We get asked about why most layer 7 attacks last less than ten minutes more than almost anything else, so here is the long answer.
Lessons for your own runbook
Know who can change DNS at two in the morning. Know your origin IPs and who can rotate them. Know which routes are expensive, and have a rate limit ready for each of them.
Most outages during attacks are not caused by the attack itself but by rushed changes made while under pressure.
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.
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.
Measuring success
We track three numbers for every incident: time to mitigation, the share of attack traffic that reached the origin, and the share of legitimate traffic that was challenged. The first should be under a second, the second under 0.1% and the third under 1%.
Those numbers go into every incident report, and they are the same numbers we are measured against in our SLA.
Testing in production, safely
Every rule starts in log mode. We replay the previous seven days of traffic through it and show exactly which requests it would have affected before anyone can promote it to challenge or block.
This one feature has prevented more incidents than any detection we have ever shipped.
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.
{ "match": { "path": "/login", "risk": ">= 36" }, "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.
Thanks — sharing this with our on-call team.