Load balancing is a technique that distributes the workload among multiple servers or nodes in a distributed system, improving performance, reliability, and scalability. In this article, you will learn how to implement load balancing in a distributed system, covering the main concepts, methods, and challenges involved.
Load balancing is essential for any distributed system that handles a large number of requests or tasks from clients or users. By spreading the load across multiple servers, load balancing can reduce response time and latency, increase throughput and availability, avoid overloading or crashing a single server or node, enhance fault tolerance and resilience, and enable horizontal scaling and elasticity of the system. All of these benefits can help ensure a smooth running system.
Load balancing helps you to scale horizontally. Having LBs in front of your application, helps on security as well, blocking incoming malicious traffic to your vulnerable application. Prefer active-active balancer to avoid a single point of failure
Load balancing works by using a component called a load balancer, which acts as a proxy or intermediary between the clients and the servers. The load balancer receives the requests or tasks from the clients and forwards them to one of the servers or nodes in the system, according to a certain algorithm or policy. The load balancer also monitors the status and capacity of the servers or nodes, and adjusts the distribution accordingly.
An example of this is Application Load Balancers in AWS, a pure nginx or even HAproxy. They are what we call Layer 7 proxy. They understand HTTP protocol, they analyze the request and take actions on it. Route to specific server, discard the. Request, add caching headers, etc
Load balancers utilize various methods or algorithms to distribute requests or tasks among servers or nodes. The most common of these are round robin, random, least connections, least response time, and weighted. Round robin assigns each request or task to the next server or node in a circular order, regardless of the current load or performance of each server or node. Random assigns requests or tasks to a server or node without considering any criteria or metrics. Least connections assigns requests or tasks to the server with the least number of active connections or tasks. Least response time assigns requests or tasks to the server with the lowest average response time. And weighted assigns requests or tasks based on a predefined weight or priority which reflects the relative capacity or performance of each server or node.
Load balancing is not a simple task, and involves various challenges and trade-offs that must be addressed. Consistency is a major challenge, as load balancing can introduce inconsistency or stale data in the system. This is especially true if servers or nodes store or update stateful information, such as if a client updates a record on one server or node, and then reads it from another server or node, without seeing the latest version of the record. Affinity is also an issue, as load balancing may break the affinity between a client and a server or node. To preserve affinity, cookies, headers, or other identifiers may need to be used to track and maintain the client-server relationship. Security is also an issue, as load balancing may expose the system to security risks if the load balancer is compromised or malfunctioning. To ensure security, encryption, authentication, or firewall techniques may need to be used to protect the load balancer and the system.
Load balancing in a distributed system can be implemented in various ways, depending on the architecture, requirements, and tools. A hardware load balancer is a dedicated physical device that uses specialized hardware and software to perform load balancing functions at the network layer. It is usually fast, reliable, and scalable, but also expensive, complex, and inflexible. Software load balancers are general-purpose applications that run on a server or node to perform load balancing functions at the application layer. They are usually cheaper, simpler, and more customizable, but slower, less reliable, and less scalable. Cloud load balancers are services provided by a cloud platform that use virtualized resources and configurations as part of the cloud infrastructure. They are convenient, flexible, and elastic but dependent, limited, and costly.