Introduction
On November 19, 2025, a worldwide outage hit the internet. Within minutes, millions of sites became unreachable. The incident, linked to Cloudflare, reminds us how much our digital infrastructure relies on a limited number of actors and critical configurations.
A global incident in a matter of minutes
The outage began around 6 a.m. (U.S. East Coast time). Major services showed errors, platforms like X or ChatGPT became unreachable, and even monitoring tools struggled. The cascading effect was immediate, because Cloudflare plays a central role in DNS, DDoS protection, and traffic management.
Why the impact is so broad
Cloudflare is a transit point for a massive share of global traffic. A single internal degradation is enough to cause global effects.
Root cause: a file that was too large
According to the technical explanations, a configuration change triggered a latent bug in a bot-mitigation service. The automatically generated rules file exceeded an expected size, causing a crash. The protection meant to filter threats ended up disrupting the entire network.
Warning
Automatically generated configuration files can become a critical point of failure if they are not tested with realistic volumes.
Architecture lessons to avoid the domino effect
Outages of this type are not exceptional: they illustrate strong centralization. To limit the damage, systems must be resilient, testable, and able to degrade services in a controlled way.
Key principle
Planning a deliberate degraded mode is often more reliable than a sudden shutdown imposed by a critical dependency.
Operational best practices
Prevention relies on simple guardrails: size limits, integration tests on generated rules, and the ability to roll back within minutes. Here are examples of useful practices and automations.
// Check a config file size before deployment
import fs from "fs";
const MAX_BYTES = 5 * 1024 * 1024;
const path = "./generated-rules.json";
const size = fs.statSync(path).size;
if (size > MAX_BYTES) {
throw new Error("Configuration too large, deployment blocked.");
}
// Degrade a service when errors repeat
let failures = 0;
const MAX_FAILURES = 5;
async function fetchWithFallback(url) {
try {
const res = await fetch(url);
failures = 0;
return res;
} catch (err) {
failures += 1;
if (failures >= MAX_FAILURES) {
return fetch("/cache/offline.json");
}
throw err;
}
}
// Minimal circuit breaker example
let state = "closed";
let openedAt = 0;
const COOLDOWN_MS = 30000;
export async function guardedCall(fn) {
if (state === "open" && Date.now() - openedAt < COOLDOWN_MS) {
throw new Error("Service temporarily disabled");
}
try {
const result = await fn();
state = "closed";
return result;
} catch (err) {
state = "open";
openedAt = Date.now();
throw err;
}
}
// Structured logging to make incident analysis easier
function logIncident(event, meta = {}) {
console.log(JSON.stringify({
event,
severity: "high",
timestamp: new Date().toISOString(),
...meta
}));
}
Warning
Never push a critical configuration without a tested and documented rollback scenario.
Quick checklist
Size limits, load testing, real-time monitoring, and a rollback plan in under 10 minutes.
Conclusion
This outage highlights a simple reality: our internet is centralized. A single faulty configuration is enough to disrupt a large part of the web. The best response remains resilient architecture, tested at scale, and designed for controlled degradation rather than total unavailability.