Last Updated on October 6, 2023 by KnownSense
Load balancers are networking devices or software components that evenly distribute incoming network or application traffic across multiple servers or resources. They play a crucial role in optimizing resource utilization, ensuring high availability, and improving the reliability and performance of modern applications and services by preventing any single server from becoming overwhelmed with traffic. Load balancers are commonly used in data centers, cloud environments, and microservices architectures to deliver a seamless and responsive user experience
Why Is a Load Balancer Required?
Load balancers are necessary for the following reasons:
- Scalability: Microservices architecture involves deploying multiple instances of each microservice. A load balancer evenly distributes incoming traffic across these instances, allowing you to scale horizontally as your application grows.
- High Availability: Microservices need to be highly available. If one instance of a microservice becomes unavailable due to failures or maintenance, a load balancer can route traffic to healthy instances, minimizing downtime.
- Traffic Management: Load balancers can implement various traffic management strategies, such as round-robin, least connections, or session affinity, to ensure efficient resource utilization and optimal response times.
- Security: Load balancers can act as a security layer, protecting microservices from direct exposure to the internet. They can handle tasks like SSL termination and filtering malicious traffic.
Working
Load balancers provides benefits discussed above by supporting multiple stateless instances of our microservices and by routing incoming traffic to these instances using some kind of load sharing algorithm. This gives us the ability to increase performance and reliability at any point by introducing new instances of our microservices. The brilliant thing is our client application is unaware of the load balancer. It’s unaware that there’s a component in the middle which is actually load sharing the incoming traffic between multiple instances of our back‑end microservices. As far as the calling application is concerned, it thinks it’s talking directly to the back‑end microservices. It’s unaware that there’s a load balancer. So in terms of the design of our client application, we don’t actually have to do anything different in order to support a load balancer. The only thing we have to do with our back‑end microservices is to ensure that they’re stateless so that the incoming traffic can be rerouted to any one of those microservice instances without having to worry about what’s actually in the memory of those microservice instances.
Most load balancers also provide additional functionality in the form of health probes, which improves the reliability of our architecture. By using this health probe functionality, our load balancers every so often make a call to our downstream microservices instances, and if a specific instance stops responding, let’s say there’s an issue with that microservice, so there’s a connection failure, our load balancer will stop routing traffic to that specific instance. These health probes normally call a specific endpoint on each one of your microservice instances to see if they respond. These endpoints can also be custom health checks, which are designed not only to provide the status of your microservice instance, but also the statuses of any dependencies of your microservice instances, like, for example, local databases or downstream connections. If one of these health check endpoints on one of your microservice instances reports that one of the dependencies is down, let’s say, for example, a downstream connection has been lost, your load balancer again can stop routing traffic to that specific instance of the microservice that’s experiencing that connectivity problem.
So hopefully from this you can see not only load balancers help us scale out in order to improve performance, but they also enable us to create a software architecture that’s kind of self‑healing.
Different Ways of Implementing Load Balancers
Several methods can be used to implement load balancing in a microservices architecture:
- Software Load Balancers: These are software-based load balancers deployed as containers or processes alongside microservices. Examples include Nginx, HAProxy, and software-based load balancing solutions provided by cloud platforms like AWS Application Load Balancer (ALB).
- Hardware Load Balancers: Physical load balancing appliances designed for high-performance, data center-level load balancing. They are suitable for large-scale microservices deployments.
- Service Mesh Load Balancing: Service mesh technologies like Istio and Linkerd provide built-in load balancing capabilities. They offer advanced features like traffic routing, retries, and circuit breaking.
- Cloud Load Balancers: Major cloud providers (e.g., AWS, Azure, Google Cloud) offer load balancing services specifically tailored for microservices deployments within their respective ecosystems.
Examples of Load Balancers
- Nginx: Nginx is a popular open-source software load balancer that can be used as an API gateway or for load balancing microservices. It is known for its speed and flexibility.
- AWS Elastic Load Balancer (ELB): AWS provides several load balancing options, including the Application Load Balancer (ALB) and Network Load Balancer (NLB), suitable for microservices deployed on AWS.
- Istio: Istio is a service mesh that includes robust load balancing capabilities. It can be used to manage microservices traffic, implement retries, and control routing.
- HAProxy: HAProxy is a high-performance software load balancer suitable for microservices deployments. It can be used to balance TCP and HTTP traffic.
Conclusion
In conclusion, load balancers are a vital component in microservices architecture, ensuring scalability, high availability, efficient traffic management, and security. The choice of load balancing strategy and technology depends on the specific needs of your microservices-based application. Whether you opt for software-based solutions like Nginx or cloud-native load balancers provided by major cloud providers, implementing effective load balancing is essential for the success of your microservices ecosystem.