eBPF lets networking software such as Cilium run selected programs at Linux kernel hook points, bringing packet handling, service load balancing and network policy closer to where traffic is processed. In Kubernetes, a CNI plugin and node-level agent can coordinate that kernel datapath with pod lifecycle events—but the capabilities and performance depend on the implementation, configuration and platform.
What an eBPF datapath means
An eBPF datapath is the part of a networking system that uses eBPF programs attached to selected points in the Linux kernel to process traffic or make networking decisions. eBPF is not itself a container network or a single feature: different program types attach to different hooks and have different allowed operations.
For networking, relevant attachment points include XDP, traffic-control (TC) hooks and socket hooks. Their positions in the path differ, so a system can choose to act at a socket or at a lower layer as packets move through the host. That placement affects which work the program can do and which traffic it can handle; the term “eBPF networking” does not describe one universal datapath.
How eBPF connects to Kubernetes workloads
Kubernetes continually creates, moves and removes pods. A network implementation has to keep connectivity and policy aligned with those changes. In Cilium’s architecture, a daemon on each node manages eBPF programs, while its CNI plugin is called as pods are scheduled or stopped. Orchestration events can therefore update the kernel networking state as the workload changes.
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This combines two kinds of work: the CNI plugin participates in pod networking lifecycle, and the node agent manages programs the kernel uses for network processing and access control. Cilium’s 2022 security audit describes XDP, TC and socket hooks in its datapath; its current stable documentation reviewed for this article identifies itself as version 1.20.2. That version label is specific to the documentation reviewed, not a claim that every cluster runs that release.
How eBPF changes policy and service handling
Policy can follow workload identity
Pod IP addresses can change as containers are replaced or rescheduled, making rules and monitoring based only on IP addresses harder to maintain. Cilium describes policy based on service, pod or container identity, allowing policy decisions to track workloads rather than treating a particular address as their permanent identity. Its policy features include L3/L4 controls, DNS-based rules and selected L7 filtering. The available controls depend on the implementation and the policy configured; eBPF does not automatically make an application-aware policy correct or complete.
Load balancing can occur at different points
Cilium documents socket-level backend selection when a connection is made, as well as lower-level load-balancing options. It also documents XDP options for supported high-throughput north-south configurations. These are different implementation choices, not interchangeable guarantees: the traffic direction, attachment point, kernel and platform all matter.
Cilium describes its socket-level path as avoiding additional lower-layer NAT in that path, and positions XDP for high-throughput scenarios. Those descriptions explain design intent; they are not benchmark results. The reviewed documentation provides no comparable numeric performance measurement that would establish a speedup for a particular cluster or show that every eBPF deployment is faster.
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What changes when considering kube-proxy replacement
Cilium can provide Kubernetes service load balancing without kube-proxy, but “replace kube-proxy” describes a capability that must be configured and validated, not a universal drop-in switch. The viable setup depends on the routing mode, host devices, kernel support and platform support, as well as the traffic paths and service behavior the cluster needs.
For example, Cilium’s documentation says NodePort XDP is unsupported on the described GCP interfaces because they lack native XDP support. That limitation applies to the documented interface scenario; it should not be generalized to every cloud network or every Cilium load-balancing mode.
Compare the main implementation choices
| Decision | Option or question | What to check |
|---|---|---|
| Pod routing | Overlay networking, such as VXLAN or Geneve | Whether encapsulation fits the underlay and operational requirements. |
| Pod routing | Native routing through the host routing table | Whether the underlying network can route pod addresses and how host routes are integrated. |
| Service load balancing | Socket-level backend selection | Which traffic paths use it and whether its behavior matches the service requirements. |
| Service load balancing | Lower-layer processing, including XDP for supported configurations | Kernel, interface and cloud-platform support; do not assume XDP is available on every node device. |
| Network policy | Identity and L3/L4 controls, with DNS or selected L7 filters where supported | Which policy layer is needed, what the implementation supports and whether rules express the intended access. |
| Operations | Privileges, device selection and BPF map sizing | Required capabilities, the node interfaces used by the datapath, and whether map capacity suits expected workload scale. |
Cilium documents overlay modes using VXLAN or Geneve, native routing through the host routing table and flexible routing integration. These are Cilium capabilities, not properties guaranteed by every eBPF-based CNI.
What to verify before choosing an eBPF datapath
- Map the network path. Decide whether pod traffic will use an overlay or native routing, and confirm that the underlay and host routing design support the choice.
- Identify the required service behavior. Establish which traffic needs load balancing, where in the path it should happen, and whether a lower-layer option such as XDP is supported by the actual node interfaces.
- Set the policy scope. Determine whether identity-based, L3/L4, DNS-based or selected L7 controls are required. Verify that the chosen implementation supports those controls and that policies match the intended workload relationships.
- Check the platform and kernel. Validate the feature requirements against the kernel version, node devices, cloud platform and CNI release used in the cluster. The Linux eBPF documentation says tcx support begins with kernel 6.6 and netkit attachment with kernel 6.7; those version details matter only if the chosen design depends on those attachment types.
- Account for operations. Confirm the needed privileges, node-device selection and BPF map sizing, and test behavior across pod creation, rescheduling and removal.
What the verifier protects—and what it does not
The eBPF verifier checks programs before they can run, including constraints intended to prevent unbounded execution and invalid memory access. That is an important program-safety mechanism, but it does not prove that a networking system is secure as a whole.
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Loading eBPF programs also involves privilege requirements. Linux documentation describes capabilities that vary by use; its BPF Token documentation identifies CAP_BPF and additional network capabilities for network programs such as TC or XDP. Beyond privileges, operators still need to account for kernel and compiler-toolchain dependencies, the Kubernetes environment, and logical mistakes in policy. A program can satisfy verifier checks while implementing an incorrect access rule.
What eBPF does—and does not—promise
eBPF gives a networking implementation a way to place selected processing and policy logic at kernel hooks, and Cilium uses that approach to connect its datapath to Kubernetes workloads. Whether it improves a particular cluster depends on the selected routing and load-balancing behavior, policy needs, hardware and platform support, and operational choices. Cilium’s documentation characterizes eBPF as enabling scalable operation in large environments; that is the vendor’s description, not an independent performance measurement.
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