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What is the difference between the common machine room and the modular machine room?

What is the difference between the common machine room and the modular machine room?

Modular data center is to integrate the transformation of cloud computing technology, virtualization technology, centralized and multi-layer network servers, improve the operation efficiency of big data center, reduce energy consumption, complete rapid expansion, realize rapid expansion and have no influence on each other.

The micro module data center is composed of several micro modular design control modules, which has a separate function and unified i/o socket. The micro modular design control module in different areas can back up data with each other, and a detailed big data center is generated according to the arrangement and combination of the control modules of the relevant micro modular design.

The micro module data center is a comprehensive, standardized, best, intelligent, high to width ratio adaptability infrastructure construction natural environment and high width ratio can be used in cloud computing platform.

Traditional machine room:
The traditional machine room generally uses industrial air conditioning to cool the overall indoor space of the main engine room, and the air frame exhaust method of the next layer of the precision air conditioner in the machine room can be selected. First, the cooling efficiency is low because there is no difference between cold and thermal safety channels; second, the net total area of the main engine room is large and the relativity is sufficient to be considered, so there are provisions for the main engine room.

1、 Challenges for traditional data centers:
1. It is a long development cycle;
According to the specific situation of construction projects, the development cycle of traditional big data center is generally divided into management decision-making, early preparation, execution and project acceptance. The development cycle is about 400 days and down.
2. It is poor scalability.
Scalability is critical for adaptability. It plans system volume based on the analysis of future business process requirements and the most difficult situation. However, they can not predict the situation in 3-4 years, and thus lead to too many construction.
3. It's a lot of energy.
There are many power consumption in big data center. Traditional Chinese buildings have not considered the problems such as power engineering, cooling, cyclone management methods. Many big data centers use pue (powerusageffectiveness) with high efficiency index value of power energy. In the basic practical sense, powerusageeffective equipment (PUE) of big data center is high But the machine equipment is usually low efficiency, pue in big data center is higher or higher than big data center, which represents that the power energy applied by big data center is about half of it load, and the other half is important physical infrastructure construction of Internet, including power supply equipment, refrigeration equipment and lighting equipment.
4. It is difficult to operate and maintain the machine room.

There are many problems in IT management, which are in a dilemma of low service level and can not be promoted: extensive operation, unclear resource account; frequent alternation of operating staff, insufficient grasp of IT resources and management methods; lack of unified service project page staff, common fault response and common fault resolution and tracking disorder The system software management and promotion must accumulate a lot of data information and tables by IT staff to draw conclusions. However, it management is difficult to carry out statistical analysis on this data information reasonably.


Modular machine room:
The difference between modular machine room and traditional machine room depends on its ability to maximize the use of cooling output power to heat the machine equipment. Because the closed cold safety channel is selected, the air conditioner is separated from the heat flow, which improves the cooling efficiency in general; the central air conditioner and it server cabinet are placed in parallel space, and the central air conditioner is selected to exhaust air at the level, and the cooling air is immediately blown to the server cabinet, and the heat discharge regulations are considered to reduce the energy consumption by more than 30%, which saves customers a lot of operating costs.
Secondly, the modular design of the host room can be deployed quickly. Because the cabinet door is self-contained before the original factory, it can be applied only by connecting the external switch power supply and fixing the door.

1. To quickly deploy and reduce the construction cycle time;
The overall planning and design scheme speed of big data center of micro touch group is accelerated, and the system structure can be effectively equipped according to the overall design plan objectives. The mass production of micro touch group can complete direct selling of manufacturers, thus improving the delivery rate; standardized interface mode can reduce the labor volume of equipment and connection in the field and accelerate the installation rate; the development cycle of big data center of micro touch group can be accelerated It can be greatly shortened. The implementation of traditional big data center must be from July to October, and the construction of micro touch group will be reduced to 2-3 months.
2. Convenient expansion, phased construction;
With the system architecture of micro module, big data center can be gradually improved, and then a micro module can be from one to dozens of micro modules in a link. For all large and medium-sized big data centers of all business scale, it indoor space is the best. The small modular design of big data center plan can significantly reduce the cost of big data center in its service life.
3. The standard control module design scheme is stable and reliable.
The design scheme of modular design, standardization and high width ratio is selected for the micro model big data center, which makes the system software have high reliability. In addition, according to the user requirements, the micro module big data center can also show the plan plans such as N, n+1 and 2n for customers to choose, and achieve the maximum level of four tier for TIA-942.
4. Green environment protection and energy saving.
In TCO (total cost), the cost of power engineering in the service period of big data center is a big one. Compared with the traditional mainframe, the cooling efficiency of the micro module big data center has increased by 12%. The micro touch group big data center integrates water-cooling system, of course, the refrigeration system can minimize pue.
5. Intelligent management method, high efficiency operation;
Intelligent system intelligent management system can help customers save resources, complete multi-level energy consumption management method and detailed energy consumption management method of data room, accurately locate additional power energy consumption points according to various tables. According to data analysis, the environmental protection and energy saving improvement scheme is output to create green data room;

The best investment management is to carry out life-cycle management method for the property of each major website, complete the closed-loop of property information content, ensure the data upgrade and management method immediately. It also helps customers to formulate property maintenance plan, assist customers to complete positive warning information in maintenance plan, and dynamically adjust maintenance plan, output the best plan according to the current situation, and optimize investment management function.

The big data center of intelligent system control module integrates power supply system, cabinet door system software, refrigeration subsystem, integrated wiring system and intelligent intelligent management system. With the rapid development trend of cloud computing technology and mobile Internet, it relative density and energy consumption have been greatly improved, which makes traditional big data center encounter great challenges.

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