how we deploy rule changes to every edge in under 30 seconds sounds like a narrow topic. It turns out to touch almost every part of how an edge network behaves under attack.
Compliance is a side effect
Regulators increasingly ask for evidence of resilience, not just promises. An incident timeline with start, peak, vectors and impact is exactly the evidence DORA and NIS2 ask for — and it falls out of good observability for free.
We export incident reports in formats auditors can file without anyone rewriting them.
Protecting the origin
None of this matters if the attacker can reach your origin directly. Historical DNS records, certificate transparency logs and misconfigured subdomains leak origin addresses all the time.
Allow-list the edge ranges, enable authenticated origin pulls and treat any origin IP that ever appeared in public DNS as burned.
The economics behind it
A booter service rents out a 100 Gbps attack for less than the price of a pizza. Defending against it with bandwidth alone is a race you lose. Defending against it by making each malicious request cost more than it earns is a race you win.
This is the entire idea behind never metering attack traffic: our costs scale with filtering, not with your invoice.
Challenges beat blocks
Blocking lists go stale within minutes when attackers rotate through residential proxies. Proof-of-work does not care where a request comes from; it only cares whether the client is willing to pay the cost.
For a real browser that cost is a few hundred milliseconds, once per session. For a botnet sending a million requests a minute it is a million puzzles a minute — and at that point the attack stops being cheap.
The numbers
Across the last quarter, 71% of challenged clients never attempted a solution, 24% solved one challenge and then behaved normally, and 5% solved challenges repeatedly while continuing to attack — the last group is where analysts spend their time.
Median added latency for legitimate visitors that were challenged was 280 ms on desktop and 410 ms on mid-range Android devices.
Latency budget
Our budget for the whole filtering pipeline is one millisecond at the 99th percentile. Anything that cannot be decided within that budget runs asynchronously and influences the next request from the same client, not the current one.
That constraint shapes everything: data structures, where state lives and which signals we are willing to compute inline.
What actually happens during a flood
The first thing to fail during a layer 7 flood is almost never bandwidth. It is connection slots, worker processes or database connections on the origin — resources measured in hundreds or thousands, not gigabits. An attacker who can make each request expensive only needs a few thousand requests per second.
That is why we score requests before they are proxied. By the time a request reaches your origin, it has been attributed to a client, compared against that client’s history and weighed against the current load on the route it targets.
{ "match": { "path": "/login", "risk": ">= 40" }, "action": "challenge" }
If you run into any of this in your own environment, our SOC is happy to take a look — even if you are not a customer.