ConTree Documentation

Sandboxes That Branch Like Git

ConTree is a cloud-based sandbox API by Nebius that enables secure code execution with Git-like branching capabilities. Perfect for AI agents that need to explore multiple execution paths, evaluate outcomes, and backtrack when necessary.

Contents

Overview

ConTree combines VM-level isolation with container efficiency, providing a secure environment for executing untrusted code. Unlike traditional containers, ConTree supports Git-like branching — fork from any checkpoint, run parallel explorations, and roll back instantly.

Key Features

Secure Isolation

VM-level isolation ensures untrusted code cannot escape the sandbox or affect other workloads.

Git-like Branching

Fork execution state at any checkpoint. Explore multiple solution paths in parallel, then score results and expand the best branches.

Instant Rollback

Return to any previous state with a single API call. No need to rebuild or re-execute from scratch.

OCI Image Support

Import images from any OCI-compliant registry (Docker Hub, GHCR, etc.). Use your existing container images as sandbox bases.

Resource Metrics

Built-in tracking of CPU time, memory usage, and I/O operations for every execution.

Async Operations

All long-running operations (image imports, executions) are async with polling support and cancellation.

Quick Start

  1. Choose a base state. Start from a preloaded environment, a previously produced checkpoint, or an imported OCI image.

  2. Make inputs explicit. Attach the files and runtime assumptions the command needs so the run can be replayed later.

  3. Start an execution. Run code inside the sandbox from the chosen state. Long-running work is represented as an operation.

  4. Wait for the operation. Poll through the CLI, SDK, or generated client until execution reaches a terminal state.

  5. Inspect the resulting checkpoint. Read logs, metrics, files, and artifacts from the state produced by the run.

  6. Branch when needed. Fork from any useful checkpoint to try alternatives, compare outcomes, and continue from the best branch.

Use Cases

AI Coding Agents

Let AI agents execute and test code safely. Branch to explore multiple approaches, evaluate results, and continue the most promising path.

Research & Experimentation

Run experiments in isolated environments. Fork state to test variations without starting over.

Educational Platforms

Provide students with safe code execution environments. Automatic cleanup and resource limits prevent abuse.

CI/CD Pipelines

Execute build steps and tests in isolated sandboxes with full resource tracking and artifact retrieval.

Resources