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This article mainly explains "what is the concept of load balancing". Interested friends may wish to take a look. The method introduced in this paper is simple, fast and practical. Let's let the editor take you to learn "what is the concept of load balancing"?

What is load balancing?

Load balancing is a general term that refers to anything you do to ensure that the resources you manage are allocated effectively. For system administrators of network servers, load balancing usually means ensuring that network server software, such as Nginx, is configured with enough worker nodes to handle the surge of visitors. In other words, if a site suddenly becomes very popular and its number of visitors multiplies several times in a few minutes, the software running the server must be able to respond to the situation without making the user feel that the access is not smooth. For simple sites, only simple configuration is required, but for complex sites with dynamic content and several database queries per user, this can be a difficult problem to deal with.

This problem should have been solved with the development of cloud computing, but when a network application encounters an unexpected surge, it may not be able to expand in time.

When it comes to load balancing, keep in mind that distributed resources do not mean evenly distributed resources. Not all tasks always require all available resources. An intelligent load balancing strategy should only provide resources to users and anyone at the right time. Of course, this is usually the job of the development engineer rather than the IT infrastructure department. Asynchronous applications can take up valuable resources on the server when the user leaves briefly.

How load balancing works

Load balancing avoids bottlenecks by distributing workloads across multiple computing nodes. Those nodes may be physical servers in the data center, containers in the cloud, servers set up for edge computing scenarios, Java virtual machines (Java Virtual Machines) in complex application frameworks, or daemon running on a single Linux server.

The specific implementation principle is to split the big problem into several small tasks, and assign a designated computer to each task. For example, for a web page that requires a user to log in, the web page may be hosted on Server A, while the landing page and all authentication lookups are hosted on Server B. This deployment allows a new user to log on to an account without having to use resources from other active users.

Cloud load balancing

Cloud computing uses containers, so there are usually no separate physical servers to handle different tasks (in fact, there are many separate servers, but they are grouped together as a computing "brain"). Instead, a "pod" is created by several containers. When an pod starts to run out of resources due to its user or task load, an identical pod is generated. Storage and network resources are shared between Pod, and each pod is assigned to a compute node when it is created. Pod can be created or destroyed according to the needs of the load, so that no matter how many users, users can experience a consistent quality of service.

Edge computing

Edge computing needs to take into account the physical world when load balancing. The cloud is a distributed system, but in practice, the nodes of the cloud are usually concentrated in several data centers. The farther away users are from the data center where the cloud is running, the more physical barriers they must overcome to get the best service. Even with fiber-optic connections and proper load balancing, the response time of a server located 3000 km away may be longer than that of a server 300 km away.

Edge computing brings computing nodes to the "edge" of the cloud in an attempt to bridge the geographical gap, thus forming a satellite network for the cloud, so it also plays a role in good load balancing.

What is the load balancing algorithm?

There are many strategies for load balancing, and their complexity depends on the technologies and requirements involved. Load balancing is not necessarily very complex, even if you use professional software such as Kubernetes or Keepalived, load balancing should be carried out from the beginning.

When your application can take simple precautions on its own, don't rely on containers to balance the load. If you design your application to be modular and short-lived from the beginning, you will benefit from clever network design, container orchestration, and load balancing opportunities offered by any future technology.

Some popular algorithms can guide you in your work as an application developer or network engineer, including:

Assign tasks to the server sequentially (this is often referred to as a polling scheduling round-robin)

Assign tasks to the least busy server at present

Assign tasks to the server with the best response time

Randomly assign tasks

These principles can be combined or weighted, for example, in favor of the most powerful server in a group when assigning particularly complex tasks. Orchestration is common so that administrators do not have to come up with perfect algorithms or strategies for load balancing, although it is sometimes up to the administrator to choose which combination of load balancing schemes to use.

Expect an accident to happen

Load balancing is not really about ensuring that all your resources are used evenly across the network. Load balancing means ensuring a reliable user experience even when unexpected situations occur. A good infrastructure can withstand computer downtime, application overload, fierce attacks on network traffic, and user errors. You can start to think about how to make the service resilient and design the corresponding load balancing from scratch.

At this point, I believe you have a deeper understanding of "what is the concept of load balancing". You might as well do it in practice. Here is the website, more related content can enter the relevant channels to inquire, follow us, continue to learn!

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