Global server load balancing (GSLB) is among several popular load balancer options, with many choosing this solution thanks to its reliability and speed. This is especially true for those who operate on a global scale, with traffic originating from a broad geographic region.
There are a number of methods that load balancers can use to achieve a beneficial distribution of traffic. These GSLB load balancing methods ought to be evaluated and selected strategically in order to see exceptional performance, reliability, and optimal user experience (UX).
What is Global Server Load Balancing (GSLB)?
Stated simply, global server load balancing involves a load balancer that works on a worldwide scale, with servers situated at various locations across the planet. While a typical load balancer may have servers located in a rather limited geographic area, GSLB has servers distributed over multiple continents. This provides a major advantage to organizations with a worldwide presence because distance matters when transmitting data. Therefore, the closer the server, the faster the response time.
A load balancer — including GSLB technology — handles traffic in the form of server requests from multiple sources, such as application-related traffic, website and web app traffic, software-as-a-service (SaaS) traffic, and beyond. If a form of technology requires the use of a server, then it may be subject to load balancing.
Global server load balancers work by identifying “clumps” of traffic and distributing those requests to available servers with the fastest response time and greatest availability. This prevents server overloads and slowdowns, effectively maximizing performance and optimizing speeds.
GSLB brings a big advantage in the realm of reliability because by spreading a load balancing infrastructure across an extremely broad region, you minimize the chance of seeing an event that takes out multiple servers and load balancers at once. With GSLB, there is a dramatic reduction in the chances of downtime and outages just due to the widely distributed nature of these load balancers.
Load Balancing Methods for GSLB
Like all load balancers, global server load balancing technology uses algorithms that employ varying methods for distributing server requests. There is no one-size-fits-all solution when it comes to global server balancing methods. The following is an overview of the most common methods and how they are used to maximize speed and performance.
Round Trip Time (RTT) – Dynamic round trip time (RTT) load balancing algorithms are commonly used for GSLB applications. With this method, the load balancer evaluates server metrics and the LDNS IP address in an attempt to identify the server that is physically closest to the client request origin. The objective is to achieve the shortest possible round trip time for the data. This is one of the favored GSLB load balancing methods because the dynamic nature allows you to take advantage of high availability across a wide geographic area. You can leverage a global server network to maximum benefit using this technique, while also considering factors such as availability.
Static Proximity – When used with GSLB, static proximity load balancer algorithms work off a static list of server locations (based on IP address). Using this list, the algorithm evaluates the location of the DNS server for the client request and the location of the nearest server in the GSLB network. The closest server is selected to handle the request. Like RTT, the static proximity load balancing method makes it possible to effectively leverage GSLB’s wide server distribution in a way that maximizes performance and speed. The only problem is that this method generally doesn’t consider real-time availability, although it is certainly possible to customize an algorithm to allow for this.
Round Robin – Round-robin load balancing is the most commonly used load balancing method, both for GSLB and others. This method involves dispatching client requests to servers in a cyclical, rotational manner. Round robin is often a great option when the server network has components with relatively equal capabilities and fairly consistent availability across the network. Although in the case of GSLB, the round-robin method may not be the best choice because you could potentially be sending requests over a significant geographical distance (an act that slows response time) simply because that server is next in line in the rotation. Generally, you want to avoid sending traffic to a far-off server if there is a more nearby server with good availability since the close proximity increases responsiveness and speed.
Least Connections – A least connections load balancing algorithm will send client requests to the server on the network that happens to have the lowest number of active connections. The decision of which server to utilize is made at the time when the request comes into the load balancer. This can be an efficient method for GSLB since it is very dynamic and allows you to leverage good network availability.
Least Response Time – When speed matters, least response time load balancing algorithms are a good option. This is true for GSLB too. With the least response time load balancer algorithms, two characteristics are evaluated when deciding where to dispatch a client request: shortest average server response time and the number of connections that a server is handling at a given moment (availability.) The server with the best metrics on both of these traits gets the client request,
Least Bandwidth – In the case of a least bandwidth load balancing algorithm, the server’s bandwidth consumption is evaluated in Mbps. The server with the lowest consumption rate is selected to handle the client request.
Least Packets – Least packets load balancing algorithms are quite similar to the least bandwidth method. Instead of evaluating Mbps consumption, the least packets load balancer method entails assigning the client request to the server that has received the smallest number of packets within the past 14 seconds (It is certainly possible to use a different timeframe, but 14 seconds is the most common interval.) In this way, the load balancer dispatches traffic to the server with good availability, which translates into better speed and performance.
There are additional load balancing methods that exist, although many are not commonly used with GSLB. For instance, source hash IP algorithms consider source and destination IP address for the client request and the server, and using this information, a unique hash key is generated. This hash key is used to allocate that request to a particular server. This method does not offer any unique benefit in the case of global server load balancing, though.
Global server load balancing is one of the many options that must be considered as you establish and refine your company’s technology. Once you opt to proceed with GSLB, it is time to choose the right load balancer method and algorithm to suit the organization’s unique needs. Here at Resonate, we are experts in GSLB and a number of other load balancing solutions. We invite you to contact our team today; a Resonate pro can help you navigate the many GSLB load balancing methods, helping you land on the perfect technology for the needs of your application, web portal, or other platform.