To compare the hosting prices of two different cloud computing plans, one would have to do a lot of juggling. The first thing that you need to compare are the price points. Price should be compared in the context of the level of service and features offered by both the plans. Ideally, your decision on the hosting plan should be based on your needs and the level of functionality that you need.
There are two main approaches to hosting cloud computing servers: on-demand and standard models. The primary difference between these two types of cloud servers is the pricing structure. Here’s a brief comparison between the two:
On-demand Cloud Computing Servers are powered by the user and are much more expensive than the standard model. For example, a developer may need many gigabytes of storage and therefore opts for a on-demand cloud compute server poweredge. The standard models are more economical but less powerful. They only allow a specified amount of memory and CPU load. The benefit here is that there’s no need for upgrades or provisioning of extra hardware.
On-demand cloud compute services provide ample capacity with high availability. Standard models on the other hand are more economical but offer only minimal capacity. They are typically deployed as shared load with other companies. As a result, the hardware resources are spread across many users. This is bad news if performance is crucial since the system is normally soldered onto a single socket of hardware.
High speed and low latency are the two features that make up a great on-demand server. We ran two high speed and two low latency benchmarks against both types and found significant increases in throughput and latency. In addition to the throughput and latency increase, we also saw an almost tripling in total traffic. In cloud terms, this is performance difference that can make the difference between being a leader in your market or being left behind.
With regards to purchasing on-demand VPS server hardware, we found that price was not a significant factor. The most important thing was to purchase the right type of processor core. For instance, a Google Compute Engine with four processor cores and eight gigabytes of RAM consumed the same amount of money as a Celeron Processor with four fewer core and eight gigabytes less of RAM. The conclusion is that speed and price do not directly correlate in terms of cloud hardware capacity per dollar. Rather, you have to have a good understanding of the hardware structure as well as the operating system used by the company that uses the computing infrastructure.