E2B

Isolated cloud machines for AI agents to run code, browse, use tools, and execute tasks at scale.

Overview

E2B is a cloud platform that provides isolated microVMs for AI agents to run in production. Each agent gets its own dedicated machine with a full Linux environment, enabling agents to execute code, control networks, access storage, and use tools safely and at scale.

The platform supports any agent framework or model—from OpenAI and Anthropic to custom implementations—and offers flexible deployment options: E2B's managed cloud (US, EU, APAC), or bring-your-own-cloud (BYOC) on AWS, GCP, or Azure. With 100K+ teams and over 1 billion sandboxes started, E2B is built for production AI workloads including coding agents, computer-use automation, reinforcement learning, and data analysis.

E2B's runtime is open-source (Apache-2.0) and battle-tested for security and compliance, with SOC 2 Type II and HIPAA certification. Pricing is usage-based, billed per second of sandbox runtime, with a free tier offering $100 in credits.

Key features

Isolated microVMs per agent session with full Linux environment
Code execution, browser control, filesystem, and networking
Snapshot-based boot for fast startup times
Pause, resume, fork, and snapshot lifecycle management
Support for any AI model and agent framework
Managed cloud or bring-your-own-cloud (BYOC) deployment
SOC 2 Type II and HIPAA compliance
200+ MCP tool servers available
Secrets vault and environment variable scoping
Real-time metrics, logs, and webhooks

Pros

Production-ready with 1B+ sandboxes started and 94 Fortune 100 customers
Flexible deployment: managed cloud or BYOC on AWS/GCP/Azure
Open-source runtime (Apache-2.0) for transparency and self-hosting
Fast startup via snapshot-based booting
Comprehensive security: full isolation, SOC 2 Type II, HIPAA
Usage-based pricing with free tier and no lock-in
Works with any agent framework and model

Cons

Requires understanding of microVM and sandbox concepts for optimal use
Enterprise tier requires $3,000/month minimum commitment
BYOC deployment adds operational complexity
Learning curve for advanced features like custom compute configurations

Use this if

You need to run AI agents in isolated, secure compute environments; you're building production agent applications; you require compliance certifications; or you want flexible deployment options.

Skip this if

You're building simple chatbots without code execution; you need a fully managed solution without any infrastructure concerns; or you require on-premises deployment without cloud options.

Best for

Running AI agents that need isolated compute environmentsExecuting untrusted code safely at scaleBuilding coding and computer-use agentsReinforcement learning and agent trainingEnterprise deployments with compliance requirementsMulti-tenant SaaS applications with agent workloads

Alternatives

Replit (code execution environment)Modal (serverless compute)AWS Lambda (general-purpose serverless)Hugging Face Spaces (ML model hosting)Anthropic's Claude API (agent framework)

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