Distributed Denial of Service (DDoS) attacks continue to evolve in both scale and complexity. For developers and infrastructure operators running public-facing services—especially game servers and APIs—basic firewall rules are no longer sufficient. This article outlines a practical approach to building a high-performance mitigation pipeline using Linux-native technologies such as nftables and XDP. The concepts presented here are based on real-world implementations used at ArzenLabs. Typical attack patterns observed in production environments include: High packet-rate UDP floods targeting open service portsAmplification attacks using spoofed sourcesBurst traffic designed to exhaust connection tracking These attacks aim to overwhelm network handling capacity rather than exploit application logic. Architecture Overview An effective mitigation pipeline should operate across multiple layers: Early packet drop (XDP / eBPF)Kernel-level filtering (nftables)Dynamic reputation-based blockingUpstream filtering (provider-level) Each layer reduces load progressively, ensuring system stability under attack conditions. Layer 1: Early Drop with XDP XDP (eXpress Data Path) allows packet filtering at the NIC level, before the kernel network stack is fully engaged. Example ConceptDrop invalid or malformed packets immediatelyFilter obvious flood patterns before conntrack involvement if (udp_packet && packet_rate_exceeds_threshold) { return XDP_DROP;}Why XDP MattersExtremely low latency filteringPrevents CPU exhaustionHandles high packet-per-second (PPS) attacks efficientlyLayer 2: nftables Rate Limiting After initial filtering, nftables can enforce structured rules. Basic Rate Limit Rulenft add table inet ddosnft add chain inet ddos input { type filter hook input priority 0 \; } nft add rule inet ddos input udp dport 25565 limit rate 300/second burst 600 packets acceptnft add rule inet ddos input udp dport 25565 dropKey BehaviorAccepts normal traffic within defined thresholdsDrops excessive packets automaticallyReduces impact of volumetric floodsLayer 3: Dynamic Blacklisting Static rules are insufficient against distributed attacks. A dynamic system is required. Example Setupnft add set inet ddos blacklist { type ipv4_addr\; flags timeout\; } nft add rule inet ddos input ip saddr @blacklist dropLogicDetect abusive IPs based on rate thresholdsAdd them to a temporary blacklistAutomatically expire entries after timeoutLayer 4: Upstream Mitigation Local filtering alone cannot handle large-scale attacks. Upstream protection is essential. Typical strategies include: Provider-level firewallsTraffic scrubbing centersAnycast-based distribution This layer absorbs the bulk of volumetric attacks before they reach the server. Performance Considerations When designing mitigation systems, consider: Packet-per-second (PPS) limits rather than bandwidth aloneCPU overhead of filtering rulesImpact of conntrack on high-volume UDP traffic Optimizing early-drop mechanisms significantly improves system resilience. Common MistakesRelying solely on iptables without rate limitingEnabling conntrack for all UDP trafficNot isolating backend services from direct exposureIgnoring monitoring and observabilityPractical Outcome A properly designed pipeline: Reduces attack surface significantlyMaintains service availability under loadMinimizes latency impact for legitimate usersConclusion DDoS mitigation is not achieved through a single tool or rule set. It requires a layered architecture that combines early packet filtering, kernel-level enforcement, and upstream protection. The approach outlined here reflects how modern infrastructure teams build resilient systems capable of handling high-volume attacks in production environments. At ArzenLabs, the focus remains on engineering practical, scalable solutions that operate effectively under real-world conditions. Templates let you quickly answer FAQs or store snippets for re-use. as well , this person and/or