Best Cloud Infrastructure for AI Agents

Cloud platform providing CDN, DNS, DDoS protection, serverless compute, and developer tools.

AWS is highly capable for agent use with mature SDKs, scoped authentication, and comprehensive REST APIs across all services, but the lack of OpenAPI specs, robots.txt blocking, and service fragmentation create significant discoverability friction. Agents can operate autonomously once configured, but require substantial upfront knowledge to identify and chain the right AWS APIs.

Fastly is well-positioned for agent integration with robust REST API access, multiple SDKs, and a powerful CLI, enabling autonomous authentication and programmatic control of edge computing infrastructure. However, the lack of OpenAPI documentation and event-driven capabilities (webhooks/streaming) represents a notable friction point for fully autonomous AI agent workflows.

Google Cloud offers enterprise-grade REST APIs with excellent auth and reliability, but the massive service portfolio (200+) creates discovery friction and lacks modern AI-agent-friendly patterns like MCP servers or standardized OpenAPI exposure. Strong for agents with pre-configured credentials and specific service knowledge, weaker for autonomous exploration and orchestration.

Upstash provides solid programmatic access through multiple SDKs and REST APIs with good authentication support for autonomous agents, but lacks machine-readable specifications and a formal MCP server that would enable seamless integration. The tool is most suitable for agents that pre-integrate with Upstash SDKs or have access to curated documentation, rather than agents discovering and adapting to APIs dynamically.

Linode is a solid cloud infrastructure provider with mature REST APIs, good SDKs, and scoped authentication, making it agent-accessible for programmatic infrastructure management. However, the lack of OpenAPI specs, MCP servers, and reactive features (webhooks) limits its readiness compared to modern API-first platforms.

DigitalOcean provides good programmatic access through REST APIs and SDKs with autonomous API key authentication, making it suitable for infrastructure automation. However, missing OpenAPI docs, weak reactivity (no webhooks), and lack of explicit dry-run/sandbox features limit agent sophistication and safety.

Vultr is a capable cloud infrastructure provider with solid REST API access and authentication mechanisms suitable for agent use, but lacks modern agent-specific integrations (MCP server, OpenAPI spec, llms.txt) and reactive capabilities that would elevate it to best-in-class agent readiness. Infrastructure management tasks are feasible but require agents to reverse-engineer API patterns rather than rely on machine-readable specifications.

Hetzner provides good programmatic access through REST APIs, SDKs, and CLI tools with API key authentication, making it serviceable for agents managing cloud infrastructure. However, lack of OpenAPI documentation, MCP server support, and webhook/event capabilities significantly limit agent discoverability and real-time responsiveness.

Azure provides solid SDK-based programmatic access and strong authentication mechanisms, making it usable for agents with pre-configured knowledge. However, poor discoverability due to missing OpenAPI specs and lack of MCP server support significantly hinders autonomous exploration and service discovery.

Bunny.net offers solid SDK support (TypeScript, Python) and API key authentication suitable for agent integration, but lacks modern AI-agent onboarding signals like OpenAPI specs, MCP servers, and machine-readable API documentation. The tool is moderately agent-ready for developers who already know the API surface, but discovery and autonomous integration are significantly hindered.