Home » What Is Load Balancer? 10 Best Open Source Load Balancers

What Is Load Balancer? 10 Best Open Source Load Balancers

by Julia
load balancers

Your new public relations campaign has erupted, and the requests are overwhelming your application server. You must swiftly scale your service to meet the millions of new users. Load balancers are an essential tool in cases like this. They’ve helped the web grow to where it is now, where it serves millions of people without a hitch.

A load balancer spreads a request or a connection over a pool of backend servers. As the demand grows, the physical limitations of the hardware limit the capacity of a single application server to process requests efficiently. This is manageable by scaling the application vertically or horizontally.

Vertical scaling works by increasing the server’s hardware resources, such as CPU cores and RAM, to accommodate additional requests. Vertical scaling, on the other hand, has physical restrictions and rapidly becomes prohibitively expensive. Horizontal scaling works by adding additional servers to the mix and distributing requests over many servers, and load balancers are essential to horizontal scalability. Your application can be scaled horizontally, which is very effective and doesn’t cost much, but it could cause a number of technical problems.

Load balancer types

Load balancers can be distinguished by how and where they are deployed.

Load Balancers in Hardware

These are hardware appliances that are constructed with accelerators such as application-specific integrated circuits (ASICs) or field-programmable gate arrays (FPGAs). This lessens the load on the CPU’s major processing requests. You may purchase and implement them on your own premises from companies like F5 or Citrix. They give good results but need to be controlled by hand. Also, because they are based on hardware, they might be hard to expand, which limits how flexible the system can be.

Load Balancers in the Cloud

AWS, GCP, Microsoft Azure, and other public cloud platforms provide high-performance load balancers housed in their data centres, combining the performance of hardware load balancers with the cost and convenience of the cloud. Cloud load balancers are affordable, with usage-based fees. Elastic Load Balancing, for example, is charged by the hour and can cost as little as $20 per month on AWS.

Load Balancers for Software

On your own servers, you may deploy and control software load balancers. Commercial and open-source software load balancers are available. Software load balancing is very flexible and can be easily set up on commodity servers. It can also work with other services that don’t need dedicated servers and comes with simple tools for monitoring and troubleshooting.

The types of requests handled by load balancers can also be differentiated.

Load balancers are implemented in either layer 4 or layer 7 according to the OSI model. In a load balancer, a request is a TCP or UDP connection for L4 load balancers or an HTTP request for L7 load balancers. Most of the time, your application’s use case will tell you which layer of load balancers to use.

A minimal web app would use simple HTTP web servers, and L7 load balancing would suffice. An L4 balancer, on the other hand, would benefit an IoT application running MQTT servers on the internet.

Load Balancers that are Open Source

Open source software has grown to be associated with high levels of quality, dependability, adaptability, and security. Load balancers are not immune to this. While AWS, GCP, and Azure’s closed source load balancers are fast and dependable, they provide limited flexibility and might induce lock-in. Open source load balancers, on the other hand, offer best-in-class performance and a variety of deployment choices, including cloud and on-premises support. Furthermore, prominent open source software projects benefit from big communities pushing their adoption. This is especially important for critical components like load balancers, making it simple to construct a production-ready system by utilising best practises and community expertise.

10 Awesome Open Source Load Balancers

Here is a list of some of the best open-source load balancers.

#1. Nginx


Nginx is a battle-tested piece of software written in C that was first released in 2004. It has since evolved into an all-in-one reverse proxy, load balancer, mail proxy, and HTTP cache. It supports HTTP, HTTPS, FastCGI, uWSGI, SCGI, Memcached, and gRPC backends with L7 load balancing. Nginx’s process worker paradigm is extremely scalable and widely used by companies such as Adobe, Cloudflare, and OpenDNS. Both HAProxy and Nginx are solid, well-known solutions. However, HAProxy is only good for load balancing and proxying, while Nginx can also be used as a high-performance file server.

#2. Pen


The Pen is a C-based L4 load balancer that handles TCP and UDP traffic. It has been tested on Microsoft Windows (as a service), Linux, FreeBSD, and Solaris, but it should operate on any Unix-based system. It employs a modified round-robin algorithm that keeps track of clients and redirects them to the server they previously visited. In these kinds of distributed systems, it’s important that clients stay loyal to the same backend server.

#3. Traefik


Traefik is a reverse proxy as well as a L7 load balancer. It was written in Go to enable microservices and container-powered services in a distributed system. It supports Docker Swarm and Kubernetes orchestration, as well as service registries like etcd and Consul. It also provides comprehensive WebSocket, HTTP/2, and gRPC capabilities. Traefik interfaces nicely with major monitoring systems like Prometheus and Datadog, and it delivers metrics, tracing data, and logs for effective monitoring. A real-time control panel is made possible through a REST API. Traefik Labs also offers an enterprise version of Traefik that has features like OpenID and LDAP authentication.

#4. HAProxy


HAProxy is a load balancer that supports TCP and UDP traffic at the L4 and L7 levels. It’s a well-known open-source solution utilised by firms like Airbnb and GitHub. HAProxy is also a powerful L7 load balancer that supports HTTP/2 and gRPC backends. HAProxy has become the de facto open source load balancer due to its lengthy history, large community, and dependable nature—it comes preinstalled on many Linux versions and is even implemented on many cloud platforms.

#5. OpenELB


OpenELB, originally known as Porter, is a project seeded by the Cloud Native Computing Foundation (CNCF) that aims to provide loadbalancer-type Kubernetes resources in bare-metal, edge, and virtualized environments. LoadBalancer resources in Kubernetes expose services. A load balancer for a cloud vendor Kubernetes deployment is often one of the previously mentioned vendor-operated cloud-based load balancers. OpenELB is an open source solution that lets bare-metal installations of Kubernetes have the same smooth service management experience.

#6. gobetween


Gobetween is a reverse proxy and an L4 load balancer for containers and microservices. Gobetween has been tested on Windows, Linux, and Mac, and it is simple to install in native and containerized settings, requiring only a single executable binary and a JSON configuration file. It, like Traefik, provides real-time monitoring and administration over a REST API. Service discovery is assisted by DNS SRV records, Docker and Docker Swarm, Consul, and other methods. The Gobetween is intended to make automated service discovery in a microservices context easier.

#7. MetalLB


Another CNCF-incubated project is MetalLB. It is a bare-metal implementation of Kubernetes’ LoadBalancer network balancer resource type. It is intended to deliver the smooth experience of cloud network balancers to bare-metal Kubernetes deployments that integrate with ordinary network equipment. It employs conventional routing protocols such as ARP, NDP, and BGP for routing services. On a typical IPv4 Ethernet network, it features a particular Layer 2 load balancing mode that replies to ARP queries for specified services. This makes a new way to balance the load in which all Kubernetes service requests are sent to a single physical IP address and then split up among the pods for that service.

#8. MOSN


MOSN is a cloud native and service mesh load balancer with L4 and L7 support. It is intended to be used in conjunction with the xDS API to find services supported by various service meshes such as Istio. MOSN supports TCP, HTTP, and RPC protocols like SOFARPC.

#9. Katran


Katran is a C++ library developed and used by Facebook for the development of high-performance L4 load balancers. It provides high-performance load balancing by processing packets in the kernel, operating considerably closer to the hardware than other load balancers, and scaling linearly with the capabilities of the networking gear. Katran is a L4 load balancer, so it is more stable when there are problems with the network. This makes it useful for scaling L7 load balancers.

#10. Envoy


Envoy is a C++-based high-performance distributed proxy. It may function as an L4 or L7 load balancer and is intended for the creation of massive distributed service meshes and microservices. With the ability to establish an Envoy mesh of services, it facilitates creating observability in large-scale services, has native support for distributed tracing, and provides wire-level monitoring of MongoDB, DynamoDB, and others. Across the mesh, there is first-class support for HTTP/2 and gRPC, and Envoy provides APIs for real-time service mesh administration.

Last Thoughts

The load-balancing algorithms available are one thing to consider when selecting the correct load balancer for you, although most load balancers provide comparable algorithms, such as IP hashing, round-robin, randomised, and so on. Other capabilities and integrations must be considered in a cloud-native future with vast and dispersed systems. Support for building service meshes, networking for containers, and easily accessible observability information like metrics and traces in standard formats like OpenTracing could all be added.

ContainIQ is a monitoring platform for Kubernetes workloads that is highly available and reliable due to its efficient and performant load balancing. It can be used to monitor and control Kubernetes metrics and events.

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