Developers

We are launching Workers Cache, a regionally tiered cache that sits directly in front of your Worker entrypoints. Infinitely composable, configured via standard HTTP headers

Dan Lapid and Connor Harwood

Cloudflare Workflows, our durable execution engine for multi-step applications, now supports saga-style rollbacks, allowing developers to specify a compensating action for each step.do().

Vaishnav Kavitha, Mia Malden, and André Venceslau

Self-Managed OAuth is now available to all developers on Cloudflare. Here's how we executed a zero-downtime migration of our core OAuth engine to make it happen.

Sam Cabell, Mike Escalante, Adam Bouhmad, and Nick Comer

By rearchitecting the Images binding, we accidentally uncovered a bug that existed in the open-source hyper library across multiple major versions.

Deanna Lam, Diretnan Domnan, and Matt Lewis

The Agents SDK is now a runtime any agent framework can build on. Today we're opening up the Agents SDK primitives, with Flue as a first framework targeting Agents SDK, and rolling out agents in the dashboard

Thomas Gauvin

AI Gateway now features real-time spend limits to prevent runaway token bills across multiple AI providers. By integrating with Cloudflare Access, companies can use identity-driven budgets and policies.

Ming Lu and Kenny Johnson

VoidZero, the team behind Vite, Vitest, Rolldown, Oxc, and Vite+, is joining Cloudflare. Vite stays open source, vendor-agnostic, and built for everyone.

Evan You and Steve Faulkner

Cloudflare now integrates with the Claude Compliance API, so that security teams can monitor Claude Enterprise activity directly in the Cloudflare Dashboard.

Abe Carryl

We’ve enabled higher usage limits, faster performance, better reliability, and increased shipping velocity for our Browser Run product by rebuilding on top of Cloudflare’s Containers. Here’s how.

Ruskin Constant, Rui Figueira, and Sofia Cardita

Dynamic Workflows is a library that lets you route durable execution to tenant-provided code on the fly. Built on Dynamic Workers, it enables platforms to serve millions of unique workflows at near-zero idle cost.

Dan Lapid and Luís Duarte

Panics in Rust Workers were historically fatal, poisoning the entire instance. By collaborating upstream on the wasm‑bindgen project, Rust Workers now support resilient critical error recovery, including panic unwinding using WebAssembly Exception Handling.

Guy Bedford, Hood Chatham, and Logan Gatlin

Learn about how we built a CI-native AI code reviewer using OpenCode that helps our engineers ship better, safer code.

Ryan Skidmore

We built our internal AI engineering stack on the same products we ship. That means 20 million requests routed through AI Gateway, 241 billion tokens processed, and inference running on Workers AI, serving more than 3,683 internal users. Here's how we did it.

Ayush Thakur, Scott Roe-Meschke, and Rajesh Bhatia

Agents Week 2026 is a wrap. Let’s take a look at everything we announced, from compute and security to the agent toolbox, platform tools, and the emerging agentic web. Everything we shipped for the agentic cloud.

Ming Lu and Anni Wang

Soft directives don’t stop crawlers from ingesting deprecated content. Redirects for AI Training allows anybody on Cloudflare to redirect verified crawlers to canonical pages with one toggle and no origin changes.

Cam Whiteside, David Belson, and André Cruz

We're building AI Gateway into a unified inference layer for AI, letting developers call models from 14+ providers. New features include Workers AI binding integration and an expanded catalog with multimodal models.

Ming Lu and Michelle Chen

Agents are becoming multi-channel. That means making them available wherever your users already are — including the inbox. Today, Cloudflare Email Service enters public beta with the infrastructure layer to make that easy: send, receive, and process email natively from your agents.

Thomas Gauvin and Eric Falcão

We built a custom technology stack to run fast large language models on Cloudflare’s infrastructure. This post explores the engineering trade-offs and technical optimizations required to make high-performance AI inference accessible.

Michelle Chen, Kevin Flansburg, and Vlad Krasnov