Cloud Computing

The most basic definition of cloud computing is distributed computing, for huge data processing we give up using the original computing processing mode of separate terminals, but through the network cloud terminal all the data is decomposed into countless small computing steps.

The original huge data calculation and processing procedures are decomposed into small procedures, each small procedure has a corresponding server, and countless servers form a complete system to process all the data, and then the processing results are finally aggregated and returned to the cloud terminal, which is the basic principle and operation mode of cloud computing.

For example, to provide basic industrial and domestic water for a city, it is not enough to rely on a single well, so if we want to meet the massive water consumption of the city, we must have an independent water plant, which takes water from a certain place and then distributes it to each water department through a pipeline. Cloud computing is one such network that aggregates resources and then distributes them to provide the appropriate supply according to the demand of each sector.

     Why cloud computing costs tend to exceed the mark

It's clear that cost has become an important issue for many companies going to the cloud, and that cloud spending is more complex to track and control.So, why are cloud costs so easily out of control? The biggest problem is that enterprises in the process of cloud migration, and will not be able to take full advantage of the cloud computing digital transformation of the foundation firmly.

One reason for the high cost of cloud is the high percentage of "direct uploads" in cloud migration, where most applications end up running on virtual machines and do not take advantage of the pay-as-you-go nature of cloud services.

Another major factor is that the cloud itself is highly dynamic. It is often cheaper to use new compute and storage services, but if you just migrate directly to the cloud without making subsequent changes, tuning, making some personalized adaptations, etc., the return on value is inevitably compromised.

In short, users who pay attention and choose a new version every year will get a more cost-effective service experience.

While built-in cost optimization mechanisms can save money, enterprises often tend to overestimate how much they need for resources. The problem here is that all of the large cloud service vendors are willing to use sizable discounts to gain customers, but enterprises can only actually save valuable money if they make the most of these resources. Failure to use resources effectively is itself a huge waste.

Another problem is that the employees responsible for cost optimization are often not the ones responsible for building technical solutions.Engineers want their applications to work, but it's hard for them to predict the exact capacity, compute, and storage space requirements, so engineers typically choose to over-provision first and then eliminate some resources later as they see fit.

But in most cases, a project ends and then a new one comes along, so the idle resources are left unused forever. Similarly, rushing to the cloud does pose the risk that the configuration decisions made by technical staff are out of sync with actual business needs.

The sudden outbreak of the new crown epidemic has forced most enterprises to rush up the amount of cloud spending. The fact is, there is no such thing as one cloud provider being a better value than another.

At the same time, the sheer number of cloud services available on the market today is a real problem, but large cloud providers do not intentionally push unnecessary over-provisioning on their customers.