Kubernetes Networking Deep Dive: CNI, eBPF, and Latency Optimization in 2024

It usually starts around 03:00 CET. Your monitoring stack turns red. The application—a microservices-based heavy hitter hosted in a generic cloud—is timing out. The CPUs aren't maxed, RAM is fine, and the disk I/O looks acceptable. Yet, packets are vanishing into the ether.

If you have managed Kubernetes at scale, you know the culprit is almost always the network overlay. The abstraction that makes K8s so portable is also the thick blanket that suffocates performance if not tuned correctly. In 2024, sticking with default kube-proxy settings and standard iptables rules is a negligence of duty.

This isn't a "Hello World" guide. This is a dissection of how to optimize the datapath for critical workloads in the Nordic region, ensuring you aren't bleeding milliseconds on every request.

The CNI Jungle: Overlay vs. Direct Routing

The Container Network Interface (CNI) is the first decision that dictates your cluster's latency floor. Most managed providers force you into VXLAN encapsulation. While convenient for them (it hides your topology), it adds CPU overhead for packet encapsulation/decapsulation and reduces your effective MTU.

In a high-performance environment, specifically if you are targeting customers in Norway where latency to the NIX (Norwegian Internet Exchange) matters, you want Direct Routing (BGP). This removes the encapsulation header.

Here is how you verify if your current CNI is forcing encapsulation on you. Run this on a node:

If that returns output, you are paying the "overlay tax." On CoolVDS NVMe instances, we provide full L2 control, allowing you to run BGP directly between your nodes using tools like Calico or Cilium without the overlay overhead. This is critical for data-intensive applications where throughput is king.

The Shift to eBPF: Killing iptables

By mid-2024, eBPF (Extended Berkeley Packet Filter) has firmly established itself as the standard for high-performance K8s networking. The old way—kube-proxy managing massive iptables chains—is an O(n) nightmare. Every service you add increases the latency of every packet lookup.

We use Cilium to bypass iptables entirely. With eBPF, the kernel can process packets at an O(1) complexity. The difference isn't just theoretical; benchmarks show a 20-30% reduction in latency for service-to-service communication.

Deploying Cilium for Maximum Throughput

Don't just install the default chart. You need to replace kube-proxy entirely. Here is the values.yaml configuration I use for production clusters targeting the Nordic market:

kubeProxyReplacement: "true"
k8sServiceHost: "API_SERVER_IP"
k8sServicePort: "6443"
l7Proxy: false # Disable if you don't need L7 visibility to save CPU
bpf:
  masquerade: true
  tproxy: true
loadBalancer:
  mode: "dsr" # Direct Server Return - massive win for external traffic
tunnel: "disabled" # We want native routing
autoDirectNodeRoutes: true
ipv4:
  enabled: true

Setting loadBalancer.mode: "dsr" is the secret weapon here. It allows the backend pod to reply directly to the client without passing back through the load balancer node, preserving bandwidth and reducing hops.

Kernel Tuning: The Forgotten Layer

You can have the best CNI configuration in the world, but if your Linux kernel is set to defaults, you will hit a wall. Generic VPS providers rarely optimize the host OS for container workloads. They oversell the CPU, meaning your "Network SoftIRQ" processing gets delayed by noisy neighbors.

When you control the environment—like on a CoolVDS instance where resources are dedicated—you must tune the sysctl parameters to handle the connection churn typical of Kubernetes.

Pro Tip: Many connection timeout issues in K8s are actually netfilter table exhaustion. Monitoring conntrack usage is mandatory.

Apply these settings to your /etc/sysctl.d/99-k8s-network.conf:

# Increase the number of connections
net.netfilter.nf_conntrack_max = 131072
net.ipv4.netfilter.ip_conntrack_expect_max = 8192

# Reduce time-wait sockets to free them up faster
net.ipv4.tcp_tw_reuse = 1
net.ipv4.tcp_fin_timeout = 15

# Increase the range of ephemeral ports
net.ipv4.ip_local_port_range = 1024 65535

# BBR Congestion Control for better throughput over the internet
net.core.default_qdisc = fq
net.ipv4.tcp_congestion_control = bbr

Then apply them:

Enabling BBR (Bottleneck Bandwidth and Round-trip propagation time) is particularly effective for users connecting from mobile networks across Norway's rugged terrain, where signal quality can fluctuate.

The Gateway API: Replacing Ingress

As of 2024, the Gateway API (v1.1) is the mature successor to the fragmented Ingress API. It decouples the role of the infrastructure provider (CoolVDS/NetOps) from the application developer.

Why switch? Because standard Ingress objects are often ambiguous. Gateway API allows for explicit Traffic Splitting (Canary deploys) and Header Matching without relying on messy annotations.

Here is a basic HTTPRoute example that splits traffic between two versions of an app—something that required complex Nginx hacking previously:

apiVersion: gateway.networking.k8s.io/v1
kind: HTTPRoute
metadata:
  name: my-service-route
  namespace: default
spec:
  parentRefs:
  - name: external-gateway
  rules:
  - matches:
    - path:
        type: PathPrefix
        value: /api/v1
    backendRefs:
    - name: my-app-v1
      port: 8080
      weight: 90
    - name: my-app-v2
      port: 8080
      weight: 10

Data Residency and the "Schrems II" Reality

Technical architecture does not exist in a vacuum. For Norwegian businesses, compliance with GDPR and the interpretation of Schrems II by Datatilsynet is non-negotiable. Hosting Kubernetes on US-owned cloud providers introduces legal friction regarding data transfers.

This is where infrastructure choice becomes a compliance strategy. Running your cluster on CoolVDS ensures data sovereignty. The bits stay in Europe. The latency stays low. The legal team stays calm.

Why Infrastructure Choice is the Ultimate Optimization

You can tune eBPF and kernel flags all day, but you cannot software-engineer your way out of bad hardware. Kubernetes is noisy. It generates massive I/O during image pulls and etcd writes.

We see developers struggling with "Disk Pressure" node conditions because they are running on shared HDD or SATA SSD storage. In 2024, NVMe is the baseline requirement for etcd performance. If etcd latency goes above 10ms, your cluster becomes unstable.

The CoolVDS Advantage for K8s:

• NVMe Storage: Keeps etcd fsync latency negligible.
• Guaranteed CPU: No steal time. Your packet processing isn't queued behind another customer's crypto miner.
• 1Gbps+ Uplinks: Essential for inter-node communication if you aren't using a private switch.

Building a Kubernetes cluster is about removing bottlenecks. Start with the network layer, optimize the kernel, but ensure the foundation—the VPS itself—is solid rock, not quicksand.

Ready to drop the overlay tax? Spin up a CoolVDS instance in Oslo today and test the raw TCP throughput yourself.