Cloudflare

Agents can now create Cloudflare accounts, buy domains, and deploy

How to enable autonomous agents to programmatically create Cloudflare accounts, purchase domains, and deploy infrastructure without manual dashboard interaction or credential handling.

api-design security
4 min
Cloudflare

Introducing Dynamic Workflows: durable execution that follows the tenant

Enable multi-tenant platforms to execute millions of unique, durable workflows without incurring significant idle infrastructure costs.

distributed-systems microservices
4 min
Cloudflare

Cloudflare Email Service: now in public beta. Ready for your agents

Enabling AI agents to send, receive, and process email natively as a multi-channel communication medium without requiring developers to build custom email infrastructure.

api-design microservices
4 min
Cloudflare

Cloudflare’s AI Platform: an inference layer designed for agents

Developers needed a unified way to access multiple AI model providers without managing separate integrations and API contracts for each one.

api-design microservices
4 min
Cloudflare

How we built Organizations to help enterprises manage Cloudflare at scale

Cloudflare needed to enable enterprise customers to manage multiple accounts and resources under a unified organizational structure with centralized authorization and access control.

api-design security
4 min
Cloudflare

Introducing EmDash — the spiritual successor to WordPress that solves plugin security

WordPress plugins pose significant security risks because they run with unrestricted access to the entire system, requiring a safer plugin architecture that isolates untrusted code.

security microservices
4 min
Cloudflare

From legacy architecture to Cloudflare One

Organizations struggle to migrate from legacy network security architectures to modern SASE (Secure Access Service Edge) solutions, facing risks from accumulated technical debt and complex dependencies in their existing infrastructure.

security microservices
3 min
Cloudflare

Powering the agents: Workers AI now runs large models, starting with Kimi K2.5

Running large AI models for agent workloads on edge infrastructure was cost-prohibitive and required significant inference stack optimization to serve models like Kimi K2.5 efficiently at scale.

ml-systems distributed-systems
4 min