Stop Treating Kubernetes Networking Like Magic

If I have to explain to one more junior developer that a Service is not a load balancer but a virtual abstraction powered by iptables rules (or eBPF maps if you're living in 2024), I might just switch to farming. Kubernetes networking is widely misunderstood. It is often treated as a black box where you toss a YAML file in, and traffic magically flows. Until it doesn't. Until you hit a 504 Gateway Timeout during a Black Friday sale, or your cross-node latency spikes because your underlying VPS provider is oversubscribing their CPU cycles.

We are going to dissect the packet flow. We will look at why kube-proxy using iptables is a bottleneck at scale, why eBPF is the standard for serious production workloads in late 2024, and how physical infrastructure in Oslo impacts your application's responsiveness.

The CNI Jungle: Why Flannel is Dead to Me

In the early days, we used Flannel. It was simple. It created a VXLAN overlay. It worked. But simplicity costs performance. Encapsulation overhead is real. Today, if you are running a high-traffic cluster on CoolVDS, you shouldn't be wrapping packets in packets unless you absolutely have to.

By November 2024, the industry standard has shifted heavily toward Cilium. Why? Because eBPF (Extended Berkeley Packet Filter). Instead of traversing the horrific maze of iptables chains—which is O(N) complexity—eBPF allows us to hook directly into the kernel network stack. It’s O(1). Whether you have 10 services or 10,000, the lookup time is virtually the same.

Pro Tip: If you are running on CoolVDS NVMe instances, you have full kernel control via KVM. Do not try running complex eBPF setups on cheap OpenVZ containers offered by budget hosts. You need the kernel headers. You need the isolation.

Deploying Cilium for Performance

Forget the default install. You want to replace kube-proxy entirely. Here is how we initialize a cluster to bypass legacy netfilter paths:

helm install cilium cilium/cilium --version 1.16.1 \n  --namespace kube-system \n  --set kubeProxyReplacement=true \n  --set k8sServiceHost=API_SERVER_IP \n  --set k8sServicePort=6443 \n  --set hubble.relay.enabled=true \n  --set hubble.ui.enabled=true

By setting kubeProxyReplacement=true, we stop writing thousands of iptables rules. The result? Lower CPU usage on the node and significantly lower latency for Service resolution.

Ingress vs. Gateway API: The 2024 Reality

The Kubernetes Gateway API hit GA a while ago, but let's be pragmatic. Most of you are still running NGINX Ingress Controller. And that is fine. NGINX is battle-tested. However, the default config is garbage for high-throughput apps.

The biggest killer of performance I see in Norwegian setups is the lack of buffer tuning. When latency varies—say, a user connecting from Tromsø to a server in Oslo on a shaky 4G connection—NGINX needs to hold that connection open. If your buffers are too small, you get I/O blocking.

Here is the ConfigMap tuning I apply to every production cluster:

apiVersion: v1\nkind: ConfigMap\nmetadata:\n  name: ingress-nginx-controller\n  namespace: ingress-nginx\ndata:\n  worker-processes: "auto"\n  max-worker-connections: "65536"\n  keep-alive: "65"\n  upstream-keepalive-connections: "100"\n  upstream-keepalive-timeout: "32"\n  client-body-buffer-size: "64k"\n  proxy-body-size: "10m"\n  use-forwarded-headers: "true"

These settings allow NGINX to handle the bursty traffic typical of e-commerce platforms without choking on memory allocation.

The Physical Layer: Latency and Sovereignty

You can optimize your CNI and tune your NGINX buffers all day, but if your physical packets have to travel through a congested route, it’s useless. This is where the geography of hosting becomes a technical spec, not just marketing.

In Norway, peering at NIX (Norwegian Internet Exchange) is critical. If your VPS provider routes traffic from Oslo to Stockholm and back just to reach a Telenor user, you are adding 15-20ms of unnecessary RTT (Round Trip Time). In a microservices architecture where one user request triggers 50 internal service calls, that latency compounds.

The "Noisy Neighbor" Problem

Kubernetes requires consistent CPU performance for the control plane. If etcd fsync latency goes high, your cluster becomes unstable. This happens constantly on shared hosting platforms where "vCPUs" are massively oversold.

We architect CoolVDS differently. When you buy a slice of our infrastructure, we isolate the I/O path. We use NVMe storage arrays because etcd writes to disk synchronously. If disk write latency exceeds 10ms, etcd starts throwing leader election warnings. On spinning rust or cheap network storage, K8s falls apart.

Here is how you verify if your current host is stealing your CPU cycles:

# Install sysstat if you haven't already\napt-get install sysstat\n\n# Watch the %steal column\niostat -c 1 10

If %steal is consistently above 0.5, your provider is overselling. Move your workload.

Compliance: The Norwegian Context

Running Kubernetes in 2024 isn't just about packets; it's about Datatilsynet (The Norwegian Data Protection Authority). With the continuing fallout from Schrems II, moving data outside the EEA is a legal minefield. Many US-based cloud providers claim compliance, but the CLOUD Act still hangs over them.

Hosting on Norwegian soil, on servers owned by a Norwegian entity, simplifies your GDPR posture immensely. You aren't just reducing latency to NIX; you're reducing legal exposure. CoolVDS infrastructure is located physically in Oslo. We don't ship your logs to a data center in Virginia.

Debugging When It All Breaks

Eventually, a pod will fail to talk to the database. It happens. Don't guess. Use nsenter to debug from the node perspective without installing tools inside your slim production containers.

Find the PID of the container:

crictl inspect --output go-template --template '{{.info.pid}}' 

Then jump into its network namespace:

nsenter -t  -n netstat -rn

This allows you to see exactly how the kernel is routing traffic for that specific pod. If you see routes missing or incorrect gateways, you know it's a CNI failure, not an application bug.

Final Thoughts

Kubernetes networking is deterministic. It follows rules. If it feels slow, it's usually because of poor encapsulation choices or cheap hardware that can't handle the interrupt load. Don't settle for default configurations, and definitely don't settle for hardware that steals your CPU cycles.

If you need a cluster that respects the laws of physics and the laws of Norway, verify your infrastructure. Spin up a CoolVDS instance, run your etcd benchmarks, and look at the latency numbers. The difference is usually double-digit milliseconds.