An early-stage, vendor-agnostic Go SDK for managing clusterable, GPU-accelerated compute across cloud providers.

• Define a clean, minimal interface for cloud compute primitives:

  • Instance
  • Storage
  • FirewallRule
  • InstanceType
  • Location

• Enable clusterable GPU workloads across multiple providers, with shared semantics and L3 network guarantees. (WIP)

All cloud integrations must follow our Security Requirements, which define:

• Network Security: Default "deny all inbound, allow all outbound" model
• Cluster Security: Internal instance communication with external isolation
• Data Protection: Encryption requirements for data at rest and in transit
• Implementation Guidelines: Security checklists for cloud provider integrations

See SECURITY.md for complete security specifications and implementation requirements.

• Version: v1 — internal interface, open-sourced
• Current scope: core types + interfaces + tests
• Cloud provider implementations are internal-only for now
• v2 will be shaped by feedback and contributions from the community

• Operating System: Currently supports Ubuntu 22 only
• Architecture: Designed for GPU-accelerated compute workloads
• Access Method: Requires SSH server and SSH key-based authentication
• System Requirements: Requires systemd to be running and accessible

• NVIDIA Cloud Partners (NCPs) looking to offer Brev-compatible GPU compute
• Infra teams building cluster-aware systems or abstractions on raw compute
• Cloud providers interested in contributing to a shared interface for accelerated compute
• Compute brokers & marketplaces (aggregators) offering multi-cloud compute

• V1 Design Notes: Design decisions, known quirks, and AWS-inspired patterns in the v1 API
• Architecture Overview: How the Cloud SDK fits into Brev's overall architecture
• Security Requirements: Security specifications and implementation requirements
• How to Add a Provider: Step-by-step guide to implement a new cloud provider using the Lambda Labs example

This is a foundation — we're opening it early to learn with the community and shape a clean, composable v2. If you're building GPU compute infrastructure or tooling, we'd love your input.