Widely used in applications with high volume of simultaneous access, a load balancer is a computational resource used to perform load distribution between two or more servers of an application.
They are usually implemented using machines dedicated to this work, which can be physical or virtual, or by “software”.
Benefits
Regardless of the model to be implemented, they aim to distribute the processing of an application among the available instances, seeking to optimize the use of computational resources, such as network, processing (CPU), memory usage, among others.
This distribution of resources reduces the risk that the instances of an application are overloaded, consequently optimizing response times at times of high number of simultaneous accesses to the application.
Another benefit that comes from using load balancing is the increase in availability (resilience), as they use application sanity validation, which means that in cases where one or more instances are unavailable, no traffic is forwarded to them, thus helping the end user not to perceive this unavailability.
Balancing models
A load balancer can operate in two network layers of the OSI model, layer 4 (transport) and layer 7 (application). Balancers built in the transport layer tend to require less processing power to perform the task, however, they have access to less request information than application layer implementations. Although more expensive, in relation to the need for processing, layer 7 deployments tend to bring many benefits and with increasingly affordable costs, its adoption has grown a lot in recent years.
Layer 4: Transport
This balancing model works at the transport layer, that is, routing decisions are based on data available there, that is, protocol information, such as TCP or UDP, destination and source IP addressing. Based on this information, the packet is forwarded through a resource called NAT.
It is important to note that balancing at this layer is done purely with this information, that is, the packet content is not intercepted and/or analyzed during forwarding, which can make it difficult or even disable the creation of rules that guarantee that the same user have your requests always directed to the same instance of an application, which can be problematic when, for example, there is a need for user session control.
Layer 7: Application
This balancing model offers more resources for balancing decisions and this is due to the fact that it works at the highest layer of the OSI model. As it is in this layer, it is possible to analyze, in addition to the existing information in layer 4, as well as other information related to the received request to decide which instance the request will be forwarded to. For example, in an HTTP request balancing, we can check information contained in the header to decide the destination server, this allows us to control the distribution in the use of resources, but also allows us to guarantee other controls, such as, for example, guarantee that all requests of a given user are always processed by the same application instance.
Balancing Strategies
The principle of a load balancer is to distribute the requests among the servers available for processing the request, however, in practically all implementations, we can define how these requests will be distributed among the instances of our application. This decision is made by pre-defined algorithms, but it is usually also possible to create custom rules.
In this text I will describe two of the algorithms that I believe to be the most used, however, several others exist and it is always recommended to evaluate them before choosing which one to use in your application.
Round Robin
This algorithm is normally the standard used by many balancing solutions on the market. In it, each request is forwarded to a different instance among the available ones, following a standardized and continuous order.
Although effective for most cases, this algorithm can cause overload on one of the servers, as it does not consider pending requests to forward a request or not. That is, it can be problematic for cases where most requests processed by the application have very different times between them and require intensive use of processing to complete, which means that one of the servers may have more requests being processed at a given moment than others, consequently degrading application performance.
Least Connection
This algorithm forwards to servers using a simple analysis model, which consists of verifying which server among those available has the least amount of requests at the moment.
In other words, it is a very efficient model in relation to load distribution and usually superior in performance, as the server with the lowest number of requests will always be the one chosen to receive the next request. However, it can still be impacted by the distribution of requests, where a server, despite having fewer connections, all require high processing power, thus degrading all active requests on this server.
Existing solutions
There are several devices and applications on the market in order to offer a load balancing solution. cloud providers such as Amazon AWS and Google Cloud, also have native solutions available, which can facilitate their implementation when using these providers.
In the Open Source world, there are several solutions created for this purpose, each with its advantages and disadvantages.
Here is a list of what I believe to be the main solutions currently and their respective layers of action:
Conclusion
Briefly, a load balancer (load balancer) is a computational resource, which can be a device or an application, responsible for distributing the processing between the different instances of an application through defined strategies.
It acts as an intermediary (proxy), receiving and directing requests according to defined rules and aiming not only to increase the processing capacity of the application but also its availability.
I hope this text has helped you understand what a load balancer is and some of the problems this solution aims to solve. Finally, I leave some links that were useful to me during the preparation of this text.
