, and forked independently, and it keeps running when your laptop doesn’t. In short:- Worktrees isolate source code.
- Sandboxes isolate entire execution environments.