Load Balancing and Autoscaling are two central technologies for the performance and reliability of contemporary Digital Infrastructures. While Load Balancing shares network traffic among several servers so that no one server bears all the workload, Autoscaling performs exactly the opposite: it automatically varies the number of active servers based on prevailing demand. The combination of Load Balancing vs Autoscaling is crucial for maintaining a seamless and efficient system.
In this blog, we will explore key differences between Load Balancing vs Autoscaling technology, how they work, the benefits, and when one should be used between load balancing and autoscaling. These concepts can be applied to run a highly trafficked website or an application with transient user loads for efficient operations.
What is Load Balancing?
Balancing the load is an important aspect of network management. It ensures that incoming traffic is distributed across multiple servers so no single server is overwhelmed; otherwise, the system slows down or crashes. Load balancers act as intermediaries, intelligently directing user requests to the most appropriate server based on their current load, capacity, and availability.
The main purpose of load balancing is to reinforce reliability and efficiency in your digital infrastructure by evenly distributing the load on the traffic. Thus, it maximizes resource utilization, reduces network latency, and assures all users experience consistency on all servers.
How Load Balancing Works
Load balancing distributes incoming requests across all types of servers so that no single server is overburdened with a heavy load. Several algorithms generally control the distribution itself. The round-robin algorithm evenly forwards requests to servers one by one. It is simple and very effective; the load always spreads evenly.
Another very common algorithm is the least connections algorithm. Requests are sent to the server with the fewest active connections. This approach is significantly helpful when the assigned servers have varying capacities or workloads. It eases the maintenance of balance by considering the real-time server load rather than equally distributing requests.
