惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

爱范儿
爱范儿
E
Exploit-DB.com RSS Feed
Google DeepMind News
Google DeepMind News
F
Full Disclosure
D
Darknet – Hacking Tools, Hacker News & Cyber Security
T
ThreatConnect
Stack Overflow Blog
Stack Overflow Blog
Last Week in AI
Last Week in AI
Martin Fowler
Martin Fowler
G
GRAHAM CLULEY
C
Check Point Blog
T
Threatpost
I
Intezer
Spread Privacy
Spread Privacy
The Register - Security
The Register - Security
Project Zero
Project Zero
月光博客
月光博客
人人都是产品经理
人人都是产品经理
阮一峰的网络日志
阮一峰的网络日志
D
DataBreaches.Net
IT之家
IT之家
Malwarebytes
Malwarebytes
T
The Blog of Author Tim Ferriss
P
Privacy International News Feed
P
Palo Alto Networks Blog
T
The Exploit Database - CXSecurity.com
量子位
李成银的技术随笔
Threat Intelligence Blog | Flashpoint
Threat Intelligence Blog | Flashpoint
Cisco Talos Blog
Cisco Talos Blog
Know Your Adversary
Know Your Adversary
美团技术团队
The GitHub Blog
The GitHub Blog
T
Tor Project blog
M
MIT News - Artificial intelligence
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
Google Online Security Blog
Google Online Security Blog
P
Proofpoint News Feed
有赞技术团队
有赞技术团队
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
博客园 - 司徒正美
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
C
Comments on: Blog
T
Threat Research - Cisco Blogs
aimingoo的专栏
aimingoo的专栏
Security Latest
Security Latest
NISL@THU
NISL@THU
The Cloudflare Blog
H
Help Net Security
Recent Commits to openclaw:main
Recent Commits to openclaw:main

The Cloudflare Blog

The day my ping took countermeasures Announcing Claude Compliance API support with Cloudflare CASB Announcing Claude Managed Agents on Cloudflare Project Glasswing: what Mythos showed us Our billing pipeline was suddenly slow. The culprit was a hidden bottleneck in ClickHouse Browser Run: now running on Cloudflare Containers, it’s faster and more scalable When "idle" isn't idle: how a Linux kernel optimization became a QUIC bug Building For The Future How Cloudflare responded to the “Copy Fail” Linux vulnerability When DNSSEC goes wrong: how we responded to the .de TLD outage Code Orange: Fail Small is complete. The result is a stronger Cloudflare network Introducing Dynamic Workflows: durable execution that follows the tenant Post-quantum encryption for Cloudflare IPsec is generally available Agents can now create Cloudflare accounts, buy domains, and deploy Shutdowns, power outages, and conflict: a review of Q1 2026 Internet disruptions Making Rust Workers reliable: panic and abort recovery in wasm‑bindgen Moving past bots vs. humans Building the agentic cloud: everything we launched during Agents Week 2026 The AI engineering stack we built internally — on the platform we ship Orchestrating AI Code Review at scale Introducing the Agent Readiness score. Check to see if your site is agent-ready Shared Dictionaries: compression that keeps up with the agentic web Redirects for AI Training enforces canonical content Unweight: how we compressed an LLM 22% without sacrificing quality Agents that remember: introducing Agent Memory Agents Week: network performance update Introducing Flagship: feature flags built for the age of AI Cloudflare’s AI Platform: an inference layer designed for agents Building the foundation for running extra-large language models AI Search: the search primitive for your agents Deploy Postgres and MySQL databases with PlanetScale + Workers Artifacts: versioned storage that speaks Git Email for agents - Cloudflare Email Service now in public beta Project Think: building the next generation of AI agents on Cloudflare Introducing Agent Lee - a new interface to the Cloudflare stack Register domains wherever you build: Cloudflare Registrar API now in beta Browser Run: give your agents a browser Rearchitecting the Workflows control plane for the agentic era Add voice to your agent Managed OAuth for Access: make internal apps agent-ready in one click Securing non-human identities: automated revocation, OAuth, and scoped permissions Scaling MCP adoption: Our reference architecture for simpler, safer and cheaper enterprise deployments of MCP Secure private networking for everyone: users, nodes, agents, Workers — introducing Cloudflare Mesh Building a CLI for all of Cloudflare Durable Objects in Dynamic Workers: Give each AI-generated app its own database Agents have their own computers with Sandboxes GA Dynamic, identity-aware, and secure Sandbox auth Welcome to Agents Week 500 Tbps of capacity: 16 years of scaling our global network From bytecode to bytes- automated magic packet generation Cloudflare targets 2029 for full post-quantum security How we built Organizations to help enterprises manage Cloudflare at scale Why we're rethinking cache for the AI era Our ongoing commitment to privacy for the 1.1.1.1 public DNS resolver Introducing EmDash — the spiritual successor to WordPress that solves plugin security Introducing Programmable Flow Protection: custom DDoS mitigation logic for Magic Transit customers Cloudflare Client-Side Security: smarter detection, now open to everyone How we use Abstract Syntax Trees (ASTs) to turn Workflows code into visual diagrams A one-line Kubernetes fix that saved 600 hours a year Sandboxing AI agents, 100x faster Inside Gen 13- how we built our most powerful server yet Launching Cloudflare’s Gen 13 servers- trading cache for cores for 2x edge compute performance Powering the agents: Workers AI now runs large models, starting with Kimi K2.5 Introducing Custom Regions for precision data control Standing up for the open Internet- why we appealed Italy’s Piracy Shield fine From legacy architecture to Cloudflare One Announcing Cloudflare Account Abuse Protection: prevent fraudulent attacks from bots and humans Slashing agent token costs by 98% with RFC 9457-compliant error responses AI Security for Apps is now generally available Building a security overview dashboard for actionable insights Investigating multi-vector attacks in Log Explorer Translating risk insights into actionable protection: leveling up security posture with Cloudflare and Mastercard Fixing request smuggling vulnerabilities in Pingora OSS deployments Active defense: introducing a stateful vulnerability scanner for APIs Complexity is a choice. SASE migrations shouldn’t take years. From the endpoint to the prompt: a unified data security vision in Cloudflare One Ending the "silent drop": how Dynamic Path MTU Discovery makes the Cloudflare One Client more resilient A QUICker SASE client: re-building Proxy Mode How Automatic Return Routing solves IP overlap Always-on detections: eliminating the WAF “log versus block” trade-off Mind the gap: new tools for continuous enforcement from boot to login Stop reacting to breaches and start preventing them with User Risk Scoring Defeating the deepfake: stopping laptop farms and insider threats Moving from license plates to badges: the Gateway Authorization Proxy Evolving Cloudflare’s Threat Intelligence Platform: actionable, scalable, and ETL-less Introducing the 2026 Cloudflare Threat Report See risk, fix risk: introducing Remediation in Cloudflare CASB How Cloudy translates complex security into human action From reactive to proactive: closing the phishing gap with LLMs Modernizing with agile SASE: a Cloudflare One blog takeover Beyond the blank slate: how Cloudflare accelerates your Zero Trust journey The truly programmable SASE platform Toxic combinations: when small signals add up to a security incident We deserve a better streams API for JavaScript The most-seen UI on the Internet? Redesigning Turnstile and Challenge Pages ASPA: making Internet routing more secure Bringing more transparency to post-quantum usage, encrypted messaging, and routing security How we rebuilt Next.js with AI in one week Cloudflare One is the first SASE offering modern post-quantum encryption across the full platform Cloudflare outage on February 20, 2026
Enhancing the Optimizely Experimentation Platform with Cloudflare Workers
Cloudflare T · 2019-06-05 · via The Cloudflare Blog

Enhancing the Optimizely Experimentation Platform with Cloudflare Workers

2019-06-05

4 min read

This is a joint post by Whelan Boyd, Senior Product Manager at Optimizely and Remy Guercio, Product Marketing Manager for Cloudflare Workers.

Experimentation is an important ingredient in driving business growth: whether you’re iterating on a product or testing new messaging, there’s no substitute for the data and insights gathered from conducting rigorous experiments in the wild.

Optimizely is the world’s leading experimentation platform, with thousands of customers worldwide running tests for over 140 million visitors daily. If Optimizely were a website, it would be the third most trafficked in the US.  And when it came time to experiment with reinvigorating their own platform, Optimizely chose Cloudflare Workers.

Improving Performance and Agility with Cloudflare Workers

Cloudflare Workers is a globally distributed serverless compute platform that runs across Cloudflare’s network of 180 locations worldwide. Workers are designed for flexibility, with many different use cases ranging from customizing configuration of Cloudflare services and features to building full, independent applications.

In this post, we’re going to focus on how Workers can be used to improve performance and increase agility for more complex applications. One of the key benefits of Workers is that they allow developers to move decision logic and data into a highly efficient runtime operating in close proximity to end users — resulting in significant performance benefits and flexibility. Which brings us to Optimizely...

How Optimizely Works

Every week Optimizely delivers billions of experiences to help teams A/B test new products, de-risk new feature launches, and validate alternative designs. Optimizely lets companies test client-side changes like layouts and copy, as well as server-side changes like algorithms and feature rollouts.

Let’s explore how both have challenges that can be overcome with Workers, starting with Optimizely’s client-side A/B testing, or Optimizely Web, product.

Use Case: Optimizely Web

The main benefit of Optimizely Web — Optimizely’s client-side testing framework — is that it supports A/B testing via straightforward insertion of a JavaScript tag on the web page. The test is designed via the Optimizely WYSIWYG editor, and is live within minutes. Common use cases include style updates, image swaps, headlines and other text changes. You can also write any custom JavaScript or CSS you want.

With client-side A/B testing, the browser downloads JavaScript that modifies the page as it’s loading.  To avoid “flash-of-unstyled-content” (FOUC), developers need to implement this JavaScript synchronously in their tag.  This constraint, though, can lead to page performance issues, especially on slower connections and devices.  Downloading and executing JavaScript in the browser has a cost, and this cost increases if the amount of JavaScript is large.  With a normal Optimizely Web implementation, all experiments are included in the JavaScript loaded on every page.

A traditional Optimizely implementation

With Workers, Optimizely can support many of these same use cases, but hoists critical logic to the edge to avoid much of the performance cost. Here’s how it works:

Implementing tests with Optimizely and Cloudflare Workers

This diagram shows how Optimizely customers can execute experiments created in the point-and-click UI through a Cloudflare Worker.  Rather than the browser downloading a large JavaScript file, your Worker handling HTTP/S requests calls out to Optimizely’s Worker.  Optimizely’s Worker determines which A/B tests should be active on this page and returns a small amount of JavaScript back to your Worker.  In fact, it is the JavaScript required to execute A/B test variations on just that specific page load.  Your Worker inlines the code in the page and returns it to the visitor’s browser.  

Not only does this avoid a browser bottleneck downloading a lot of data, the amount of code to execute is a fraction of a normal client-side implementation.  Since the experiments are set up inside the Optimizely interface just like any other Web experiment, you can run as many as you want without waiting for code deploy cycles.  Better yet, your non-technical (e.g. marketing) teams can still run these without depending on developers for each test.  It’s a one-time implementation.

Use Case: Going Further with Feature Rollouts

Optimizely Full Stack is Optimizely’s server-side experimentation and feature flagging platform for websites, mobile apps, chatbots, APIs, smart devices, and anything else with a network connection.  You can deploy code behind feature flags, experiment with A/B tests, and roll out or roll back features immediately.  Optimizely Rollouts is a free version of Full Stack that supports key feature rollout capabilities.

Full Stack SDKs are often implemented and instantiated directly in application code.

An Optimizely full stack experimentation setup

The main blocker to high velocity server-side testing is that experiments and feature rollouts must go through the code-deploy cycle — and to further add to the headache, many sites cache content on CDNs, so experiments or rollouts running at the origin never execute.  

In this example, we’ll consider a new feature you’d like to roll out gradually, exposing more and more users over time between code deploys. With Workers, you can implement feature rollouts by running the Optimizely JavaScript SDK at the edge.  The Worker is effectively a decision service.  Instead of installing the JS SDK inside each application service where you might need to gate or roll out features, centralize instantiation in a Worker.

From your application, simply hit the Worker and the response will tell you whether a feature is enabled for that particular user.  In the example below, we supply via query parameters a userId, feature, and account-specific SDK key and the Worker responds with its decision in result.  Below is a sample Cloudflare Worker:

import { createManager } from '../index'

/// <reference lib="es2015" />
/// <reference lib="webworker" />

addEventListener('fetch', (event: any) => {
  event.respondWith(handleRequest(event.request))
})

/**
 * Fetch and log a request
 * @param {Request} request
 */
async function handleRequest(request: Request): Promise<Response> {
  const url = new URL(request.url)
  const key = url.searchParams.get('key')
  const userId = url.searchParams.get('userId')
  const feature = url.searchParams.get('feature')
  if (!feature || !key || !userId) {
    throw new Error('must supply "feature", "userId" and "key"')
  }

  try {
    const manager = createManager({
      sdkKey: key,
    })

    await manager.onReady().catch(err => {
      return new Response(JSON.stringify({ status: 'error' }))
    })
    const client = manager.getClient()

    const result = await client.feature({
      key: feature,
      userId,
    })

    return new Response(JSON.stringify(result))
  } catch (e) {
    return new Response(JSON.stringify({ status: 'error' }))
  }
}

This kind of setup is common for React applications, which may update store values based on decisions returned by the Worker. No need to force a request all the way back to origin.

All in all, using Workers as a centralized decision service can reduce the complexity of your Full Stack implementation and support applications that rely on heavy caching.

How to Improve Your Experimentation Setup

Both of the examples above demonstrate how Workers can provide speed and flexibility to experimentation and feature flagging.  But this is just the tip of the iceberg!  There are plenty of other ways you can use these two technologies together. We’d love to hear from you and explore them together!

Are you a developer looking for a feature flagging or server-side testing solution? The Optimizely Rollouts product is free and ready for you to sign up!

Or does your marketing team need a high performance A/B testing solution? The Optimizely Web use case is in developer preview.

  • Cloudflare Enterprise Customers: Reach out to your dedicated Cloudflare account manager learn more and start the process.

  • Optimizely Customers and Cloudflare Customers (who aren’t on an enterprise plan): Reach out to your Optimizely contact to learn more and start the process.

You can sign up for and learn more about using Cloudflare Workers here!

ServerlessCloudflare WorkersJavaScriptDevelopersDeveloper Platform