Scalable Load Balancing and Ingress
Cloud Native Load Balancing with Cilium
- Pod-to-Pod (Intra-Cluster) Load-Balancing
- Usually provided by the limited iptables-based kube-proxy.
- External-to-Pod (North-South LB)
- Exposing pods externally typically requires another tool.
- Inter-Cluster Load-Balancing
- Driven by requirements for High-Availability and Disaster Recovery.
- Can be difficult to configure and manage.
- Non-Kubernetes Load-Balancing
- Traditional Hardware Load-balancers can be very costly.
Cilium Load-Balancing Options
- Scalable and efficient Intra-Cluster Load-Balancing with XDP.
- XDP (eXpress Data Path) is an eBPF-based high-performance data path.
- XDP Acceleration provides 5x reduction in CPU usage.
- Direct Server Return (DSR) provides optimized low-latency connectivity, while maintaining the client source IP (required for observability purposes).
- Cilium Cluster Mesh automatically provides cross-cluster service load-balancing and discovery.
- Cilium Standalone LB offers a high-performance LB, providing huge throughput gains at a reduced CPU overhead.
High Performance Load-Balancing
- Load-Balancing within a cluster much more efficient and scalable.
- Load Balancing across Multi-Cloud Clusters much easier to configure and operate than alternatives.
- Improved user experience for applications hosted on Kubernetes clusters through lower-latency network path
- Non-K8S environments benefit from extremely high performance Load Balancing at the fraction of the cost of traditional HW Load Balancing appliances.
North-South Load Balancing of Kubernetes Services with eBPF/XDP
Kubernetes service load balancing has relied far too long on netfilter and iptables - two technologies which carry legacy accumulated over 20 years of development grounded in a more traditional networking environment that is typically far smaller and more static than your average Kubernetes cluster.
In this talk, the audience will learn how Cilium leverages eBPF/XDP to replace both to implement load balancing of Kubernetes services. The implementation not only improves scalability of service load balancing, but also brings new features, such as DSR or consistent hashing.
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