Load balancing distributes network traffic among multiple servers to ensure availability without any performance degradation. Load balancing is crucial for any application, especially when dealing with large distributed or microservices-based containerized environments. Kubernetes provides powerful networking capabilities like load balancing to facilitate communication between all the resources within the cluster, both internally and externally. This post will see how to implement load balancing in a Kubernetes cluster.
What is Kubernetes Load Balancing?
The core load balancing principles do not differ from traditional server-based applications to containerized applications. Network traffic will be routed to an available server or service depending on the load, availability, etc. It not only balances out resource utilization, but also increases availability. Thus, the load balancer will route the traffic to the next available server without impacting the end-user, even when a server error causes a 5xx error.
Kubernetes Pods are not designed to be persistent. Hence, they can be easily created or destroyed without any input from the user, depending on the use case. Direct communication with pods is impossible as new IPs are attached to them. Kubernetes addresses this issue by providing a way to expose a set of pods as a network service. The service will get a request from an external resource and then dispatch the request to an available pod. It can be considered a simpler form of load balancing. However, using Kube-Proxy or Ingress are the two primary methods available for load balancing.
Kube-Proxy vs. Ingress
Load distribution is the most basic type of load balancing available in Kubernetes. It is done through the Kube-proxy. Iptables is the default Kube-proxy mode for rule-based IP management with random selection as the load distribution method. Kube-proxy is ideal for routing internal traffic, debugging services, and connecting to internal dashboards. However, it requires the user to run kubectl as an authenticated user. Therefore, it is not a good load balancing solution for production.
The preferred solution for production is to load balance using ingress. It allows users to expose HTTP and HTTPS routes from outside the cluster to internal services. Traffic routing is controlled by the set of rules defined within the ingress resource. Ingress has numerous capabilities, including load balancing, SSL/TLS termination, name-based virtual hosting, etc., which an ingress controller controls. The ingress controller has built-in load balancing features and can be customized for specific infrastructure configurations. Kubernetes supports different types of Ingress controllers and a wide range of plugins for the ingress controllers to extend their capabilities further.
An alternative approach to ingress is to use an external load balancer. However, it will lack the tighter integration and control provided by Kubernetes ingress. Besides, its capabilities are solely dependent on the platform or service.
Types of Load Balancing Strategies Available in Kubernetes
Now we understand how load balancing works in a Kubernetes cluster. So let’s look at some load balancing strategies and algorithms available in K8s.
Round Robin
Here, the requests are distributed to all the available servers in sequential order. It is a static algorithm that does not account for the performance of individual servers. Thus it can be unsuitable for production environments while being useful in development environments.
Fastest Response
This method sends requests to the server, providing the fastest response. It is also called “weighted response time” and is measured by the time to the first byte. It is an excellent choice for managing short-lived connections that require the fastest possible response.
Fewest Servers
This strategy distributes all the requests across all the required servers by determining the least number of servers required to fulfill the network requests. In Kubernetes, the load balancer sends connections to the first available server and sends them to the next available server only when it reaches full capacity. It is a great option to control the resource requirements.
Least Connections
This method includes routing requests based on the least number of active connections. However, it also accounts for connection load, since long-lived connections can impact the performance. This option is particularly suited for slower and unhealthy servers, and works for both short and long-lived connections.
Resource Bases / Least Load
This algorithm will send requests to the server with the lightest load, despite the number of connections. The traffic is sent to the server with the least load, depending on the response times of older requests. It prevents smaller requests from getting tied behind larger requests, improving latency.
Conclusion
Proper load balancing is essential to ensure the availability and performance of applications within the cluster, ultimately leading to a reliable user experience. Users can easily accommodate any load balancing requirements in a Kubernetes cluster with Kube-Proxy for internal communications, development, and debugging use cases. In the meantime, they can use ingress for production load balancing.
