Jiangsu Huawei's five methods of cloud computing cost Many organizations benefit from hosting workloads in the cloud service platform. However, if the cost of cloud computing technology cannot be controlled, this infrastructure construction model will not continue. When the SARS CoV-2 pneumonia epidemic still endangers the operation of institutions, institutions must reassess their own expenditures, including the cost of cloud computing technology. There are many reasons for the soaring cost of cloud accounting, such as over allocation of resources, excess volume and poor visibility of its natural environment. Fortunately, there are some special tools and cost raising practices that can help eliminate excess expenses. Organizations can choose the following special tools and practices to reduce cloud accounting costs.

What are the five methods of Huawei's cloud computing cost?

1. Select the saved cases in the cloud. If organizations want to make some measurements, they can find alternatives with lower prices according to their needs. And try to apply the following discount pricing scheme: embedded case pricing. By applying a certain number of organizations within one to three years, early service commitment can save cloud resources through embedded cases. According to independent variables such as service platform, the price of embedded cases is only one third of that of on-demand cases. Each key cloud computing technology service provider will provide such price options, such as Amazon 2 embedded case (RI), Microsoft Azure embedded virtual machine case and Google cloud service commitment application solution. Compared with the standard EC2RI, AWS enterprises also present a "saving plan", showing similar discounts and more coordination ability at the application level. Embedded cases are best suited for workloads with consistent and predictable analysis. Price the box on the spot. Developers can obtain discount prices for their unused volumes according to Amazon EC2 competition case, Azure competition virtual machine virtual machine and Google CloudPreemitbleVM. The saving of this pricing model lies in the purchase resources and purchase prices. The cost of such cases may change frequently and may vary from time to time. If the case exceeds the ceiling price of cloud computing technology customers, it may stop. Low priority queuing cases can save up to 90% of the cost, but the ease of use of such cases is greatly limited and may end abruptly, which actually depends on the overall capacity demand of the region. They are best suited for stateless workloads, batch command work, and other daily tasks that can tolerate termination.

2. Overall volume planning Even if an organization can start a startup project or close a case in the cloud service platform, it will still pay for unused volumes. The IT elite team must ensure that there is enough capacity to solve unexpected peak traffic and load fluctuations, but not too little, to prevent them from overusing redundant resources. Overall capacity planning helps reduce overall cloud accounting costs. Fully automated resource expansion can help organizations ensure that they do not pay for unused cloud volumes. Cloud computing technology service providers present full-automatic expansion of original ecological service projects, such as AWSAutoScaling. This role can fully and automatically monitor and adjust the running scale of the application software to meet the requirements, and can be used to clarify the priority of cost, ease of use or features. Considering the cost, set the main parameters of auto scaling. For example, these characteristics are limited to low priority queue workloads and are not extended. Autoscale settings are provided to apply at least total resources to meet demand. And, where appropriate, incorporate some of the above preferential discount schemes. No network server computing can also help deal with many expansion problems, but some early solutions are still necessary to prevent costs from getting out of control. Organizations can also apply technologies such as long queues and cached files to cope with unexpected peak periods of total traffic without paying for spare capacity.

3. The data transmission cost of institutions that limit the cost of public cloud data transmission is likely to be very high. Cloud computing technology service providers generally deduct the import and export costs of data and information, thus removing data and information from their service platforms, or even moving them across regions. In order to reduce these costs, redundant data transmission must be prevented. The organization first evaluates the data transmission costs of its cloud computing technology service providers. Then, adjust its cloud computing architecture to reduce the frequency of data transmission. For example, organizations can move the internally deployed applications that frequently browse cloud hosting data information to the cloud service platform to clear this transmission. In addition, the cost of different transmission technologies specifically used to accelerate and maintain the movement of data information between cloud service platforms and exclusive big data centers was also evaluated. For example, compare the cost of application specific data connection services (such as AWSDirectConnect, AzureExpressRoute, or Google CloudInterconnect) with the cost of physical transport machines (such as AWSSnowball or AzureDataBox).

4. AWS enterprises use special tools for cost supervision to launch various special tools for cost supervision. AWSCostExplorer, a special tool presented in it, can analyze the past expenditures of an organization, even 13 months ago, and predict and analyze the cloud computing technology expenditures of the organization in the next three months. Another special tool is AWSBudgets, which sets custom alerts to notify customers when the cost exceeds a special point. It can also automatically limit resources to reduce cloud accounting costs. Microsoft cloud customers can apply for Azure cost control fees to monitor their expenditures. This special tool tracks the cost of each Azure service project, provides forecast analysis of future credit card bills, and alerts customers when they exceed their budget. Similarly, Google Cost Management enables Google Cloud Service platform customers to identify the highest cost and set expense reports to increase costs. In addition to cloud local options, third-party cost and expense monitoring tools can also help organizations make informed expenditure management decisions. For example, CloudChecker tracks the cost of cross cloud computing servers and makes recommendations to reduce costs. Scalr is another third-party special tool that can use cost analysis reports as part of its cloud computing technology management system.

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5. Avoiding cloud diffusion Cloud diffusion is the external diffusion of cloud computing servers that will not be manipulated, which should be attributed to the soaring cost of many cloud computing technologies. When organizations cannot eliminate cloud computing technology that is not part of their overall development strategy, they will still pay for it again. To prevent this problem, organizations must apply infrastructure construction and its application software monitoring and visualization tools to create appropriate visibility of cloud computing platforms. Set countermeasures on how and when to stop using unnecessary cloud computing servers. The original working load shall be turned off by fully automatic equipment.