Planning L4/L7 Load Balancing for Kubernetes Workloads

TL;DR

Kubernetes load balancing should be considered on three separate levels: the public entry at the edge, forwarding into the cluster network, and distribution to the actual workloads. L4 and L7 serve different purposes. The ayedo Edge Cloud enables this separation independently of the provider – with ayedo Managed Kubernetes as well as with externally operated clusters.

Introduction

A Kubernetes Service is not automatically a robust public entry point. If external accessibility is modeled directly from within the cluster, routing, protection functions, TLS, service discovery, and workload operation become intertwined. This complicates failover, provider changes, and the analysis of disruptions. A viable architecture therefore separates the public edge entry from the cluster network and the application itself. Kubernetes load balancing is thus not understood as a single function, but as an interplay of multiple levels: L4 or L7 at the edge, a clearly defined transition into the cluster, and subsequent forwarding to services or pods.

1. Three Levels Instead of a Single Load Balancer

The first level is the ayedo Edge Cloud as the public entrance. Incoming connections or HTTP/HTTPS requests are accepted, protected, and forwarded to a defined backend. The second level is the network of the Kubernetes cluster . It decides how traffic reaches a service, an ingress endpoint, or another published cluster entry. Only the third level concerns the actual workload: service selection, pod distribution, and application-level protocol processing.

This separation reduces coupling. The edge entry does not have to be tied to the lifecycle of a single cluster. Conversely, the cluster can continue to use its internal routing and deployment mechanisms without fully representing public DNS, DDoS, or TLS issues itself. For operations, it is crucial to make responsibilities and fault domains visible: a faulty pod is a different problem than an unreachable cluster endpoint or a connection not accepted at the edge.

2. Choosing L4 and L7 Based on Protocol Needs

L4 load balancing operates at the transport layer. It is suitable when TCP connections need to be distributed to a Kubernetes endpoint transparently or with minimal application interpretation. This is relevant for protocols that are not HTTP-based, or when the application itself must make the protocol decision. The edge distributes connections; the functional semantics largely remain in the backend.

L7 load balancing, on the other hand, processes HTTP or HTTPS requests. This allows application-level rules, TLS termination, and a web application firewall to be organized at the edge. Depending on the architecture, the cluster then receives already terminated or forwarded requests. This variant creates more control options but increases the requirements for headers, source information, certificates, and error analysis. The decision should therefore not be made based on the pattern “L7 is more modern,” but based on protocol, security requirements, TLS responsibility, and required visibility.

3. Provider Independence Through Clear Backend Contracts

Kubernetes integration should not assume that edge and compute are operated by the same provider. For the ayedo Edge Cloud, a Kubernetes cluster can serve as a backend at ayedo, in its own data center, or with another provider. Technically necessary is a stable transition between edge and cluster: defined endpoints, reachable routes, appropriate health checks, and understandable behavior in case of failures.

Backend cloaking prevents internal cluster addresses or the structure of the compute environment from becoming a public architectural detail. External traffic hits the edge; the backend remains hidden behind this layer. In L4 scenarios, the proxy protocol may be relevant if the original connection information needs to be evaluated at the backend. In L7 scenarios, HTTP headers and the TLS model must be consciously defined. These contracts are more important than the specific provider affiliation because they facilitate migrations and multi-cluster scenarios.

4. Planning Operations, Failover, and Responsibilities

Kubernetes load balancing does not end with a functioning route. For reliable operations, health checks must distinguish between “port reachable” and “application usable.” An open network port does not prove that the respective service processes requests correctly. The Edge Cloud can check backends and support failover in case of errors. Which targets are considered healthy must fit the application and cluster setup.

The ayedo Edge Cloud is based on anycast load balancing, its own network infrastructure, and a distributed multi-PoP architecture in an active-active principle. These properties affect the public edge entry, not the availability of individual Kubernetes workloads. Even an actively operated edge can only distribute to reachable and functional backends. Therefore, cluster state, service routing, and pod availability belong to the operational responsibility of the compute side. Traffic and usage statistics at the edge complement this view but do not replace workload and cluster monitoring.

Practical Scenario: One Cluster, Two Operating Models

A company initially operates an HTTP API in ayedo Managed Kubernetes and plans to switch to another provider later. Instead of binding the public address directly to a provider-dependent Kubernetes entry, the ayedo Edge Cloud is defined as a stable edge entry. L7 handles TLS termination, WAF, and forwarding to the cluster endpoint. Health checks determine if the service is reachable.

When switching providers, the external DNS and edge configuration remain unchanged; only the backend is adjusted and tested. For an additional TCP service, L4 load balancing is used separately. The cluster networks of both workloads remain separate, while public accessibility is centrally managed at the edge.

FAQ

Is Kubernetes Load Balancing Always a Task of the Cluster?

No. The cluster distributes internally to services and pods. The public entry can be located on an edge platform before that. Both levels should be planned and operated separately.

When Is L4 Load Balancing Preferable to L7?

L4 is suitable for TCP-based or non-HTTP-specific services. L7 is advisable when HTTP/HTTPS processing, TLS termination, or a web application firewall is needed at the edge.

Does the Integration Only Work with ayedo Managed Kubernetes?

No. The ayedo Edge Cloud can also connect to Kubernetes clusters that are self-operated or run by other providers. Reachable backends and clearly defined routing and health-check contracts are crucial.

Conclusion

Provider-independent Kubernetes load balancing is not achieved through a single service, but through the clean separation of edge entry, cluster network, and workload. L4 and L7 must be chosen based on protocol and operating model. The ayedo Edge Cloud organizes public traffic entry, protection, TLS, and backend distribution independently of the compute platform – for Managed Kubernetes as well as for external clusters.