Build fluency in the vocabulary of detecting and filtering a malicious traffic flood before it hits the origin.
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At standup, a dev mentions a service designed specifically to detect and filter a flood of malicious traffic before it ever overwhelms the origin servers behind it. What is this practice called?
DDoS mitigation detects and filters a flood of malicious traffic before it ever overwhelms the origin servers behind it, typically through a dedicated scrubbing layer sitting in front of the actual application. Autoscaling the origin's own capacity adds more servers but does nothing to filter out the malicious traffic itself, so a large enough attack can still overwhelm even an autoscaled fleet. This dedicated filtering is what protects an origin from a volumetric or application-layer flood that autoscaling alone can't absorb.
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During a design review, the team wants a volumetric flood of traffic to be absorbed across many geographically distributed edge locations instead of concentrating entirely on one origin data center. Which capability supports this?
Anycast routing distributes a volumetric flood of attack traffic across many geographically distributed edge locations, so no single origin data center bears the full brunt of the attack. Routing every request to a single fixed origin, with no distribution, concentrates the full force of an attack on one location, which is exactly what a volumetric DDoS attack is designed to overwhelm. This distribution across many edge locations is a core technique behind how a large-scale DDoS mitigation service absorbs a massive attack.
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In a code review, a dev notices a mitigation system maintains a rolling baseline of normal traffic patterns for a given endpoint, so it can flag a sudden deviation as a likely attack rather than a genuine traffic surge. What does this represent?
Traffic-pattern baselining maintains a rolling picture of what normal traffic looks like for a given endpoint, letting the mitigation system flag a sudden deviation as a likely attack rather than simply a legitimate surge, like a marketing campaign driving real demand. Treating every sudden increase identically, with no baseline, risks either missing a genuine attack or blocking real customers during a legitimate spike. This baselining is what lets an automated mitigation system make that distinction quickly enough to matter during an active attack.
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An incident report shows an origin's application servers became completely unresponsive during an attack because all incoming traffic, malicious and legitimate alike, reached the origin directly with no scrubbing layer in front of it. What practice would prevent this?
Routing traffic through a dedicated DDoS mitigation layer filters malicious traffic before it ever reaches the origin, keeping the application servers responsive to genuine customer requests even during an active attack. Continuing to route all traffic directly to the origin with no scrubbing layer is exactly what left the origin completely unresponsive in this incident. This front-line filtering is a standard architectural safeguard for any public-facing service at meaningful risk of a volumetric attack.
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During a PR review, a teammate asks why the team routes traffic through a dedicated DDoS mitigation service instead of just autoscaling the origin to absorb a larger volume of traffic on its own. What is the reasoning?
Autoscaling adds more origin capacity but does nothing to filter out malicious traffic itself, so a sufficiently large attack can still overwhelm even a heavily autoscaled origin, and autoscaling that much capacity purely to absorb an attack is also extremely costly. A dedicated mitigation layer can filter and absorb an attack at a scale far beyond what any single origin could reasonably provision for. The tradeoff is the added dependency on, and cost of, running traffic through that dedicated mitigation service continuously.
What does the "DDoS Mitigation Vocabulary" vocabulary exercise cover?
This exercise tests real IT vocabulary related to ddos mitigation vocabulary through 5 multiple-choice questions, each built from realistic workplace sentences rather than abstract definitions.
Is this vocabulary exercise free to use?
Yes. Every exercise on CoderSlingo, including this one, is completely free — no account, sign-up, or payment required.
How many questions does this exercise have?
This exercise has 5 questions. Each one shows a real-world sentence or scenario with multiple-choice options and an explanation once you answer.
What happens after I answer a question?
You'll see immediate feedback showing whether your answer was correct, along with a short explanation of why — then a button to move to the next question, and a full results screen at the end.
Can I retry the exercise if I get questions wrong?
Yes. Once you reach the results screen, click "Try again" to reset your answers and go through the exercise from the start as many times as you like.
Do I need to create an account to take this exercise?
No account is needed. Your answers are scored in your browser during the session — nothing is saved to a server, so you can jump straight in.
Is my progress saved if I leave the page?
No — progress within an exercise resets if you navigate away or reload. Each exercise is short enough to complete in a few minutes in one sitting.
Are these vocabulary exercises connected to other topics?
Yes — this module shares real-world context with 14 other vocabulary modules. See "Related vocabulary" below to keep building a connected skill set.
How is this different from reading a glossary or blog article?
Exercises like this one are active recall drills — you have to choose the correct term or phrasing yourself, which builds retention faster than passively reading a definition.
Where can I find more vocabulary exercises?
Browse the full Vocabulary exercises hub for hundreds of modules covering Agile, DevOps, security, databases, architecture, and more — organised by IT role and skill.