Load balancing
APIs refers to distributing incoming API requests across multiple backend servers or resources to optimize performance, ensure high availability, and prevent overload on any single server. It improves the efficiency of handling API traffic by evenly distributing requests based on predefined algorithms or metrics such as server load, response time, or server capacity.
Load balancing, in general, is the process of evenly distributing workload across multiple computing resources (such as servers, CPUs, or network links) to optimize resource utilization, maximize throughput, and minimize response time. It helps maintain system stability and prevent any single resource from becoming a bottleneck.
An example of load balancing is a website that receives a large volume of user requests. Instead of routing all requests to a single server, a load balancer distributes them across multiple servers in a server farm. This distribution ensures that no single server becomes overwhelmed, thereby improving the overall performance and reliability of the website.
An API gateway is not strictly a load balancer but can include load balancing capabilities. While an API gateway primarily acts as an entry point for API requests, it may include features such as request routing, load distribution, and traffic management to optimize API performance and ensure scalability.
In microservices architecture, load balancing is crucial due to the distributed nature of services. It involves distributing incoming requests across multiple instances of microservices to avoid overloading any single service instance. Load balancing strategies in microservices typically include round-robin, least connections, or weighted algorithms to manage traffic efficiently and maintain service availability and responsiveness.