Cloud computing distributed server load Balancing principle and automation problem

What is load balancing?

Load balancing will distribute site traffic to multiple servers to help ensure that resources are used efficiently and that there is no server overload at every time. The allocation of requirements between server networks can limit time delays and increase response speed. With load balancing, if one or more servers are down due to failure or routine maintenance, the application will not necessarily be shut down completely. Instead, the remaining servers take the task directly. You can set up multiple servers locally, or you can choose a distributed server within the cloud network model.

Within a distributed computing cloud, servers can reside in secure data centers in many different geographic regions. Even if a data center suffers from natural disasters, there will still be a large number of servers available elsewhere to handle the workload. With a private cloud with a complete infrastructure, a service (IaaS) package, load Balancing can be a dedicated set of servers reserved for a particular enterprise customer.

Automation issues

Load Balancing on the cloud sounds very good theoretically. But it's not the magic that happens. For example, an enterprise organization might choose to pursue storage consolidation on a storage area network (SAN) to make better use of server hardware resources. Many companies have tried this approach, discovering that they are constantly stretching their workloads to avoid space or storage constraints.

This is a labor-intensive, repetitive task, and over time the volume of data tends to increase, and the workload itself is in a state of volatility. Manual handling of this process involves analyzing current and projected capacity and performance requirements, providing additional storage configuration, reconfiguring applications, shutting down and restarting servers and applications, and so on. This process must be repeated each time the workload changes significantly, or some servers will exceed the load, while others remain idle.

In this case, there will always be resource consumption, but it is not being used effectively. Load balancing tasks can also take up all of the effective time for IT administrators. Worse, because this type of forecasting and computing needs to perform the appropriate load balancing is so complex and interrelated that occasional errors occur. Any miscalculation will increase server downtime when the need to expand or reduce resources increases.

Using virtualization technology eliminates the need to manually reconfigure resources and automation to ensure that data is placed optimally on a storage area network (SAN), saving it time and money. These features can greatly improve performance. It's just a simple question, but the job uses software better than people do. There are many mundane, repetitive system maintenance tasks that fit this category-but far beyond this storage area network (SAN) example.