How to Choose a Load Balancer For Cloud Workloads

Load balancing is a critical component of cloud-based software infrastructure; without it the scale of modern internet applications would not be possible. If not for the ability to automatically distribute requests efficiently, web-facing software would still be constrained to the resources of a single server.

There are a multitude of load balancing options available to organizations, including managed provider services, open-source solutions, and 3rd-party appliances. Choosing the correct implementation requires understanding the advantages and disadvantages of each approach. This article explores the various load balancing solutions, and provides some insights on which might be the best fit for a given engineering organization.

Managed Services Load Balancing

Customers of the major cloud providers have access to scalable, managed load balancing services. AWS, Google, and Azure all provide options for organizations looking for a solution that offloads operational management of the underlying infrastructure.

Amazon Web Services

AWS offers three types of load balancers:

• Application Load Balancer (ALB): Designed for HTTP and HTTPS traffic, it operates at Layer 7 of the OSI model and offers advanced routing capabilities, microservices support, and real-time metrics.

• Network Load Balancer (NLB): Operating at Layer 4 of the OSI model, it is designed for TCP, UDP, and TLS traffic, and offers high performance, low latency, and handling of millions of requests per second.

• Classic Load Balancer (ELB): The legacy solution from AWS, it provides basic load balancing for both HTTP/HTTPS (Layer 7) and TCP traffic (Layer 4), but lacks some of the advanced features found in the newer offerings.

Google Cloud

Google Cloud Load Balancing (GCLB) GCLB offers two primary services to address global and regional requirements:

• Global Load Balancing: Designed for HTTP(S), SSL proxy, and TCP proxy traffic, it offers a single anycast IP address that automatically directs users to the closest available backend, providing low latency and high availability.

• Regional Load Balancing: Ideal for managing traffic within a single region, it supports a variety of traffic types such as HTTP(S), TCP/SSL, and UDP, and allows for the distribution of traffic across multiple backends within a region.

Azure

Azure offers two distinct services for load balancing needs:

• Azure Load Balancer: A Layer 4 load balancer that supports both TCP and UDP traffic, it provides high availability by distributing incoming traffic across multiple virtual machines within the same Azure datacenter. It is capable of handling millions of requests per second with low latency.

• Azure Application Gateway: Operating at Layer 7 of the OSI model, this service is designed for HTTP and HTTPS traffic, offering advanced features such as SSL termination, cookie-based session affinity, URL-based routing, and support for Web Application Firewall (WAF). This makes it suitable for more complex and sophisticated application architectures.

Advantages Of Managed Services Load Balancing

1. Easy Integration with Platform Resources: Integrating a provider's load balancing solution is typically the simplest and most seamless option among the three categories. Managed services are designed to work cohesively with the provider's platform resources, ensuring smooth compatibility and streamlined operations.

2. Simpler IaC Configuration: When using managed services, Infrastructure-as-Code (IaC) tool configurations tend to be simpler compared to installing and configuring services or tools on individual compute nodes. This reduces the complexity of managing and deploying infrastructure.

3. Less Administrative Overhead: With managed services, organizations can reduce the burden of managing the operational and security posture of the underlying infrastructure. This allows teams to focus on their core business functions and application development, rather than getting bogged down in administrative tasks.

Disadvantages Of Managed Services Load Balancing

1. Cost: Managed services often come with a non-trivial cost, adding to the overall expense of cloud deployments. More complex, multi-layered implementations involving cross-zone or cross-region network transit may also incur hidden costs that can quickly add up.

2. Opinionated Implementation: Managed solutions tend to have a more limited feature set compared to 3rd-party alternatives. As a result, certain application architectures might require features not provided by managed solutions, which can create constraints and challenges when designing and deploying applications.

3. Limited Support for External Resources: Managed load balancing services may have limited support for directing traffic to resources outside of the provider's platform. In some cases, this may require workarounds or might not be possible at all, leading to provider lock-in and reduced flexibility when it comes to incorporating external resources.

Self-Managed Load Balancing

Self-managed load balancing leverages open-source software (OSS) tools installed on top of a provider's compute resources. Traefik, HAProxy, and Nginx are all examples of free, OSS load balancers that have seen broad usage across a variety of application environments. This approach offers a fine-tuned, custom implementation and may appear to be the most cost-effective option. However, it's essential to consider the costs associated with management overhead.

Traefik

Traefik is a modern, open-source load balancer and reverse proxy solution designed for cloud-native environments. Developed by Containous, it is written in Go and focuses on simplicity and ease of use. It offers HTTP/HTTPS Layer 7 load balancing, and integrates with Let’s Encrypt for SSL termination. Traefik has gained popularity due to its dynamic configuration capabilities, allowing it to adapt to ever-changing infrastructure landscapes.

HAProxy

HAProxy is a widely used, open-source load balancer and reverse proxy solution known for its high performance, reliability, and flexibility. Developed initially by Willy Tarreau in 2000, it is written in C and primarily operates at the transport layer (Layer 4) of the OSI model, although it also supports Layer 7 capabilities. 

Nginx

Nginx (pronounced "engine-x") is a popular, open-source web server, reverse proxy server, and load balancer solution. Initially released in 2004, Nginx has gained widespread adoption due to its high performance, stability, and scalability. It is often used to handle HTTP and HTTPS traffic, but can also manage other protocols. Recently acquired by F5 networks, it now offers a paid load balancing solution as well.

Advantages Of Self-Managed Load Balancing

• Typically lowest cost: Although network transit is still an issue, running on vanilla compute may offer a lower cost option, especially compared to 3rd-party paid LB options.

• Full control of configuration and implementation: Self-managed load balancing allows for much more granular control over configuration and implementation design, providing the flexibility to tailor the solution to specific requirements.

• Easier support for multi-cloud deployments: Self-managed load balancing can be implemented across multiple clouds as long as the provider offers Linux compute nodes and multiple network interfaces. This approach also makes it easier to host the load balancer in one cloud while running compute resources in another.

Disadvantages Of Self-Managed Load Balancing

• Full operational overhead of managing the underlying compute: Self-managed load balancing infrastructure comes with the same administrative and operational overhead as running your own compute nodes, including security, patching, and overall uptime.

• No support if not using paid solution: If something goes wrong or there is an issue integrating with a provider service, you’ll be on your own for troubleshooting and support. Most OSS solutions have a fairly active community, but the response will be “best effort”.

• IaC will be more complex: Instead of defining an existing provider resource, will need to configure compute as well as configuration and deployment of LB software. Cold-starting new compute infrastructure for load balancing will add to overall start times and may affect infrastructure performance during peak load times.

Third-Party Load Balancing

Third-party load balancing solutions, such as F5 Big-IP, Citrix ADC VPX, and Nginx Plus, are paid options that can be installed on top of cloud provider compute resources. They offer fully supported solutions, without the need to depend on provider services. Additionally, solutions from F5 and Citrix mirror some of the features available in hardware offerings, potentially easing the transition for organizations migrating from on-premise, hardware deployments.

F5 Big-IP

Originally a hardware load balancing appliance, F5 now offers its load balancing solution as a virtual appliance on cloud platforms like AWS. It offers Layer 4 and Layer 7 load balancing, as well as SSL termination. Big-IP appliances can also be configured to provide additional networking features like DDOS protection and Web Application Firewall (WAF). 

Citrix ADC VPX

Citrix ADC VPX is a cloud-based load balancing solution that aims to provide reliable and efficient application delivery across various cloud platforms. It is a virtualized version of Citrix's Application Delivery Controller (ADC) and offers a range of features, including load balancing, traffic management, security, and optimization. It provides Layer 4 and Layer 7 load balancing, SSL termination, and WAF.

Nginx Plus

Nginx Plus is a paid cloud-based load balancing solution that builds upon the popular open-source Nginx web server and reverse proxy. It offers additional features and enhanced capabilities aimed at providing efficient and reliable application delivery in cloud environments. It offers Layer 4 and Layer 7 load balancing, SSL termination, JWT authentication, and additional routing features not available in the OSS solution.

Advantages Of Third-Party Load Balancing

• Full vendor support: Paid solutions have the benefit of access to customer support. There is a much quicker response service-level-agreement, which is critical for issues in production and Tier-1 services.

• Effective bridge solution: Enterprise organizations that are migrating to cloud from on-premise will often have hardware load balancer deployments. Several vendors offer cloud appliance versions of the same load balancer, offering an easier path to transition.

• Easier support for multi-cloud deployments: Third-party load balancers can also be cloud agnostic. Somewhat more dependent on if they offer a dedicated appliance, but if it can be installed on Linux compute it should be compatible.

Disadvantages Of Third-Party Load Balancing

• Cost: Organizations will have to account for the paid subscription cost from the vendor plus the compute and network charges from the platform; this is likely to be the costliest solution.

• Still need to manage and secure the underlying compute: These appliances frequently install on top of existing compute. Organizations will still need to account for the operational overhead of managing these devices and their authentication and authorization surfaces.

• IaC will be more complex: Infrastructure-as-code will still be more complex as you will not be working directly against the provider API–extra configuration is needed to install and run software on compute.

Conclusion

There are a variety of different paths to take when choosing a load-balancing solution, and the best option depends on organizational needs and context. Enterprise organizations migrating from on-premise environments may find it beneficial to mirror their existing appliances, ensuring a smoother transition to the cloud.

Larger, multi-cloud deployments can benefit from the flexibility and control offered by open-source solutions, while smaller organizations and startups might find managed services more suitable, as they provide a cost-effective and simplified approach to load balancing. Ultimately, understanding the specific requirements and constraints of each organization is key to selecting the most suitable load-balancing solution for optimal application performance, reliability, and security.