Stop DDoS Attacks on Kubernetes Clusters

/ Containers

Stop DDoS Attacks on Kubernetes Clusters

Secure your Kubernetes infrastructure with proven DDoS prevention, detection, and mitigation strategies

DDoS attacks are becoming increasingly sophisticated, and Kubernetes clusters are a prime target. Imagine your critical applications grinding to a halt under a flood of malicious traffic, costing your business thousands—or even millions—in downtime and lost opportunities.

Kubernetes clusters, with their dynamic scaling and cloud-native design, offer incredible flexibility and resilience. But these same features can also be exploited by attackers. DDoS campaigns can overwhelm your system’s resources, disrupt operations, and even exploit your auto-scaling capabilities to inflate cloud costs—an insidious new tactic known as an Economic Denial of Sustainability (EDoS) attack.

How DDoS Attacks Target Kubernetes

External Threats

Your Kubernetes cluster’s public-facing services, such as exposed APIs or web applications, are the most common targets for external attackers. These entry points are vulnerable to being bombarded with illegitimate traffic:

  • SYN Flood Attacks: Exploit the handshake process in TCP connections
  • HTTP-Based DDoS Attacks: Flood web-facing services with massive numbers of fake requests

Internal Threats

If an attacker gains access to your cluster, they can escalate the attack from within. Kubernetes’ default networking allows lateral movement, making it possible for attackers to infect other workloads and amplify the damage.

Economic Denial of Sustainability (EDoS)

The Yo-Yo Attack is one of the newest and most insidious forms of DDoS attacks. Attackers generate sudden traffic spikes, triggering Kubernetes’ auto-scaling mechanisms, then back off, forcing your system into a constant loop of scaling up and down—like a yo-yo—without any real user activity.

Critical Threat: EDoS Attacks

While traditional DDoS attacks aim to disrupt availability, EDoS attacks exploit cloud-native auto-scaling to drain your budget. By driving up compute, storage, and bandwidth costs, attackers can harm your business without ever taking down your systems.

DDoS Prevention Strategies

Network-Level Protections

  • Web Application Firewalls (WAFs): Google Cloud Armor, AWS Shield, or Azure DDoS Protection
  • Rate Limiting: Set limits on ingress traffic using NGINX annotations
nginx.ingress.kubernetes.io/limit-rps: '10'
nginx.ingress.kubernetes.io/limit-connections: '2'

Zero Trust Network Policies

Adopt a zero-trust approach using tools like Calico or Cilium to enforce strict network policies. Control which external traffic is allowed into your cluster and restrict outgoing traffic to limit potential data exfiltration.

Global Traffic Distribution

CDNs like Cloudflare and Fastly are designed to handle massive amounts of traffic, making them ideal for absorbing and mitigating DDoS attacks. They route traffic through globally distributed networks, offloading surges from your Kubernetes cluster.

Detection and Mitigation

Key Metrics to Monitor

  • CPU and Memory Usage Spikes: Sudden surges often signal malicious traffic
  • Increased Inbound Traffic: Abnormally high volume of requests to specific services
  • Baseline Monitoring: Establish normal traffic patterns for rapid anomaly detection

Immediate Mitigation Actions

  1. Temporarily reduce rate limits on ingress controllers
  2. Identify and block attacking IPs with Network Policies
  3. Capture and analyze traffic patterns using tools like tcpdump
  4. Implement packet capture for forensic analysis
apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
  name: deny-malicious-traffic
spec:
  podSelector: {}
  ingress:
  - from:
    - ipBlock:
        cidr: 203.0.113.0/24

Best Practice: Use tools like Prometheus and Grafana for real-time monitoring, or integrate with Calico for comprehensive network visibility and anomaly detection.

Cost Controls for EDoS Protection

Protect your budget from Economic Denial of Sustainability attacks by implementing proper cost controls:

  • Optimize Autoscaling: Configure HPA and Cluster Autoscaler with sensible limits
  • Enforce Resource Limits: Use resource requests and limits in pod specifications
  • Set Maximum Scaling Boundaries: Define maximum pod limits to control resource allocation
resources:
  requests:
    memory: "256Mi"
    cpu: "500m"
  limits:
    memory: "512Mi"
    cpu: "1"

Elevate Your IT Efficiency with Expert Solutions

Transform Your Technology, Propel Your Business

Protect your Kubernetes clusters from sophisticated DDoS attacks with proven defense strategies. At InventiveHQ, we help you implement comprehensive security measures that safeguard your infrastructure and your bottom line from evolving cyber threats.

Secure Your Kubernetes Cluster