Cloud computing distributed server load Balancing principle

Many business organizations are talking to IT staff about the cloud environment transfer and/or use of virtual machine technology for better scalability. Ability to access more resources to your needs, and to provide your enterprise with an excellent end-user experience for both internal and external customers. Applications can run faster and can reduce disruption of service while processing network traffic spikes.

In the world of distributed servers, load balancing is the core aspect of any system scalability function. The secret of long-term load balancing work is automation. Let's look at the basics of load balancing. Then we can look at how automation makes programs faster, cheaper, and more efficient.

What is load balancing? How does it work?

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.

In a public cloud, your IP traffic is load-balanced with many other customers on a widely distributed network server. From a true scalability perspective, load balancing in a public cloud is probably the easiest because you can get unlimited server resources from the main cloud service provider. Of course, it is important to check the performance records of any potential cloud service providers to ensure that their customers really experience the ease of scalability requirements.

Focusing on scalability does not mean that the entire program must be transferred to the cloud. There are also blending options available.

For example, Amazon offers 2 EC2 (Amazon Elastic Cloud Computing) version of the Zeus (traffic manager and simple load balancer), allowing businesses and small business customers to balance network traffic load on the cloud based on demand. This gives customers two choices, using the local server for normal traffic, while the peak traffic is temporarily extended to the cloud.

Discuss load balancing with vendors

Some features to ask when purchasing an Extensible load Balancing tool:

Ability to collect detailed, real-time statistics that are used in the allocation effort. Using historical data alone to make predictions is a foolproof way to prevent guessing errors.

A virtual network environment, represented by a single server equipment resources. This is an important feature when it comes to managing cloud applications. A simple interface that makes management tasks easier.

Load balancing services can "see" the load at the application layer, not just at the instance layer. It is one aspect of scalability that there may be a large number of application instances running simultaneously in the cloud.

The load balancer itself has the ability to create new instances and, if necessary, configures the equalizer to meet customer requirements. Ideally, there should be an application programming interface (API) that supports a high degree of integration for a particular business application.

Load balancing includes monitoring capabilities to identify unhealthy application instances and redirect them to healthy instances. Just because a server or application is "available" does not mean it is in the best working state.

The ability to automatically expand, based on preset thresholds, to enable more additional virtual servers to be added-automatically rebalancing workloads between existing and newly joined servers when new servers are available. This rebalancing should occur when any service interruption, reboot, or other requests for it are required.

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.

Of course, automation is just as good as executing scripts created. It doesn't matter how the price of your hardware changes, as long as you're designing a Java application that doesn't make the best use of the server-either locally or on the cloud.

(Responsible editor: The good of the Legacy)