Community Blog Improve Kubernetes Network Performance with eBPF

Improve Kubernetes Network Performance with eBPF

In this article, we discuss how an eBPF-based solution can improve the performance issues of Kubernetes networks.

Kubernetes Network Performance Issues

A Kubernetes network can be divided into Pod network, service network, and network policy. The Pod network connects Pods and Nodes in the cluster to a flat network with three layers according to the Kubernetes network model. It is the base for implementing service network and network policy. The service network adds Server Load Balancer (SLB) to the path of the Pod network to support access from pods to the service. Network policy provides Resource Access Management (RAM) between Pods through the stateful firewall.


Service network and network policy are mostly implemented based on the Netfilter framework of Linux kernel including conntrack, iptables, nat, and ipvs. As a packet filtering technology that was added to the kernel in 2001, Netfilter provides a flexible framework and rich functions, which is the most widely used packet filtering technology in Linux. However, there are issues in performance and expansion capability. For example, iptables rules update and match slowly due to linear structure. Conntrack has fast performance degradation in high concurrency scenarios and full connection tables. These problems make the service network and network policy difficult to meet the requirements of large-scale Kubernetes clusters and high-performance scenarios.

To solve these, there are some methods through cloud network products. For example, implement service network with SLB, or network policy with security group. Network products on the cloud provide a wide range of network functions and guarantee SLA. However, since the current cloud network products mainly focus on IaaS, its creation speed, quota, and other restrictions are difficult to meet the elasticity and speed requirements of cloud-native scenarios.

The implementation of the Pod network can be divided into two categories according to whether it passes through kernel L3 protocol stack: routing and Bridge through L3 protocol stack; IPVlan, MacVlan bypass L3 protocol stack. The solution that passes through the L3 protocol stack is compatible with the current service network and the implementation of network policies since the complete L3 processing is retained in the datapath. But the performance of such solutions is low due to the heavier logic of L3. The solution of the bypass L3 protocol stack has good extensibility due to the simple datapath logic, but it is difficult to implement service networks and network policies.

To sum up, the following is the performance issues of Kubernetes networks are summarized:

Service network, network policy ● The solution is based on the netfilter framework: low performance and extensibility.
● The cloud product solution: unable to meet the requirements of cloud-native scenarios.
Pod network ● Pass L3 protocol stack: low performance.
● bypass L3 protocol stack: difficult to realize service network and network policy.

Considering the current situation of the Kubernetes network, we need to re-implement a lightweight service network and network strategy that does not depend on Netfilter. On the one hand, it can be applied to high-performance Pod networks such as IPVlan and MacVlan, and complement the support for service networks and network policies. On the other hand, new implementations need to have better performance and scalability.

eBPF-based Solution

eBPF: Programmable Data Plane

eBPF implements a register-based virtual machine in the kernel and has its 64bit instruction set. Through the system call, we can load a written eBPF program to the kernel and trigger it to run when the corresponding event occurs. At the same time, the kernel also provides relevant verification mechanisms to ensure that the loaded eBPF program can be executed to avoid risks such as damage to the kernel, painc, and security risks.

Kernel currently adds eBPF support to many modules and defines many eBPF program types. Each type determines where it can be loaded into the kernel, the kernel helper function that can be called, the object passed when running the eBPF program, and the read and write permissions on the kernel object. At present, the network is one of the subsystems with more eBPF applications and faster development. Multiple types of eBPF support exist from the network interface controller at the bottom of the protocol stack to the socket at the upper layer.

For the performance of the current netfilter, the community is implementing a new packet filtering technology named bpfilter: https://lwn.net/Articles/755919/

From the perspective of network developers, eBPF is providing a programmable data plane in the kernel, and the kernel ensures the security of the program. Based on this, we hope to implement a high-performance service network and network policy, which is applied to pod networks such as IPVlan, MacVlan, mounting, and other bypass L3. This provides a network solution with good comprehensive performance in Kubernetes.

tc-ebpf: A New Service Network&Network Policy

The tc-ebpf is located at the L2 of the Linux protocol stack and can hook the network device inbound and outbound traffic to the datapath implemented by eBPF. There are many advantages of implementing a service network&network policy based on tc-ebpf:

  • The hook is at the tc layer and does not rely on the L3 protocol stack capability of the kernel. It can easily support many high-performance network types such as IPVlan, MacVlan, and mounting.
  • It can read and write skb_buff. The helper function provided by the kernel is rich and easy to implement complex datapath.
  • The matching and updating rules are Hash-based, which has higher performance and extensibility than iptables rules for linear operations.
  • Datapath is programmable. It can update and optimize the datapath without restarting or upgrading the kernel.

Building a service network&network policy through tc-ebpf requires the following modules:


Conntrack is the basic module of service network and network policy. Egress and ingress traffic is processed by conntrack first, and the connection status of container traffic is generated.

LoadBalance + ReverseNat is the module of the service network. LoadBalance selects the available endpoint for the egress traffic and synchronizes the SLB information to the connection tracing information. ReverseNat searches for the LoadBalance information for the ingress traffic and executes nat to change the source IP address to cluster ip.

The Policy module applies user-defined policy rules for new connections based on the connection status of Conntrack.

We have investigated some implementations in the current community. Cilium is one of the best in building Kubernetes networks based on eBPF technology. eBPF is used to implement pod network, service network, and network policy. However, we found that the network types currently supported by cilium are not well applied to public cloud scenarios.

  • vxlan packet mode: It causes additional performance loss in the process of packet and unpacking. In addition, UDP packets are unable to be optimized by the offloading of network interface controllers such as tso.
  • linux routing mode: In virtualization environments, L2 routing protocols are not supported. For example, in Alibaba Cloud, the IP address of pods of different machines cannot be opened through routing protocols.
  • cni chain: cilium currently supports cni chain mode, which can be connected to the veth network plug-ins, but the performance optimization is not obvious.

Terway With eBPF: Our Plan

Terway is an open-source container network plug-in with high performance by the Alibaba Cloud Container Service team. It supports the use of Alibaba Cloud elastic network cards to implement container networks. It makes the container network and the virtual machine network lay on the same network plane. There will be no packet loss and other losses when the container network communicates between different hosts. The cluster size is not limited by routing entries without distributed routing.

We cooperated with Terway to connect Terway and Cilium through the CNI chain, further optimizing the network performance of Kubernetes.


As the first CNI of the CNI chain, Terway creates the pod network on Alibaba Cloud VPC to connect pods to VPC and provide high-performance container network communication. Cilium, as the second CNI, implements a high-performance service network and network policy.

IPVlan Based CNI Chain

Combining factors such as pod density and performance on a single node, the Pod network uses the eni multi-ip of VPC based on IPVlan L2.


At the same time, implement a CNI chain mode for IPVlan mode in Cilium, and access to the datapath of tc-eBPF on the Pod network created by terway creation to implement the service network and network policy.


Performance Evaluation

The network performance evaluation is mainly compared with Terway's current three network types:

  • Policy-based routing mode
  • IPVlan
  • ENI

The Performance Testing Conclusions of Terway With eBPF mode in this scheme:

  • Pod network performance

    • The ebpf mode is close to but 2% lower than the IPVlan mode and 11% higher than the policy-based routing.
    • Extended performance

      • When the number of Pods increases by 156 from 3, IPVlan and eBPF decrease by about 13%, and policy-based routing decrease by about 23%.
  • Service network performance

    • Compared with kube-proxy(iptables mode), short connections are improved by about 32%, and long connections are improved by 19%.
    • Compared with kube-proxy(ipvs mode), the short connection is improved by about 60%, and the long connection is improved by about 50%.
    • Extended performance

      • When kuberenetes service is increased from 1 to 5000, eBPF and kube-proxy(ipvs mode) performance show good expansion capability. The performance of 5000 services is reduced by 3%. Kube-proxy(iptables mode) short connection decreased by about 60% and long connection decreased by about 6%.
  • Network policy performance

    • when with one pod and policy, the eBPF mode is improved by about 32% compared to the policy-based routing in the short connection and the long connection by about 16%.
    • When with 120 pods and policies, the short connection eBPF improves performance by 19% compared with the policy-based routing; the long connection improves by 24%.

Pod Network

tcp performance testing result:


udp performance testing result:


Service Network

The service network tests the forwarding and scaling capabilities of service networks under different network models. The test compares the pod network. The service is 1,100, and 5000 types. The test tool uses ab and nginx, and nginx is configured as 8 cores.


Network Policy

Terway only has policy-based routing. This test compares the performance data of the two modes when the pod under test is configured with 1 policy and 1 pod and 120 policies and 120 pods. The test tool is ab-nginx and nginx configured as 8 cores.



To analyze the performance, scalability, and other issues in the current Kubernetes network (Pod network, service network, and network policy), we investigated the kenrel eBPF technology and the open-source eBPF container solution Cilium. Finally, we combined Terway on Alibaba Cloud and implemented a high-performance container network solution based on the network characteristics of ENI and multiple IPs. At the same time, the CNI chain solution of IPVlan L2 implemented in cilium has also been open-sourced in the Cilium community.

In the current solution, the service network and network policy of Host Namespace are still implemented by kube-proxy. At present, the service network traffic in Host Namespace accounts for a small proportion of cluster traffic, the traffic types are complex (including cluster ip, node port, extern ip), and the priority and the benefit implemented by eBPF are low.

Since tc-ebpf is before L3 of Linux, it is not yet able to support the reorganization of the sharding packet. This will lead to the failure of the service network-network policy to sharding packets. Therefore, we designed a scheme that redirects shardings to L3 protocol stack re-entry eBPF. However, considering that Kubernetes clusters are mostly deployed in similar networks, the probability of occurrence of sharded messages is relatively low and is not implemented in the current version. In addition, cilium has added service network&network policy support for sharding packets in eBPF. At present, the implementation still has a problem which is sharding packets fails to be out of order to the end.


As a new technology, eBPF provides huge possibilities for network data plane development of kerenl. Our current solution implements service network and network policy at L2. Although there is a certain improvement in performance compared with the netfilter-based solution, the conntrack module is still an overhead that is unable to be ignored on the network. On the other hand, we are also thinking about whether conntrack is needed on the pod of Kubernetes or the datapath in node. We also wonder whether conntrack without load overhead can be implemented based on the socket information.

Based on this, we are exploring the possibility of implementing the service network and network policy at the socket layer. We hope that we can use eBPF at the socket layer to build a conntrack with minimal overhead, thus realizing the service network and network policy scheme with better performance and extensibility.

In addition, we want to implement an IPVlan mode CNI chain mode in Cilium and connect to the tc-eBPF datapath based on the pods created by terway to implement service network and network policy.

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