How Does Load Balancing Reduce Server Pressure?
With the growth of digital services, the need to enhance characteristics such as scalability, responsiveness, performance, and availability has become critical. One effective way to achieve this is by creating replicas of the service and distributing requests evenly across servers among all replicas.
This technique, referred to as load balancing, utilizes advanced hardware or software components known as load balancers. These load balancers adhere to specific criteria to choose the most suitable server from a group of available servers to process a client’s request.
In this article, we will explore the different types of load balancers, static and dynamic load balancing algorithms, and how this process reduces pressure on servers.
What is Load Balancing?
Load balancing involves spreading incoming requests across various servers to enhance performance and prevent any individual server from being overloaded. This is achieved using load balancers, which are devices or software that direct client requests to servers based on specific algorithms. The primary goal is to optimize resource utilization, increase reliability, and reduce response time, thereby minimizing system downtime risks and enhancing user experience, particularly in applications requiring fast processing, such as e-commerce websites and streaming services.
Types of Load Balancing
There are various types of load balancers based on their operation and the technology used, each suited to specific needs for efficiently distributing requests across servers.
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Load Balancing Using SDN (Software-Defined Networking)
Load balancing using SDN decouples the control plane from the data plane to facilitate efficient application delivery. This enables the management of multiple load balancers, allowing the network to function as virtualized instances of computing and storage. With centralized control, network policies and parameters can be programmed directly to provide more responsive and efficient application services, making networks more flexible. This approach facilitates flexible and intelligent request distribution across servers, enhancing network efficiency.
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Load Balancing Using UDP
Load balancers using the User Datagram Protocol (UDP) transmit data without establishing a direct connection between parties. This type is commonly used in live streaming and online gaming, where speed is a priority, and extensive error correction is not required. UDP is characterized by low latency as it avoids time-consuming integrity checks.
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Load Balancing Using TCP
Load balancers relying on the Transmission Control Protocol (TCP) manage data traffic. TCP-based load balancing provides reliable and error-corrected data packet delivery to IP addresses, which could otherwise be easily lost or corrupted without this protocol.
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Server Load Balancing (SLB)
Server Load Balancing (SLB) provides network services and content delivery using a set of load balancing algorithms. It prioritizes responding to specific client requests over the network, ensuring consistent and high-performance application delivery.
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Virtual Load Balancing
Virtual load balancing strives to emulate software-supported infrastructure using virtualization, functioning by executing physical load balancer software within a virtual machine environment. However, virtual load balancers do not overcome the architectural challenges of traditional hardware, such as scalability limitations, automation constraints, and lack of centralized management.
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Elastic Load Balancing
Elastic load balancing scales application traffic as demand fluctuates over time. It uses system health checks to determine the status of application pool members (servers), directs requests to available servers, manages failover to high-availability targets in case of failure, or automatically creates additional capacity.
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Geographical Load Balancing
Geographical load balancing redistributes requests across servers in data centers located in different regions to maximize efficiency and security. While local load balancing occurs within a single data center, geographical load balancing leverages multiple data centers in various locations.
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Multi-Site Load Balancing
Multi-site load balancing, also known as Global Server Load Balancing (GSLB), distributes requests across servers located in multiple sites worldwide. These servers can be local, hosted in public or private clouds. This type is crucial for rapid disaster recovery and ensuring business continuity following a server outage at a specific location.
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Load Balancing as a Service (LBaaS)
Load Balancing as a Service (LBaaS) employs advanced techniques to distribute requests across servers to meet flexibility and application traffic requirements for organizations implementing private cloud infrastructure. Using a service model, LBaaS provides a simple way for application teams to quickly deploy load balancers.
Types of Load Balancing Algorithms
Static Load Balancing Algorithms
In scenarios where the system is consistent and uniform, with steady request traffic, static load balancing algorithms prove to be highly efficient. These algorithms define request distribution rules at the design stage and operate independently of the system’s state during runtime.
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Round Robin
This algorithm distributes requests to servers in a cyclical manner. Instead of relying on specialized software or hardware, it uses a trusted name server, such as the Domain Name System (DNS), to return a different IP address from the list for each request. This method assumes all servers have identical performance capabilities.
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Weighted Round Robin
An enhancement of the Round Robin algorithm, this assigns each server a weight based on its priority or capacity. Servers configured with higher weights receive a larger share of traffic, allowing them to handle more incoming requests than servers with lower weights. Requests are distributed cyclically, allowing servers with greater capacity to handle more requests. This approach ensures request distribution aligns with servers’ actual capabilities.
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IP Hash
This algorithm uses hashing to convert the client's IP address into a number that determines the specific server to handle the request. The hash function considers factors such as the number of servers, their availability, and weights when generating the number.
Dynamic Load Balancing Algorithms
In environments where the system is diverse and request patterns fluctuate often, dynamic load balancing algorithms prove more efficient. These algorithms define request distribution rules based on the system’s state before and during operation, adjusting distribution in real-time based on continuous system health monitoring.
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Least Connection
In this approach, the load balancer identifies the server with the fewest open connections at the time of a client’s request and directs the request to it. Similar to Round Robin, this method assumes all servers have identical performance capabilities.
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Weighted Least Connection
A refinement of the Least Connection algorithm, this method allocates weights to servers according to their priority or capacity. Servers given higher weights are tasked with handling a greater volume of requests than those assigned lower weights. For example, if all servers have the same number of connections, the server with the highest weight is selected, enabling more efficient request distribution based on server capabilities.
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Least Response Time
This algorithm selects the fastest server by analyzing both its response time and the number of active connections. This ensures all client requests are processed with minimal delay.
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Resource-Based
Each server in the pool runs software known as an agent, which collects real-time data about the server’s load based on CPU and available memory. The agent sends this information to the load balancer, which then determines the most capable server to process the client's request and routes it to that server.
Conclusion
Load balancing is a fundamental component in designing modern digital systems, playing a vital role in enhancing performance and ensuring a seamless user experience. By leveraging load balancers and their diverse algorithms—whether static or dynamic—businesses can efficiently distribute requests across servers, whether within a single data center or across multiple geographical locations.
Intelligent request distribution not only reduces pressure on resources but also enhances system resilience and adaptability to changes.