Top 6 Load Balancing Algorithms Every Developer Should Know

Hey there! In today's video,   we’ll have a comprehensive overview  of load balancing algorithms. Have you ever wondered how big web platforms   handle millions of requests  without breaking a sweat? Load balancing is an absolutely critical  component of any large-scale web application. By distributing workload across  multiple servers, load balancing   helps ensure high availability,  responsiveness, and scalability. Understanding the core load balancing  algorithms will allow us to better architect,   troubleshoot, and optimize our applications. There are two main categories of  algorithms: static and dynamic. We'll provide an overview of each category and  dive deeper into the major specific algorithms,   including how they work and their pros and cons. Stick around to the end because we'll  also summarize key criteria to help   you select the right algorithm. Let's get started! Static load balancing algorithms distribute  requests to servers without taking into   account the servers' real-time conditions  and performance metrics. The main advantage   is simplicity, but the downside is  less adaptability and precision. Round robin is conceptually the simplest  approach. It rotates requests evenly among   the servers, sending request 1 to  server A, request 2 to server B,   and so on in sequence. This algorithm  is easy to implement and understand. However, it can potentially overload  servers if they are not properly monitored. Sticky round robin is an extension of round robin   that tries to send subsequent requests  from the same user to the same server. The goal here is to improve performance  by having related data on the same server. But uneven loads can easily occur since  newly arriving users are assigned randomly. Weighted round robin allows  admins to assign different   weights or priorities to different servers. Servers with higher weights will receive a  proportionally higher number of requests.   This allows us to account for  heterogeneous server capabilities. The downside is that the weights  must be manually configured,   which is less adaptive to real-time changes. Hash-based algorithms use a hash function to  map incoming requests to the backend servers. The hash function often uses the client's IP   address or the requested URL as input for  determining where to route each request. It can evenly distribute requests  if the function is chosen wisely.   However, selecting an optimal hash  function could be challenging. Now let's switch gears to dynamic  load balancing algorithms. These adapt in real-time by  taking active performance   metrics and server conditions into  account when distributing requests. Least connections algorithms  send each new request to the   server currently with the least number  of active connections or open requests. This requires actively tracking the number of  ongoing connections on each backend server. The advantage is new requests are adaptively  routed to where there is most remaining capacity. However, it's possible for load to unintentionally   concentrate on certain servers  if connections pile up unevenly. Least response time algorithms send  incoming requests to the server with   the lowest current latency  or fastest response time. Latency for each server is continuously measured   and factored in. This approach  is highly adaptive and reactive. However, it requires constant monitoring which   incurs significant overhead  and introduces complexity. It also doesn't consider how many  existing requests each server already has. So in summary, there are clear tradeoffs between   simpler static algorithms and  more adaptive dynamic ones. Think about our specific performance goals,   capabilities, and constraints when  selecting a load balancing strategy. Static algorithms like round robin  work well for stateless applications.   Dynamic algorithms help optimize response  times and availability for large, complex   applications. Also, the differentiation between  "static" and "dynamic" is somewhat simplified. Which algorithms do you  think suits your needs best?   Have you faced any challenges with load balancing  in the past? Share your experiences and insights   in the comments below. We’d love to learn  from you, and we’ll see you in our next video. If you like our videos, you may like our system  design newsletter as well. It covers topics and   trends in large-scale system design. Trusted by  500,000 readers. Subscribe at blog.bytebytego.com