Open-source cloud infrastructure providing secure sandboxes for AI agents to run code in isolated environments. Sandboxes start in 80ms and support Python, JavaScript, Ruby, and C++ on Linux.

Open-source virtualization technology from AWS that powers secure sandboxes for AI agents with hardware-level isolation. Used by E2B and other sandbox platforms.

Architectural patterns for isolating and managing data for multiple customers (tenants) in shared vector database infrastructure. Multi-tenancy strategies include namespace isolation, metadata filtering, and separate collections, each offering different trade-offs between performance, cost, and data isolation.

Architectural patterns for isolating data between different tenants (customers/organizations) in vector databases. Includes collection-per-tenant, partition-per-tenant, and filter-based approaches with different trade-offs.

Strategies for deleting and updating vectors in production systems including soft deletes, versioning, and rebuild patterns. Critical for maintaining data accuracy and handling GDPR/compliance requirements.