Kubernetes, the container orchestration tool, is a saving grace against the Microservices backdrop. In short, many businesses have adopted Microservices to manage projects. That is to say, companies now have to deal with hundreds of small containers across various platforms.
If the network isn’t managed and balanced properly, data loads can create a huge performance bottleneck. Moreover, if you don’t conduct data balancing, end users have less resources to run VMs and containers. Yet, when you manage scalability and availability adequately, bottlenecks and resource limitations no longer pose a threat.
To use Kubernetes efficiently, you have to use load balancing. Load balancing spares users the annoyance of dealing with unresponsive services and applications. It also acts as an invisible facilitator between a group of servers and a client, which helps ensure connection requests don’t get lost.
In this article, I’ll go through the basics of load balancing, its benefits, and how to align it with Kubernetes. In addition, you’ll learn how to manage requests over the Kubernetes platforms.
To begin, let’s delve into the basics of load balancing.
What is Kubernetes Load Balancing?
Websites and business applications have to deal with a vast number of queries at peak times. Moreover, to meet this demand, enterprises spread the workload over many servers. Besides cost savings, it also enables an even distribution of load across all servers. This load balancing prevents a single server from crashing. Due to business demands and user needs all modern applications cannot run without it.
Servers can be on-premises, in the cloud, or in a data center. They can be virtual, physical, or part of hybrid solutions. To that end, load balancing needs to work across many different platforms. In any case, you need to achieve the greatest output with the lowest response time.
One way of looking at load balancing is to consider the process as a “traffic cop”. In this analogy, the “traffic cop” routes incoming requests and data across all servers. Here, the “cop” ensures no single server is overworked and brings order to a chaotic situation. If, for some reason a server does go down, the load balancer redirects traffic automatically. When you add a new server to the server pool, the load balancer automatically allocates its resources. To that end, automatic load balancers ensure your system maintains high availability during upgrades and system maintenance tasks.
Now you’re up to speed with the load balancing basics, let’s look at the benefits.
Benefits of Load Balancing
Load balancing provides high availability to your business along with many other value-adding advantages:
- Support for traffic during peak hours: as transactions spike load balancing provides a high quality and rapid response to demand.
- Traffic shifting during canary releases: as new developments are released traffic is redirected through the network to compensate for specific resource bottlenecks.
- Blue or green releases: as you run different versions of an application in two separate environments load balancing helps reduce a systemwide slowdown.
- Infrastructure migration: as platform transitions occur, load balancing helps ensure high availability is achieved.
- Predictive analytics: as user traffic changes it can be monitored and proactive changes to routine made to accommodate it.
- Maintenance task flexibility: as maintenance occurs outages are reduced by routing users to online servers.
I’ve now explained how you can use load balancing to help your business. Now, you’ll learn how load balancing can be applied to the Kubernetes network model.
Understanding the Kubernetes Network Model
In this section, I’ll help you understand how load balancing works with a Kubernetes solution. You’ll learn all the main terms used in Kubernetes networking to help you understand how everything works.
Load Balancing in Kubernetes
Something called “services” plays a big role in load balancing. In short, a service is a group of pods under a common name. By grouping objects like this, the system can easily identify the pod groups and enables selection by other components.
Kubernetes assigns a ClusterIP to each service you create. This is an IP address accessible only within a K8s cluster. It enables you to link other containers within the cluster with these pods. Services can go beyond internal usage. In fact, services can become accessible to external clients if needed.
Load Balancing in External Connections
LoadBalancer, Ingress, and NodePorts are different ways of exposing services to the world. In effect, they enable you to bring external traffic into your cluster. The standard way to directly expose a service to the internet is via a LoadBalancer service. In this case, traffic on the specified node is forwarded to the service without any filtering or routing. This enables you to send any kind of traffic, like TCP, gRPC, HTTP, UDP, etc., to it. In other words, LoadBalancer provides a stable endpoint for external traffic to access.
Ingress Smart Routing
Ingress, unlike the LoadBalancer, isn’t a type of service. Instead, Ingress acts as a “smart router” in front of multiple routers. This smart router operates using a controller, which includes an Ingress resource and a daemon. Both resource and daemon use a specialized Kubernetes pod that helps the project pods to communicate to external clients. In essence, the Ingress resource is a set of rules that govern traffic. This is to say, ingress decides which inbound connections can reach which services. The daemon applies these rules during runtime and specifies connection requirements.
Ingress Customized Rules and Compliance
The ingress resource enables you to add more detailed load balancing rules if needed. Doing so helps you accommodate specific vendors or regulatory requirements. Customizable rules allow you to control load balancing specifically for your needs. In this case, it means you can cater to application needs and runtime conditions.
Now that you have a good understanding of how load balancing works in Kubernetes, let’s go through key terms used in Kubernetes networking.
Key Terms in Kubernetes Networking
When working with a complex system like K8s, it can get overwhelming fast! To help you understand and keep up with unfamiliar phrases and terms I’ve added here key terms you need to know. You’ll see many of these terms when discussing K8s network structures so ensure you know each one well!
Kubernetes services are groups of pods under a common name. Services have stable IP addresses and act as the point of access for external clients. Services are like conventional load balancers as they’re designed to distribute the traffic to a set of pods.
Pods are objects that consist of a set of containers. Projects that use these spaces are closely related to the service they provide. In essence, pods exist so you can simulate application-specific environments reflecting the use-case. Alternatively, you often use them as a self-contained “logical host”. This makes pods perfect for software development and enables teams to migrate projects quickly between sites or companies in dynamic working environments.
In general, pods help you form a single cohesive service building block. You often create Pods for projects and similarly destroy or achieve them to meet business needs. You can think of pods as non-persistent entities that can be scaled, modified and transferred as required. Each pod you create has its own UID and IP address. Pod can use these attributes to communicate with each other but not with containers of a different pod.
Ingress is a collection of routing rules that controls how external users access services. Each rule set is capable of load balancing, SSL termination, and name-based virtual hosting or routing. In essence, Ingress is capable of working at layer 7, this allows it to gather more information for intelligent routing through packet sniffing. For Ingress to function in a Kubernetes cluster, you need to have a component called an ingress controller. Some controller examples include; NginX, HAProxy, Traefik, etc. In any case they don’t start with the cluster so you’ll need to activate them.
So far, you’ve come to understand the basics and benefits of load balancing and how it works in a K8s environment. Now, I’ll show you how a service mesh works and handles load balancing.
How a Service Mesh Handles Load Balancing
A service mesh helps manage all service-to-service communications. In your own case, you can use it to observe data as it resides on the critical path for every request being handled.
Service meshes can help you manage the traffic inside your cluster. In other words, it amplifies your application with a new process that handles load balance requests. In terms of service meshes, they look at protocols and discover IP address services automatically. Service meshes inspect connections like gRPC.
Load balancing in a service mesh utilizes algorithms to identify data throughput and route traffic across your network. In essence, it holds back or routes traffic around unhealthy resources to provide a robust service. Moreover, a service mesh helps reduce the risk of system downs from unbalanced network loading.
Now, I’ll go through a few policy types used for load balancing you can use to optimize your system.
Policies for Load Balancing
Various methods or policies exist for load balancing that can control traffic distribution. To that end, they help carry out intelligent and efficient load balancing. Check out the 3 key policy types you can use.
1. Round Robin
Round robin is the default load balancer policy that distributes incoming traffic. In this case, the server list rotates server connections in the same order as the list. For most companies Round robin works the best in situations with minimal performance variation.
2. Least Connection
This is a dynamic policy where incoming traffic is routed to the backend server with the fewest active connections. It ensures that connections are equally distributed between backend servers.
3. IP Hash
This policy utilizes the source IP address of an incoming request as a hashing key to route client requests to the same backend server. It ensures that requests from a particular client are always routed to the same backend server as long as it’s available.
Load balancing has progressed from simple traffic management systems to managing complex systems. Moreover, it can deliver a lot of value to a business that hosts demanding platforms like Kubernetes. This is because Kubernetes needs dynamic resource allocation across many platforms for projects.
Load balancing is an essential part of keeping your Kubernetes clusters operational. Above all else, remember to configure your Kubernetes infrastructure to meet your needs. That is to say, you don’t have to stick to default traffic management rules. When you optimize your system you’ll have a hardy solution that’ll have less ‘server downs’ and is easier to maintain.
What is Kubernetes load balancer?
It’s a service that sends connections to the first server in the pool until it’s at capacity. When the server is full, it sends new connections to the next available server. It also acts as a stable endpoint for external traffic to access.
What are the key components of Kubernetes load balancing?
The key components of Kubernetes load balancing are:
- Pods and containers; these help you classify and select data.
- Service; this is a group of pods and clusters under a common name.
- Ingress or the ingress controller; these provide access to services from external clients.
- Kubernetes load balancer; this internally balances Kubernetes clusters.
What are the uses of load balancing in Kubernetes?
Load balancing in Kubernetes helps improve server utilization, reduces ‘system down’ events and provides faster data transactions. Additionally, Kubernetes load balancers work on level 7, providing you access to all data parsed through the system. In other words, you have the very best data monitoring and analytics possible when using kubernetes load balancers.
How does Kubernetes handle load balancing?
Kubernetes handles load balancing through a load balancer. This can be internal or external. In the case of internal load balancing, the load balancer enables routing across containers. In essence, internal load balancers help you to optimize in-cluster load balancing. That said, external load balancing helps direct internet traffic to nodes.
How does a service mesh handle load balancing?
A service mesh handles load balancing by using algorithms to decide how traffic should be routed across the network. The idea is that service mesh helps reduce the effort needed by a Kubernetes administrator through this abstraction.
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