Kubernetes 1.34 is actively supported, and eBPF CNIs can enforce and observe pod traffic in real time. Build the stack step by step. Read now.
Why eBPF fits Kubernetes security
Kubernetes 1.34 is actively supported, which makes it a practical baseline for teams that want modern networking and observability without chasing every experimental feature. At the same time, eBPF-based CNIs sit close to the kernel: they can see packet paths as pods talk, apply policy before traffic leaves a node, and surface connection-level signals without installing agents inside every container. That combination—supported control plane plus kernel-level enforcement—is what makes a real-time security stack viable rather than a pile of disconnected tools.
Traditional approaches often rely on sidecar proxies or post-hoc log shipping. Those work, but they add hop latency, configuration surface, and blind spots when traffic never leaves the node. eBPF programs attach at well-defined points in the network path, so you can enforce allow/deny rules and observe flows with less per-pod overhead. The tradeoff is operational: you need kernel support, careful CNI choice, and clear ownership of policy and telemetry so security does not become a black box only one person understands.
Choose the building blocks
Start with a single eBPF CNI that both connects pods and understands network policy. Mixing a classic CNI for connectivity with a separate eBPF layer for security can work, but it doubles failure modes and makes “why was this packet dropped?” harder to answer. Prefer one datapath that implements Kubernetes NetworkPolicy (and any extended policy model you need) so enforcement and observation share the same source of truth.
Next, decide what “observe” means for your cluster. Minimum useful set: identity of source and destination (namespace, pod labels, service), protocol and ports, allow vs deny outcome, and enough volume or rate context to spot scans and noisy neighbors. Export that telemetry to a store your on-call team already uses. Avoid inventing a second dashboard that only the networking team opens during incidents.
- CNI: pod networking plus policy enforcement in one eBPF datapath
- Policy: namespace defaults, least-privilege allow lists, and explicit deny visibility
- Telemetry: flow or connection events with Kubernetes identity attached
- Ops: runbooks for drop reasons, CNI health, and kernel compatibility
Build the stack step by step
Step one: bring up a small non-production cluster on Kubernetes 1.34 (or later within the same support line) with your chosen eBPF CNI. Verify basic pod-to-pod and pod-to-service connectivity before any security rules. Step two: enable network policy in a single namespace. Start with a default-deny ingress rule, then add explicit allows for known clients. Confirm both “works when allowed” and “fails when denied” with simple probes so you trust the datapath before wider rollout.
Step three: turn on real-time observation. Stream flow or drop events to your aggregator and practice reading them during a controlled deny. Step four: expand policy by application tier—frontend, API, data—rather than by node or IP. Label-based identity survives rescheduling; IPs do not. Step five: codify policy in Git (or your usual config pipeline) so reviews catch overly broad allows before they hit production. Keep each change small enough that a bad rule can be reverted without a cluster-wide incident.
Operate without losing the signal
Real-time security only helps if you act on it. Wire drop spikes and unexpected egress to alerts with enough identity context to page the right team. During incidents, compare policy intent (“this service should only talk to that database”) against live flows; mismatches usually mean missing labels, stale NetworkPolicy, or a second path that bypasses the eBPF CNI. Test upgrades of Kubernetes and the CNI together in staging so kernel, kubelet, and eBPF programs stay aligned.
Document the failure modes you care about: policy misconfiguration, CNI agent crash, node kernel too old for required eBPF features, and multi-network setups where not all traffic hits the eBPF path. When those are written down and exercised, eBPF on Kubernetes 1.34+ is not a research project—it is a practical way to enforce and observe pod traffic in real time, one deliberate layer at a time.