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機房建置，如今的企業或組織，都非常依賴於他們的計算機系統和他們存儲的信息。數據繼續呈指數增長，對數據存儲的需求也持續增強。
其實數據存儲已成爲了熱門話題，因爲組織需要考慮如何存儲他們正在生成的海量數據。用戶所產生的內容的增加，以及來自法規遵從性的不斷增加的壓力，導致信息存儲在未來很長時間內都是重點。
僅僅增加更多的存儲容量來滿足這種數據增長，對於那些需要壓縮預算、物理空間、電力和管理資源的組織來說，已經不再是一種可行策略。於是出現了一些根據高密度和低功耗原則而建立的現代存儲解決方案。
一個現代存儲基礎設施
有沒有一種新的技術或策略可以幫助企業克服那些超過了他們預算的數據增長所帶來的挑戰？答案是：沒有。不過，有一種已經存在了相當長一段時間的技術，它能夠滿足當今組織的所有存儲需求。
有些希望實現現代存儲體系結構的組織，發現自己可以利用閃存、磁盤和磁帶來創建存儲基礎設施，從而能夠在訪問速度和負擔能力的平衡下存儲數據。在這個案例中，磁帶提供了最大的密度和最低的功耗。
近年來，磁帶被認爲是一種瀕死的數據中心技術，但是隨着數據和存儲環境的不斷髮展，由於其高密度和低能耗，仍然保持着相關性。雖然基於磁盤的解決方案常常被考慮用於數據保護場景，與傳統的磁帶截然相反，但是對於大多數組織來說，重要的問題並不是在兩種技術之間進行選擇，而是如何在現代的存儲架構中有效地使用它們。
簡單地說，存儲的決定應該來自於一個平衡的“等式”，其中包括業務需求和每個存儲設備的投資回報 （ROI）最大化。
爆發式數據增長的原因
很長一段時間內，各種規模的組織都需要努力應對越來越多的“關鍵商業信息”和“其他信息”。這一非同尋常的數據增長背後有很多原因，這在組織中有所不同，但主要涉及以下方面：
1、組織要求對產品、服務和客戶提供更詳細的信息，這些信息將影響業務策略、驅動增長和提高服務水平（業務應用程序和數據倉庫）。
2、用戶驅動的非結構化內容增長，如圖像、視頻和音頻，以及更多的傳統內容。
3、減少風險的需要受到內部政策和遵守外部法規的影響，要求數據存儲的時間更長。
IT經理們不太關心這種指數級數據增長的原因，更關心如何存儲這些數據。這種工作在備份和歸檔存儲領域尤爲繁重，因爲公司數據被保存的時間更長。對於組織來說，關鍵挑戰就在於，平衡存儲需求和預算需求，滿足業務需求並保護公司數據免受許多可能導致災難性數據丟失的威脅。
最後的想法
磁盤和磁帶的角色已經在數據中心中“東山再起”，在實現最佳實踐策略方面是一個補充。組織能夠利用磁盤和閃存的高性能來處理關鍵業務數據，並利用磁帶來實現其優越的密度、壽命和經濟性。
在許多環境中，磁帶不再是具有嚴格恢復和訪問需求的重要應用程序的主要備份目標。然而，它繼續保持其作爲應用程序的主要備份和歸檔目標的角色，其要求不那麼嚴格，而且對數據保護和總體擁有成本（TCO）都是如此。
磁帶在現代存儲架構中扮演着重要的角色，在這種架構中，數據中心的密度需要跟上當今組織所面臨的指數級數據增長。將舊的備份從更昂貴的基於磁盤的存儲媒介遷移出來，具有一定的成本效益。如果需要存儲存檔數據很長一段時間，磁帶應該是成本最低和最可靠的數據保護媒介。

機房建置，如今的企業或組織，都非常依賴於他們的計算機系統和他們存儲的信息。數據繼續呈指數增長，對數據存儲的需求也持續增強。
其實數據存儲已成爲了熱門話題，因爲組織需要考慮如何存儲他們正在生成的海量數據。用戶所產生的內容的增加，以及來自法規遵從性的不斷增加的壓力，導致信息存儲在未來很長時間內都是重點。
僅僅增加更多的存儲容量來滿足這種數據增長，對於那些需要壓縮預算、物理空間、電力和管理資源的組織來說，已經不再是一種可行策略。於是出現了一些根據高密度和低功耗原則而建立的現代存儲解決方案。
一個現代存儲基礎設施
有沒有一種新的技術或策略可以幫助企業克服那些超過了他們預算的數據增長所帶來的挑戰？答案是：沒有。不過，有一種已經存在了相當長一段時間的技術，它能夠滿足當今組織的所有存儲需求。
有些希望實現現代存儲體系結構的組織，發現自己可以利用閃存、磁盤和磁帶來創建存儲基礎設施，從而能夠在訪問速度和負擔能力的平衡下存儲數據。在這個案例中，磁帶提供了最大的密度和最低的功耗。
近年來，磁帶被認爲是一種瀕死的數據中心技術，但是隨着數據和存儲環境的不斷髮展，由於其高密度和低能耗，仍然保持着相關性。雖然基於磁盤的解決方案常常被考慮用於數據保護場景，與傳統的磁帶截然相反，但是對於大多數組織來說，重要的問題並不是在兩種技術之間進行選擇，而是如何在現代的存儲架構中有效地使用它們。
簡單地說，存儲的決定應該來自於一個平衡的“等式”，其中包括業務需求和每個存儲設備的投資回報 （ROI）最大化。
爆發式數據增長的原因
很長一段時間內，各種規模的組織都需要努力應對越來越多的“關鍵商業信息”和“其他信息”。這一非同尋常的數據增長背後有很多原因，這在組織中有所不同，但主要涉及以下方面：
1、組織要求對產品、服務和客戶提供更詳細的信息，這些信息將影響業務策略、驅動增長和提高服務水平（業務應用程序和數據倉庫）。
2、用戶驅動的非結構化內容增長，如圖像、視頻和音頻，以及更多的傳統內容。
3、減少風險的需要受到內部政策和遵守外部法規的影響，要求數據存儲的時間更長。
IT經理們不太關心這種指數級數據增長的原因，更關心如何存儲這些數據。這種工作在備份和歸檔存儲領域尤爲繁重，因爲公司數據被保存的時間更長。對於組織來說，關鍵挑戰就在於，平衡存儲需求和預算需求，滿足業務需求並保護公司數據免受許多可能導致災難性數據丟失的威脅。
最後的想法
磁盤和磁帶的角色已經在數據中心中“東山再起”，在實現最佳實踐策略方面是一個補充。組織能夠利用磁盤和閃存的高性能來處理關鍵業務數據，並利用磁帶來實現其優越的密度、壽命和經濟性。
在許多環境中，磁帶不再是具有嚴格恢復和訪問需求的重要應用程序的主要備份目標。然而，它繼續保持其作爲應用程序的主要備份和歸檔目標的角色，其要求不那麼嚴格，而且對數據保護和總體擁有成本（TCO）都是如此。
磁帶在現代存儲架構中扮演着重要的角色，在這種架構中，數據中心的密度需要跟上當今組織所面臨的指數級數據增長。將舊的備份從更昂貴的基於磁盤的存儲媒介遷移出來，具有一定的成本效益。如果需要存儲存檔數據很長一段時間，磁帶應該是成本最低和最可靠的數據保護媒介。

Datacenter migration, enterprise leasing data center space demand driving factors continue to develop.With this ongoing change, more than 700 decision makers responsible for selecting enterprise IT and storage services were involved in a study commissioned by Vertiv to further understand this sustained and stable development.
The study, conducted by Research firm 451 Research, aims to better understand the changing nature of space demand in rental data centers.If one looks back to the early 2000s, most of the demand for rental data center space comes from telecoms operators.However, people can now see greater demand from service providers, including public cloud providers and businesses looking for space to include higher-level services.
While analysts, investors and pundits have predicted that the trend will reduce the demand for rental data center space, these views do not take into account the potential future demand from wider Internet of things adoption.Nor do they take into account the need for hybrid data center space, nor the trend of not all workloads now moving to the cloud, for many reasons.
Future opportunities
As the report makes clear, the data center demand outlook is not entirely negative.The following seven major findings will drive current and future demand for rental data center space and how they will affect multi-tenant data center (MTDC) providers.
Continuous cloud adoption
In less than a decade, cloud computing has moved from the edge of the market to the mainstream. With the widespread adoption of cloud computing, companies have been shifting IT from internal data centers to external hosting, hosting private clouds, and public cloud environments.While each enterprise on average retains 40 percent of its workload in internally deployed data centers, and up to 36 percent in non-cloud environments, most respondents plan to increase their use of private and public clouds over the next two years.
The development of the Internet of things will further drive demand for data centers
Iot adoption was widespread among the 700 respondents surveyed, with only a tiny 2% of respondents saying they were not involved in any iot projects.It is clear that enterprise applications are still in the early stages of the iot maturity curve, with about two-thirds (64%) of respondents saying that their current iot activity phase is defined as "" in testing or planning" ".
Iot projects often require multiple locations for data analysis and storage.These include: endpoint devices with integrated computing/storage, intelligent gateway devices, nearby devices that perform local computing, internal deployment data centers, hosting facilities, hosting web sites, and the presence point location of network providers.
Not only do various hosting destinations exist for data analysis and storage, many deployments may end up storing, integrating, and moving data in a combination of public clouds and other commercial facilities, including hosting sites and/or network providers.
The promise of expanding the Internet of things
Respondents said that while most businesses are now in the early stages of iot projects, a significant amount of IT capacity is currently used for iot.Surprisingly, 54% of respondents said that between 26% and 75% of their current IT business support iot plans.Looking ahead to the next two years, 73 percent of respondents said they expect as much as three quarters (75 percent) of their data center and cloud computing capacity to be used to support iot plans.
Analysis workloads that drive computational requirements
In addition to the cloud computing that allows the iot process data storage, it also allows the processing of iot data, which is another great opportunity for data center providers.The public cloud is currently the most popular cloud platform (39%) for analyzing iot generated data, but it is by no means the only cloud platform.In fact, data processing is allocated between the hosting facilities (30%), attached to the local computing devices of the data generator (30%), in the network operator infrastructure (31%), and in the internal data center (35%).
Workload and provider
The nature of iot workloads also affects the location of iot data storage and processing.Slightly less than half (48%) mentioned that quality control/tracking systems are most likely to be processed near the data source.To meet this requirement, the micromodular data center is likely to become more prominent in addition to the relatively close multi-tenant data center (MTDC).
An undecided opportunity
For multi-tenant and micro-modular data center providers, undefined organizations in iot infrastructure represent market opportunities.
A quarter of respondents said public cloud providers were the top choice for iot storage and processing for infrastructure providers.There are fairly balanced differences between public clouds, with some respondents also choosing public clouds, private clouds and collocated data centers (21 percent).In addition, 28 percent of respondents chose services provided by network operators (14 percent) or hosted service providers (14 percent).
At the edge of the fog calculation
The OpenFog alliance defines fog computing as "a system-level architecture that allocates computing, storage, control, and network resources and services anywhere in the continuum from cloud computing to the Internet of things."
Of those respondents, there were some very early adopters, with up to 45 percent saying they were "" familiar" "or" "very familiar" "with the OpenFog alliance.The main market driver of fog computing is real-time analysis of data streams, which was chosen by more than a quarter (26 per cent) of respondents, followed by lower network return trip costs (24 per cent) and improved application reliability (21 per cent).
The key points
Based on these premises, the survey report further identified eight key points for multi-tenant data center (MTDC) providers:
(1) streamlining public cloud use or making it safer for hosted services and private cloud options are becoming increasingly important for customers.
(2) as demand for off-site deployments grows, multi-tenant data center (MTDC) providers with interconnected or hosted services will benefit greatly.
(3) hosting providers and telecom operators are in a unique position to address the specific challenges of public cloud.
(4) iot is an opportunity that data center capacity service providers should not ignore.
(5) the emergence of the Internet of things has created a new battlefield for computing power positioning.
(6) the Internet of things will bring applications and workloads that require near real-time response (low latency), which determines that computing capacity may be closer to the edge of the network or devices to minimize transmission delay impact.
(7) fog computing/edge computing market will bring important cooperation opportunities.
(8) marketing focuses on disseminating data center services that support critical fog computing/edge computing.
In addition to these key points, data center providers should also pay special attention to vertical industries and iot support in the countries/regions with the highest proportion in the mature planning stage.For example, the study found that Italy has the highest percentage of external organizations using cloud computing (67 percent), while China is most active in using web hosting as an iot data storage environment in the coming year.The biggest shift related to iot data storage is away from enterprise-owned data center facilities.While 71 per cent of the companies surveyed now store iot data internally, that number is expected to fall to 27 per cent in a year.
If one thing is clear, developments in cloud computing and the Internet of things will have a significant impact on data center demand.If data center providers are open to the opportunities these emerging technologies offer and the demand-driven power of renting data center space, it will enable them to enter new markets and stay ahead of the competition.

Datacenter migration, enterprise leasing data center space demand driving factors continue to develop.With this ongoing change, more than 700 decision makers responsible for selecting enterprise IT and storage services were involved in a study commissioned by Vertiv to further understand this sustained and stable development.
The study, conducted by Research firm 451 Research, aims to better understand the changing nature of space demand in rental data centers.If one looks back to the early 2000s, most of the demand for rental data center space comes from telecoms operators.However, people can now see greater demand from service providers, including public cloud providers and businesses looking for space to include higher-level services.
While analysts, investors and pundits have predicted that the trend will reduce the demand for rental data center space, these views do not take into account the potential future demand from wider Internet of things adoption.Nor do they take into account the need for hybrid data center space, nor the trend of not all workloads now moving to the cloud, for many reasons.
Future opportunities
As the report makes clear, the data center demand outlook is not entirely negative.The following seven major findings will drive current and future demand for rental data center space and how they will affect multi-tenant data center (MTDC) providers.
Continuous cloud adoption
In less than a decade, cloud computing has moved from the edge of the market to the mainstream. With the widespread adoption of cloud computing, companies have been shifting IT from internal data centers to external hosting, hosting private clouds, and public cloud environments.While each enterprise on average retains 40 percent of its workload in internally deployed data centers, and up to 36 percent in non-cloud environments, most respondents plan to increase their use of private and public clouds over the next two years.
The development of the Internet of things will further drive demand for data centers
Iot adoption was widespread among the 700 respondents surveyed, with only a tiny 2% of respondents saying they were not involved in any iot projects.It is clear that enterprise applications are still in the early stages of the iot maturity curve, with about two-thirds (64%) of respondents saying that their current iot activity phase is defined as "" in testing or planning" ".
Iot projects often require multiple locations for data analysis and storage.These include: endpoint devices with integrated computing/storage, intelligent gateway devices, nearby devices that perform local computing, internal deployment data centers, hosting facilities, hosting web sites, and the presence point location of network providers.
Not only do various hosting destinations exist for data analysis and storage, many deployments may end up storing, integrating, and moving data in a combination of public clouds and other commercial facilities, including hosting sites and/or network providers.
The promise of expanding the Internet of things
Respondents said that while most businesses are now in the early stages of iot projects, a significant amount of IT capacity is currently used for iot.Surprisingly, 54% of respondents said that between 26% and 75% of their current IT business support iot plans.Looking ahead to the next two years, 73 percent of respondents said they expect as much as three quarters (75 percent) of their data center and cloud computing capacity to be used to support iot plans.
Analysis workloads that drive computational requirements
In addition to the cloud computing that allows the iot process data storage, it also allows the processing of iot data, which is another great opportunity for data center providers.The public cloud is currently the most popular cloud platform (39%) for analyzing iot generated data, but it is by no means the only cloud platform.In fact, data processing is allocated between the hosting facilities (30%), attached to the local computing devices of the data generator (30%), in the network operator infrastructure (31%), and in the internal data center (35%).
Workload and provider
The nature of iot workloads also affects the location of iot data storage and processing.Slightly less than half (48%) mentioned that quality control/tracking systems are most likely to be processed near the data source.To meet this requirement, the micromodular data center is likely to become more prominent in addition to the relatively close multi-tenant data center (MTDC).
An undecided opportunity
For multi-tenant and micro-modular data center providers, undefined organizations in iot infrastructure represent market opportunities.
A quarter of respondents said public cloud providers were the top choice for iot storage and processing for infrastructure providers.There are fairly balanced differences between public clouds, with some respondents also choosing public clouds, private clouds and collocated data centers (21 percent).In addition, 28 percent of respondents chose services provided by network operators (14 percent) or hosted service providers (14 percent).
At the edge of the fog calculation
The OpenFog alliance defines fog computing as "a system-level architecture that allocates computing, storage, control, and network resources and services anywhere in the continuum from cloud computing to the Internet of things."
Of those respondents, there were some very early adopters, with up to 45 percent saying they were "" familiar" "or" "very familiar" "with the OpenFog alliance.The main market driver of fog computing is real-time analysis of data streams, which was chosen by more than a quarter (26 per cent) of respondents, followed by lower network return trip costs (24 per cent) and improved application reliability (21 per cent).
The key points
Based on these premises, the survey report further identified eight key points for multi-tenant data center (MTDC) providers:
(1) streamlining public cloud use or making it safer for hosted services and private cloud options are becoming increasingly important for customers.
(2) as demand for off-site deployments grows, multi-tenant data center (MTDC) providers with interconnected or hosted services will benefit greatly.
(3) hosting providers and telecom operators are in a unique position to address the specific challenges of public cloud.
(4) iot is an opportunity that data center capacity service providers should not ignore.
(5) the emergence of the Internet of things has created a new battlefield for computing power positioning.
(6) the Internet of things will bring applications and workloads that require near real-time response (low latency), which determines that computing capacity may be closer to the edge of the network or devices to minimize transmission delay impact.
(7) fog computing/edge computing market will bring important cooperation opportunities.
(8) marketing focuses on disseminating data center services that support critical fog computing/edge computing.
In addition to these key points, data center providers should also pay special attention to vertical industries and iot support in the countries/regions with the highest proportion in the mature planning stage.For example, the study found that Italy has the highest percentage of external organizations using cloud computing (67 percent), while China is most active in using web hosting as an iot data storage environment in the coming year.The biggest shift related to iot data storage is away from enterprise-owned data center facilities.While 71 per cent of the companies surveyed now store iot data internally, that number is expected to fall to 27 per cent in a year.
If one thing is clear, developments in cloud computing and the Internet of things will have a significant impact on data center demand.If data center providers are open to the opportunities these emerging technologies offer and the demand-driven power of renting data center space, it will enable them to enter new markets and stay ahead of the competition.

機房建置，供配電系統作爲數據中心業務不間斷運行的基礎設施，面臨着嚴峻的挑戰,，一旦出現故障將導致巨大的損失。如何快速地將電池故障排除掉,防患於未然？低負載下的數據中心電費居高不下，如何破解？傳統UPS不間斷電源運維複雜，管理苦難，如何解決？雲融合時代對數據中心供配電系統有何要求？
面對以上問題，華爲模塊化UPS不間斷電源有話說。華爲在電源領域有着20年+的深厚技術，積累了深厚的市場經驗。華爲模塊化UPS不間斷電源作爲網絡能源的核心產品，具有以下優秀特質：
#高可靠#：全冗餘架構打造系統高可靠。從控制模塊冗餘,功率模塊冗餘到雙總線冗餘設計,消除系統單點故障；
#高效率#：華爲模塊化UPS不間斷電源系統效率高達97.1%,模塊效率高達97.5%。同時,保證系統在低載區域持續高效運行,20%負載率下效率爲96.5%,40%負載率下爲97.1%,匹配當前大部分數據中心的運行負載率區域。效率的提升就意味着電費的節省,1個點的效率提升,則將在生命週期幾乎節省出設備投資成本；
#簡單運維#：模塊化UPS不間斷電源不需要專家維護,普通工程師即可運維,功率模塊通過在線熱插拔,5min之內,兩人即可完成更換。相比於塔式UPS不間斷電源複雜的原廠專業複雜運維,節省大量的運維時間和費用。
作爲新器件，要通過華爲嚴格的選型流程才能引入：
*引入元件後，要進行可靠性測試
*進入生產時，要進行來料管控，進行IQC抽檢
*每一步的生成測試和管控，從PCB到單板、到模塊、到整機
*針對市場運行情況進行失效分析、短板改進等等，應對客戶問題
華爲UPS秉承華爲強大的技術研發實力以及嚴苛的質量保障體系，經過超過1400項標準測試，21項專項可靠性試驗保證產品質量，並在傳統電力電子技術基礎上融合了數字信息技術，有效改善了可擴展性與可用性。華爲高頻模塊化UPS不間斷電源採用在線式雙變換和部件模塊化冗餘設計，基於DSP（數字信號處理）全數字化控制，可靠性高、功率密度高。同時，華爲模塊化UPS不間斷電源功率模塊，監控模塊，旁路模塊、控制模塊均支持熱插拔，安裝、擴容、維護簡單，支持關鍵部件失效預警功能，防止故障擴大，能夠提供穩定可靠電力保障。
華爲網絡能源營銷運作總裁李俊朋表示："各行各業的數字化轉型對數據中心基礎設施提出了巨大的挑戰，面對龐大的業務處理需求，高可靠的供配電解決方案是業務零中斷的根本保障。華爲模塊化UPS不間斷電源通過數字化、網絡化手段實現了智能管理，能更好地支撐客戶未來業務的發展。"
華爲模塊化UPS不間斷電源近年來的表現可圈可點，全球市場份額呈現快速上升趨勢，這主要得益於華爲在該領域的持續投入與研發。它曾獲得2016年模塊化UPS不間斷電源年度最佳公司、2016年德國DCI供配電領域鉑金獎等榮譽。同時，華爲供配電解決方案已在全球廣泛商用，覆蓋政府、ISP、交通、金融等多個關鍵行業，並在歐洲、南太等地區的諸多國家贏得了多個客戶的信任，並保持了長期穩固的合作伙伴關係，爲全球用戶提供智能全方位的動力保障。

機房建置，供配電系統作爲數據中心業務不間斷運行的基礎設施，面臨着嚴峻的挑戰,，一旦出現故障將導致巨大的損失。如何快速地將電池故障排除掉,防患於未然？低負載下的數據中心電費居高不下，如何破解？傳統UPS不間斷電源運維複雜，管理苦難，如何解決？雲融合時代對數據中心供配電系統有何要求？
面對以上問題，華爲模塊化UPS不間斷電源有話說。華爲在電源領域有着20年+的深厚技術，積累了深厚的市場經驗。華爲模塊化UPS不間斷電源作爲網絡能源的核心產品，具有以下優秀特質：
#高可靠#：全冗餘架構打造系統高可靠。從控制模塊冗餘,功率模塊冗餘到雙總線冗餘設計,消除系統單點故障；
#高效率#：華爲模塊化UPS不間斷電源系統效率高達97.1%,模塊效率高達97.5%。同時,保證系統在低載區域持續高效運行,20%負載率下效率爲96.5%,40%負載率下爲97.1%,匹配當前大部分數據中心的運行負載率區域。效率的提升就意味着電費的節省,1個點的效率提升,則將在生命週期幾乎節省出設備投資成本；
#簡單運維#：模塊化UPS不間斷電源不需要專家維護,普通工程師即可運維,功率模塊通過在線熱插拔,5min之內,兩人即可完成更換。相比於塔式UPS不間斷電源複雜的原廠專業複雜運維,節省大量的運維時間和費用。
作爲新器件，要通過華爲嚴格的選型流程才能引入：
*引入元件後，要進行可靠性測試
*進入生產時，要進行來料管控，進行IQC抽檢
*每一步的生成測試和管控，從PCB到單板、到模塊、到整機
*針對市場運行情況進行失效分析、短板改進等等，應對客戶問題
華爲UPS秉承華爲強大的技術研發實力以及嚴苛的質量保障體系，經過超過1400項標準測試，21項專項可靠性試驗保證產品質量，並在傳統電力電子技術基礎上融合了數字信息技術，有效改善了可擴展性與可用性。華爲高頻模塊化UPS不間斷電源採用在線式雙變換和部件模塊化冗餘設計，基於DSP（數字信號處理）全數字化控制，可靠性高、功率密度高。同時，華爲模塊化UPS不間斷電源功率模塊，監控模塊，旁路模塊、控制模塊均支持熱插拔，安裝、擴容、維護簡單，支持關鍵部件失效預警功能，防止故障擴大，能夠提供穩定可靠電力保障。
華爲網絡能源營銷運作總裁李俊朋表示："各行各業的數字化轉型對數據中心基礎設施提出了巨大的挑戰，面對龐大的業務處理需求，高可靠的供配電解決方案是業務零中斷的根本保障。華爲模塊化UPS不間斷電源通過數字化、網絡化手段實現了智能管理，能更好地支撐客戶未來業務的發展。"
華爲模塊化UPS不間斷電源近年來的表現可圈可點，全球市場份額呈現快速上升趨勢，這主要得益於華爲在該領域的持續投入與研發。它曾獲得2016年模塊化UPS不間斷電源年度最佳公司、2016年德國DCI供配電領域鉑金獎等榮譽。同時，華爲供配電解決方案已在全球廣泛商用，覆蓋政府、ISP、交通、金融等多個關鍵行業，並在歐洲、南太等地區的諸多國家贏得了多個客戶的信任，並保持了長期穩固的合作伙伴關係，爲全球用戶提供智能全方位的動力保障。

Datacenter migration,What is HUAWEI architects doing to the trend of intelligent data center? First of all, let's answer this question: why is it intelligent? No manual inspection?
Really not, because "artificial" as the protagonist of data center operations and maintenance needs too much experience, can only be good after, can not warn, can not achieve fine management. The position of "artificial" in the data center should eventually gradually tend to "execution" instead of "management", and the work of management should rely on the continuous improvement of AI to gradually replace manual work. Modular data center plus intelligence will make the data center more powerful and perfect.
Faced with the intelligence of data center, how did HUAWEI do it?
Through the continuous intelligent upgrading of the self research equipment and the understanding of the L2 layer service, HUAWEI launched an intelligent micro module 3 products around I3 (iPower, iCooling, iManager) features.
Why is it 3? To put it simply, the 1 is hardware integration, the 2 is the combination of software and hardware, and the 3 is the integration of functions. So what functions do these 3 I3 features incorporate? And let me be fine.
IPower guarantee business is not interrupted; dangerous state can be predicted in advance; fire hazard is excluded for the first time.
In terms of intelligence, iPower can mainly achieve:
The power supply full link visual and alarm can locate accurately and identify faults in minutes.
The switch current, voltage and temperature of the power supply branch are monitored comprehensively, and the abnormal state is reported in the morning.
Socket level power supply monitoring, cabinet equipment running state at a glance;
The battery management system monitors key information such as SOH, current, voltage, internal resistance and temperature of each cell.
When the battery and socket devices fail, they can isolate the battery / socket power supply and eliminate fire hazards.
I feel that this understanding is more convenient, that is, Bian Que + Hua Tuo, a hope of knowledge, a drug can scrape bones.
ICooling: refrigeration is not only reliable but also energy efficient.
.AI self-learning algorithm, combined with the temperature and humidity of the channel, through the adjustment of indoor and outdoor fans, compressors, expansion valves, and so on, to achieve energy saving 8%, a year can save tens of tens of thousands of electricity costs;
The temperature cloud chart and the load power are no longer independent functions. ICooling combines the temperature nephogram - cabinet load - temperature control system to realize the double insurance of eliminating real-time hot spot - eliminating hidden trouble of hot spot.
The refrigerant capacity of air-conditioning is no longer half-hidden. One key of iCooling detects the refrigerant capacity to solve the problem of overheating and downtime caused by insufficient refrigerant.
IManager is the brain of smart micromodule 3.0, which not only carries the algorithms of iPower / iCooling, but also makes the operation and maintenance of the computer room easier. The best technology is that people can't feel the existence of technology. IManager is trying to make you:
You can't feel the place that needs to be operated manually. Intelligent lighting, automatic translation door, eLight module status indicator and fire fighting linkage.
I don't feel the trouble of asset management. In the face of quarterly and annual reconciliation of asset statements, asset automation functions can be easily reduced and manual statistics cost reduced.
IManager is more like a perfect housekeeper, earnest and dedicated, meticulous and never lose his duty.
In the future, HUAWEI will continue to explore the intelligent path of the micro module, continuous optimization around the I3 features, to ensure a new generation of data centers with both quality and intelligence for customers.

Datacenter migration,What is HUAWEI architects doing to the trend of intelligent data center? First of all, let's answer this question: why is it intelligent? No manual inspection?
Really not, because "artificial" as the protagonist of data center operations and maintenance needs too much experience, can only be good after, can not warn, can not achieve fine management. The position of "artificial" in the data center should eventually gradually tend to "execution" instead of "management", and the work of management should rely on the continuous improvement of AI to gradually replace manual work. Modular data center plus intelligence will make the data center more powerful and perfect.
Faced with the intelligence of data center, how did HUAWEI do it?
Through the continuous intelligent upgrading of the self research equipment and the understanding of the L2 layer service, HUAWEI launched an intelligent micro module 3 products around I3 (iPower, iCooling, iManager) features.
Why is it 3? To put it simply, the 1 is hardware integration, the 2 is the combination of software and hardware, and the 3 is the integration of functions. So what functions do these 3 I3 features incorporate? And let me be fine.
IPower guarantee business is not interrupted; dangerous state can be predicted in advance; fire hazard is excluded for the first time.
In terms of intelligence, iPower can mainly achieve:
The power supply full link visual and alarm can locate accurately and identify faults in minutes.
The switch current, voltage and temperature of the power supply branch are monitored comprehensively, and the abnormal state is reported in the morning.
Socket level power supply monitoring, cabinet equipment running state at a glance;
The battery management system monitors key information such as SOH, current, voltage, internal resistance and temperature of each cell.
When the battery and socket devices fail, they can isolate the battery / socket power supply and eliminate fire hazards.
I feel that this understanding is more convenient, that is, Bian Que + Hua Tuo, a hope of knowledge, a drug can scrape bones.
ICooling: refrigeration is not only reliable but also energy efficient.
.AI self-learning algorithm, combined with the temperature and humidity of the channel, through the adjustment of indoor and outdoor fans, compressors, expansion valves, and so on, to achieve energy saving 8%, a year can save tens of tens of thousands of electricity costs;
The temperature cloud chart and the load power are no longer independent functions. ICooling combines the temperature nephogram - cabinet load - temperature control system to realize the double insurance of eliminating real-time hot spot - eliminating hidden trouble of hot spot.
The refrigerant capacity of air-conditioning is no longer half-hidden. One key of iCooling detects the refrigerant capacity to solve the problem of overheating and downtime caused by insufficient refrigerant.
IManager is the brain of smart micromodule 3.0, which not only carries the algorithms of iPower / iCooling, but also makes the operation and maintenance of the computer room easier. The best technology is that people can't feel the existence of technology. IManager is trying to make you:
You can't feel the place that needs to be operated manually. Intelligent lighting, automatic translation door, eLight module status indicator and fire fighting linkage.
I don't feel the trouble of asset management. In the face of quarterly and annual reconciliation of asset statements, asset automation functions can be easily reduced and manual statistics cost reduced.
IManager is more like a perfect housekeeper, earnest and dedicated, meticulous and never lose his duty.
In the future, HUAWEI will continue to explore the intelligent path of the micro module, continuous optimization around the I3 features, to ensure a new generation of data centers with both quality and intelligence for customers.

機房建置，隨着數據中心網絡不斷擴展，客戶增添越來越多的服務器和交換機，以及服務器虛擬化後虛擬機的動態遷移，會使得現有扁平式的二層網絡更加龐大，這就要求在二層實現多路徑功能來提高網絡效率和可靠性，也就是說數據中心網絡還必須能夠支持大型的扁平化設計。IETF組織制定的大量鏈路透明互聯（TRILL）標準提供了這一能力。VDX系列交換機即是基於TRILL協議下支持DCB以太網的革命性的下一代交換機。
虛擬集羣交換（VCS）解決方案簡析
虛擬集羣交換技術（VCS™）是一種2/3層以太網技術，包含了一系列新的標準及高級特性，可以提供更高的帶寬利用率、更高的網絡可擴展性、對網絡融合的無縫支持及管理簡便性。VCS技術的核心是三大技術“支柱”：以太網Fabric架構、分佈式智能和邏輯機箱。
以太網Fabric架構利用新的IETF多鏈路透明互連（TRILL）協議來消除對生成樹協議（STP）的需求，因爲它可以在兼容VCS的不同交換機之間建立多條路徑來傳輸數據中心橋接（DCB）流量。矩陣架構內的所有路徑都是活動的，如果一條鏈路發生故障，流量會以最短的時延自動分配到其它可用的等價路徑上。利用分佈式智能，配置和網絡拓撲信息可以自動分配給矩陣架構內的所有交換機。利用TRILL，矩陣架構可以原封不動地將幀從源端口發送到目標端口，就象整個矩陣架構是一個邏輯交換機機箱，而每個兼容VCS的交換機就象是機箱中的一個端口模塊。這種矩陣架構可在邏輯機箱中擴展到1000多個端口。
VCS架構VS傳統網絡架構
在擴展虛擬服務器環境時，網絡會帶來多方面的挑戰和侷限性，傳統網絡如生成樹（STP）的缺點、低利用率和鏈路故障恢復。
VCS可以爲管理員帶來以下優勢：
· 從邏輯上消除管理多個交換層的需要
· 在多臺物理交換機中執行策略並管理流量，就好象它們是一臺交換機
· 擴展網絡帶寬而不需要以手工方式重新配置交換機端口和網絡策略
· 向服務器、網絡和存儲管理員提供有關網絡狀態的單一定製視圖
VCS技術可幫助IT部門輕鬆應對虛擬化環境中的網絡挑戰。VMware環境中的VCS技術還可以爲IT部門一套可擴展且易於管理的基礎架構來支持雲計算。雲計算已成爲數據中心滿足這些IT要求的全新計算模式。它依靠服務器虛擬化來降低資本和運營支出，提供更安全而且高度可用的計算環境，來縮短應用部署時間，同時提供更高的容量靈活性來滿足不斷變化的需求。服務器虛擬化是計算技術領域的重大進步，其中的虛擬機（VM）包含了提供特定服務所需的所有軟件。VM將硬件和應用分開，使服務可以在任何可用的硬件（只要提供管理程序來運行虛擬機）上運行。雲計算還改變着IT部門的業務模式。IT部門需要基於服務的計算，其中的共享資源連接到應用，成本基於資源消耗情況而不是資產的購買。

機房建置，隨着數據中心網絡不斷擴展，客戶增添越來越多的服務器和交換機，以及服務器虛擬化後虛擬機的動態遷移，會使得現有扁平式的二層網絡更加龐大，這就要求在二層實現多路徑功能來提高網絡效率和可靠性，也就是說數據中心網絡還必須能夠支持大型的扁平化設計。IETF組織制定的大量鏈路透明互聯（TRILL）標準提供了這一能力。VDX系列交換機即是基於TRILL協議下支持DCB以太網的革命性的下一代交換機。
虛擬集羣交換（VCS）解決方案簡析
虛擬集羣交換技術（VCS™）是一種2/3層以太網技術，包含了一系列新的標準及高級特性，可以提供更高的帶寬利用率、更高的網絡可擴展性、對網絡融合的無縫支持及管理簡便性。VCS技術的核心是三大技術“支柱”：以太網Fabric架構、分佈式智能和邏輯機箱。
以太網Fabric架構利用新的IETF多鏈路透明互連（TRILL）協議來消除對生成樹協議（STP）的需求，因爲它可以在兼容VCS的不同交換機之間建立多條路徑來傳輸數據中心橋接（DCB）流量。矩陣架構內的所有路徑都是活動的，如果一條鏈路發生故障，流量會以最短的時延自動分配到其它可用的等價路徑上。利用分佈式智能，配置和網絡拓撲信息可以自動分配給矩陣架構內的所有交換機。利用TRILL，矩陣架構可以原封不動地將幀從源端口發送到目標端口，就象整個矩陣架構是一個邏輯交換機機箱，而每個兼容VCS的交換機就象是機箱中的一個端口模塊。這種矩陣架構可在邏輯機箱中擴展到1000多個端口。
VCS架構VS傳統網絡架構
在擴展虛擬服務器環境時，網絡會帶來多方面的挑戰和侷限性，傳統網絡如生成樹（STP）的缺點、低利用率和鏈路故障恢復。
VCS可以爲管理員帶來以下優勢：
· 從邏輯上消除管理多個交換層的需要
· 在多臺物理交換機中執行策略並管理流量，就好象它們是一臺交換機
· 擴展網絡帶寬而不需要以手工方式重新配置交換機端口和網絡策略
· 向服務器、網絡和存儲管理員提供有關網絡狀態的單一定製視圖
VCS技術可幫助IT部門輕鬆應對虛擬化環境中的網絡挑戰。VMware環境中的VCS技術還可以爲IT部門一套可擴展且易於管理的基礎架構來支持雲計算。雲計算已成爲數據中心滿足這些IT要求的全新計算模式。它依靠服務器虛擬化來降低資本和運營支出，提供更安全而且高度可用的計算環境，來縮短應用部署時間，同時提供更高的容量靈活性來滿足不斷變化的需求。服務器虛擬化是計算技術領域的重大進步，其中的虛擬機（VM）包含了提供特定服務所需的所有軟件。VM將硬件和應用分開，使服務可以在任何可用的硬件（只要提供管理程序來運行虛擬機）上運行。雲計算還改變着IT部門的業務模式。IT部門需要基於服務的計算，其中的共享資源連接到應用，成本基於資源消耗情況而不是資產的購買。