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市场调查报告书
商品编码
1850137

资料中心自动化：市场占有率分析、产业趋势、统计资料和成长预测（2025-2030 年）

Data Center Automation - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2025 - 2030)
出版日期: | 出版商: Mordor Intelligence | 英文 120 Pages | 商品交期: 2-3个工作天内

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简介目录

资料中心自动化市场规模预计到 2025 年将达到 104.8 亿美元，预计到 2030 年将达到 238 亿美元，在此期间的复合年增长率为 17.83%。

资料中心自动化市场-IMG1

在对云端平台依赖性日益增强、人工智慧工作负载呈现爆炸性成长以及降低能耗压力不断增加的推动下，自动化正从营运层面的便利措施转变为董事会层面的强制性要求。超大规模资料中心的建设推动了对软体定义编配的需求，以在降低电力成本的同时维持服务品质。同时，模组化设计和液冷系统的部署需要精细化的即时控制，而这只有自动化系统才能实现。供应商透过整合能够自我调整基础设施并预测硬体故障​​的人工智慧引擎，加速了竞争，从而显着节省了人工、能源和停机时间。此外，美国能源局报告预测，到2028年，资料中心的电力需求可能会翻倍甚至两番，而人工智慧应用将是推动这一成长的主要动力，这使得能够优化能源使用的自动化解决方案的需求变得迫切。日益成熟的电网互动计划进一步促进了自动化解决方案的普及，这些计划奖励运营商转移负载并将能源灵活性转化为收入来源。

全球资料中心自动化市场趋势与洞察

云端运算和超大规模建筑的激增

到2025年，超大规模园区投资计画超过2,500亿美元，自动化需求涵盖容量规划、温度控管和即时工作负载迁移等各个面向。营运商正在围绕人工智慧主导的控制器设计设施，这些控制器能够即时分配运算、电力和冷却资源，以在最大限度减少人工干预的情况下满足服务等级需求。如今，资本密集的扩充功能透过预先接线和预先测试的模组化模组进行协调，这需要编配软体来即时发现、基准并整合每个模组。全球供应商正在透过基于意图的平台来响应这一需求，这些平台可以跨越数千个资产应用策略，从而将建置速度转化为竞争优势。

对节能和永续营运的需求

目前，资料中心的用电量占全球总用电量的1%至3%，但随着人工智慧的加速应用，预计到2030年这一比例将上升至5%。诸如欧洲气候中和资料中心协议等严格倡议将新建资料中心的PUE（电源使用效率）上限设定为1.3，鼓励业者采用自动化系统，持续调整气流、风扇转速和工作负载布局。在早期部署中，人工智慧控制系统已将冷却能耗降低高达40%，而能够证明其碳减检验的营运商正在吸引那些必须满足自身ESG（环境、社会和治理）目标的超大规模租户。自动化的永续性报告进一步降低了合规成本，并提高了与监管机构沟通的透明度。

旧有系统互通性障碍

许多运营商仍然使用专有硬件，其API有限，迫使他们在现代编配得以应用之前，必须使用成本高昂的定制连接器。网路团队往往因为担心配置错误导致脚本中断，而对处理关键业务流量的核心交换器的自动化犹豫不决。传统设施缺乏标准化设计进一步加剧了部署的复杂性，因为为一个站点建置的模板很少能顺利移植到其他站点。供应商正在透过丰富的插件市场和基于人工智慧的设备配置逆向工程工具来应对这项挑战，但对于技术债权沉重的企业而言，迁移週期仍然漫长。

细分市场分析

到2024年，伺服器自动化将占据资料中心自动化市场51.8%的份额，而网路自动化预计到2030年将以19.20%的复合年增长率成长，成为成长最快的市场。网路专用平台的成长反映了微服务、容器丛集和东西向流量模式的普及导致手动命令列变更的主导地位。企业正在转向使用能够将业务意图转化为设备配置并透过闭合迴路遥测检验结果的控制器。这种转变释放了可程式服务品质（QoS）、微隔离和自动回滚功能，从而减少了停机事件的发生。

从中长期来看，编配套件会将组态管理、效能分析和合规性检查等以往各自独立的功能整合到一个由基于角色的存取控制的整合工具链中。人工智慧驱动的诊断功能将识别延迟的根本原因并提案修復建议，从而缩短平均故障解决时间。因此，企业主管开始将网路自动化视为策略性投资，而非成本中心。到了2026年，30%的企业计划实现至少一半网路活动的自动化，这为意图式网路的广泛应用奠定基础。

到2024年，三级资料中心将占资料中心自动化市场规模的45.20%，而四级资料中心预计将以18.34%的复合年增长率成长，因为它们预期正常执行时间将达到99.995%。四级资料中心编配依赖精心设计的容错移转流程、即时健康评分和自癒网状架构。自动化诊断系统每分钟对冗余路径和环境感测器进行数千次测试，从而实现零件的预先更换和负载转移。

相反，预算限制促使一级和二级站点采取选择性自动化，重点是备份调度和修补程式管理。然而，软体成本的下降和模组化控制器设计的出现降低了进入门槛。灾难復原编配正成为一项普遍优先事项：自动化运作手册现在每月无需人工干预即可测试容错移转序列，从而保障收入并满足审核要求。这些功能正在逐步缩小不同层级站点之间的营运差距，​​并提高整个产业的基本期望。

资料中心自动化市场按解决方案类型（伺服器自动化、网路自动化等）、资料中心层级（Tier 1 和 Tier 2、Tier 3、Tier 4）、部署模式（本地部署、云端部署）、资料中心类型（超大规模/云端服务供应商、託管服务提供者等）和地区进行细分。市场预测以美元计价。

区域分析

受云端运算普及和雄厚资本的推动，北美地区预计在2024年仍将占据资料中心自动化市场46.30%的份额。北维吉尼亚等核心区域电力供应紧张，促使企业更加关注电网互动自动化，以最大限度地利用可用电力。联邦政府的研究表明，到2028年资料中心电力需求可能翻一番，这推动了企业对能够最大限度减少閒置能耗并透过需量反应计画实现灵活性的平台的兴趣。企业永续性目标也进一步推动了人工智慧辅助冷却和容量规划工具的广泛应用。

亚太地区是成长最快的地区，预计2025年至2030年的复合年增长率将达到19.45%。中国、日本和印度的国家级倡议正在鼓励建造本地云端区域和边缘运算，推动了自动化需求，以弥补劳动力短缺。泰国和印尼的大型计划涉及数十亿美元的投资，这些专案将液冷技术与可再生能源结合，从一开始就需要一个编配层来整合不同的技术。

欧洲拥有成熟的资料中心和严格的环境法规，是先进永续自动化技术的温床。 2030年实现气候中和设施的承诺促使营运商将PUE值维持在1.3或以下，并实施持续优化引擎以检验可再生能源的使用。需量反应参与和余热再利用计划的奖励进一步增强了其商业价值。沙乌地阿拉伯、阿联酋和南非的大型计划需要净零排放示范点和自主运行，以克服偏远地区人员配备不足的问题，因此自动化成为融资和吸引租户的先决条件。

其他福利：

  • Excel格式的市场预测（ME）表
  • 3个月的分析师支持

目录

第一章 引言

  • 研究假设和市场定义
  • 调查范围

第二章调查方法

第三章执行摘要

第四章 市场情势

  • 市场概览
  • 市场驱动因素
    • 云端运算和超大规模建筑的激增
    • 对能源效率和永续营运的需求
    • 对人工智慧/机器学习工作负载自动化的需求日益增长
    • 混合云和多重云端架构的复杂性
    • 以资料中心为导向的 Grid Interactive奖励计划
    • 新兴经济体的边缘定位
  • 市场限制
    • 旧有系统互通性障碍
    • 网路安全和合规风险日益加剧
    • 网路维运/自动化人才短缺
    • 主要地区出现电力和供水短缺
  • 供应链分析
  • 监管环境
  • 技术展望
  • 波特五力分析
    • 供应商的议价能力
    • 买方的议价能力
    • 新进入者的威胁
    • 替代品的威胁
    • 竞争对手之间的竞争
  • 对宏观经济趋势的市场评估
  • 永续性和碳中和倡议
  • 容量和电力需求分析

第五章 市场规模与成长预测

  • 透过解决方案
    • 伺服器自动化
    • 网路自动化
    • 储存/资料库自动化
    • 编配与设定管理
    • 绩效与合规管理
  • 按资料中心层级类型
    • 一级和二级
    • 三级
    • 第四级
  • 透过部署模式
    • 本地部署
    • 云
  • 依资料中心类型
    • 超大规模资料中心业者云端伺服器供应商
    • 託管服务提供者
    • 企业和边缘运算
  • 按地区
    • 北美洲
      • 美国
      • 加拿大
      • 墨西哥
    • 欧洲
      • 英国
      • 德国
      • 法国
      • 义大利
      • 西班牙
      • 其他欧洲地区
    • 亚太地区
      • 中国
      • 日本
      • 印度
      • 新加坡
      • 澳洲
      • 马来西亚
      • 亚太其他地区
    • 南美洲
      • 巴西
      • 智利
      • 阿根廷
      • 其他南美洲
    • 中东
      • 阿拉伯聯合大公国
      • 沙乌地阿拉伯
      • 土耳其
      • 其他中东地区
    • 非洲
      • 南非
      • 奈及利亚
      • 其他非洲地区

第六章 竞争情势

  • 市场集中度
  • 策略趋势
  • 市占率分析
  • 公司简介
    • Cisco Systems Inc.
    • VMware Inc.
    • Microsoft Corporation
    • IBM Corporation
    • Hewlett Packard Enterprise（HPE）
    • Dell Technologies Inc.
    • BMC Software Inc.
    • ServiceNow Inc.
    • Oracle Corporation
    • Fujitsu Ltd.
    • Juniper Networks Inc.
    • ABB Ltd.
    • Citrix Systems Inc.
    • Chef Software Inc.（Progress Software）
    • Brocade Communications Systems
    • HashiCorp Inc.
    • Puppet Labs LLC
    • Micro Focus Intl. plc
    • Huawei Technologies Co. Ltd.
    • Schneider Electric SE
    • NetApp Inc.

第七章 市场机会与未来展望

简介目录
Product Code: 54894

The data center automation market size is estimated at USD 10.48 billion in 2025 and is forecast to reach USD 23.80 billion by 2030, registering a 17.83% CAGR over the period.

Data Center Automation - Market - IMG1

Rising reliance on cloud platforms, surging AI workloads, and growing pressure to reduce energy footprints are moving automation from an operational convenience to a board-level mandate. Hyperscale build-outs have intensified the need for software-defined orchestration that maintains service quality while trimming power bills. In parallel, modular designs and liquid-cooling rollouts demand fine-grained, real-time controls that only automated systems can deliver. Competitive intensity is accelerating as vendors embed AI engines that self-tune infrastructure and predict hardware failures, yielding measurable savings on labor, energy, and downtime. Further, the U.S. Department of Energy reports that data center electricity demand could double or triple by 2028, with AI applications driving much of this growth, creating urgent pressure for automation solutions that can optimize energy usage. Adoption is further strengthened by maturing grid-interactive programs that pay operators to shift loads, turning energy flexibility into a revenue stream.

Global Data Center Automation Market Trends and Insights

Surge in cloud and hyperscale build-outs

Hyperscale campuses scheduled for 2025 investment exceed USD 250 billion, creating an automation imperative that spans capacity planning, thermal management, and live migration of workloads. Operators are designing facilities around AI-driven controllers able to allocate compute, power, and cooling resources in seconds, matching service-level demands while shaving operator intervention to a minimum. Capital-intensive expansions are now coupled with modular blocks that ship pre-wired and pre-tested, so orchestration software must instantly discover, baseline, and integrate each block. Global vendors are responding with intent-based platforms that enforce policies across thousands of assets, turning build-out velocity into a competitive weapon.

Demand for energy-efficient and sustainable operations

Datacenters currently use 1-3% of global electricity, and projections suggest the share could rise to 5% by 2030 if AI uptake accelerates. Strict initiatives such as the Climate Neutral Data Centre Pact in Europe set a PUE ceiling of 1.3 for new builds, prompting operators to adopt automation that continually tunes airflows, fan speeds, and workload placements. AI-enhanced controls have already trimmed cooling power by up to 40% in early deployments, and operators showcasing verifiable carbon reductions are attracting hyperscale tenants that must hit their own ESG targets. Automated sustainability reporting is further lowering compliance overheads and improving transparency with regulators.

Legacy system interoperability hurdles

Many operators still run proprietary hardware with limited APIs, forcing costly custom connectors before modern orchestration can take hold. Network teams often hesitate to automate core switches that handle mission-critical traffic, fearing outages from mis-configured scripts. Lack of design standardization across legacy estates further complicates rollouts because templates built for one site rarely port cleanly to another. Vendors are responding with extensive plugin marketplaces and AI-based discovery tools that reverse-engineer device configurations, yet migration timelines remain protracted for organizations with deep technical debt

Other drivers and restraints analyzed in the detailed report include:

  1. Rising AI/ML workload automation needs
  2. Complexity of hybrid and multi-cloud architectures
  3. Heightened cyber-security and compliance risks

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Network Automation is the fastest-growing segment with a 19.20% CAGR projected through 2030, although Server Automation retained 51.8% of the data center automation market share in 2024. Growth in network-focused platforms mirrors the proliferation of micro-services, container clusters, and east-west traffic patterns that overwhelm manual command-line changes. Enterprises are shifting to controllers that translate business intent into device configurations, then verify outcomes through closed-loop telemetry. This shift unlocks programmable QoS, micro-segmentation, and automatic rollback capabilities that reduce downtime incidents.

In the medium term, orchestration suites are converging previously separate functions- configuration management, performance analytics, and compliance checks- into unified toolchains governed by role-based access. AI-powered diagnostics pinpoint latency roots and suggest remediations, shortening mean time to resolution. As a result, senior leadership now views network automation as a strategic investment rather than a cost center. Momentum is expected to continue as 30% of enterprises aim to automate at least half of their network activities by 2026, setting the foundation for widespread intent-based networking adoption.

Tier 3 facilities commanded 45.20% of the data center automation market size in 2024, but Tier 4 deployments are on track for an 18.34% CAGR thanks to stringent 99.995% uptime expectations. Operators of Tier 4 campuses rely on orchestrated failover processes, real-time health scoring, and self-healing mesh architectures. Automated diagnostics inspect redundant paths and environmental sensors thousands of times per minute, triggering pre-emptive part swaps or load transfers.

Conversely, Tier 1 and Tier 2 sites pursue selective automation, often focusing on backup scheduling and patch management, due to budget limits. Yet falling software costs and modular controller designs are lowering entry barriers. Disaster-recovery orchestration is becoming a universal priority: Automated runbooks now test failover sequences monthly without human intervention, fulfilling audit requirements while safeguarding revenue. These capabilities gradually narrow the operational disparities between tier levels and raise baseline expectations across the industry.

Data Center Automation Market is Segmented by Solution (Server Automation, Network Automation, and More), by Data Center Tier Type (Tier 1 and 2, Tier 3, and Tier 4), by Deployment Mode (On-Premise, Cloud), by Data Center Type (Hyperscalers/Cloud Service Providers, Colocation Providers, and More), and by Geography. The Market Forecasts are Provided in Terms of Value (USD).

Geography Analysis

North America retained 46.30% of the data center automation market share in 2024, benefiting from deep cloud adoption and access to large capital pools. Power constraints in core corridors such as Northern Virginia sharpen the focus on grid-interactive automation that maximizes every available megawatt. Federal research indicating that data-center electricity demand may double by 2028 magnifies interest in platforms that minimize idle consumption and monetize flexibility through demand-response programs. Corporate sustainability narratives further encourage aggressive deployment of AI-guided cooling and capacity-planning tools.

Asia-Pacific is the fastest-growing territory with a 19.45% CAGR expected between 2025-2030. National initiatives in China, Japan, and India incentivize local cloud zones and edge build-outs, magnifying the need for automation that can compensate for labor shortages. Large-scale projects, including multi-billion-dollar investments in Thailand and Indonesia, bundle liquid-cooling and renewable power sources, demanding orchestration layers able to harmonize disparate technologies from day one.

Europe combines mature colocation hubs with tight environmental regulation, creating a crucible for advanced sustainability automation. Commitments to achieve climate-neutral facilities by 2030 push operators to deploy continuous-optimization engines that maintain sub-1.3 PUE targets and verify renewable-energy usage. Incentives for demand-response participation and heat-re-use schemes reinforce the business case. Growing activity in the Middle East and Africa mirrors this momentum: flagship projects in Saudi Arabia, the United Arab Emirates, and South Africa require net-zero proof points and autonomous operation to overcome remote-site staffing limitations, positioning automation as a prerequisite for securing financing and tenants.

  1. Cisco Systems Inc.
  2. VMware Inc.
  3. Microsoft Corporation
  4. IBM Corporation
  5. Hewlett Packard Enterprise (HPE)
  6. Dell Technologies Inc.
  7. BMC Software Inc.
  8. ServiceNow Inc.
  9. Oracle Corporation
  10. Fujitsu Ltd.
  11. Juniper Networks Inc.
  12. ABB Ltd.
  13. Citrix Systems Inc.
  14. Chef Software Inc. (Progress Software)
  15. Brocade Communications Systems
  16. HashiCorp Inc.
  17. Puppet Labs LLC
  18. Micro Focus Intl. plc
  19. Huawei Technologies Co. Ltd.
  20. Schneider Electric SE
  21. NetApp Inc.

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 Study Assumptions and Market Definition
  • 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET LANDSCAPE

  • 4.1 Market Overview
  • 4.2 Market Drivers
    • 4.2.1 Surge in cloud and hyperscale build-outs
    • 4.2.2 Demand for energy-efficient and sustainable operations
    • 4.2.3 Rising AI/ML workload automation needs
    • 4.2.4 Complexity of hybrid and multi-cloud architectures
    • 4.2.5 Grid-interactive incentive programs for data centers
    • 4.2.6 Edge localization in emerging economies
  • 4.3 Market Restraints
    • 4.3.1 Legacy system interoperability hurdles
    • 4.3.2 Heightened cyber-security and compliance risks
    • 4.3.3 NetOps/automation talent shortage
    • 4.3.4 Power and water scarcity in major hubs
  • 4.4 Supply-Chain Analysis
  • 4.5 Regulatory Landscape
  • 4.6 Technological Outlook
  • 4.7 Porter's Five Forces Analysis
    • 4.7.1 Bargaining Power of Suppliers
    • 4.7.2 Bargaining Power of Buyers
    • 4.7.3 Threat of New Entrants
    • 4.7.4 Threat of Substitutes
    • 4.7.5 Intensity of Competitive Rivalry
  • 4.8 Assessment of Macro-economic Trends on the Market
  • 4.9 Sustainability and Carbon-Neutral Initiatives
  • 4.10 Capacity and Power-Demand Analysis

5 MARKET SIZE AND GROWTH FORECASTS (VALUES)

  • 5.1 By Solution
    • 5.1.1 Server Automation
    • 5.1.2 Network Automation
    • 5.1.3 Storage/Database Automation
    • 5.1.4 Orchestration and Configuration Mgmt.
    • 5.1.5 Performance and Compliance Mgmt.
  • 5.2 By Data Center Tier Type
    • 5.2.1 Tier 1 and 2
    • 5.2.2 Tier 3
    • 5.2.3 Tier 4
  • 5.3 By Deployment Mode
    • 5.3.1 On-premise
    • 5.3.2 Cloud
  • 5.4 By Data Center Type
    • 5.4.1 Hyperscalers/Cloud Server Providers
    • 5.4.2 Colocation Providers
    • 5.4.3 Enterprise and Edge
  • 5.5 By Geography
    • 5.5.1 North America
      • 5.5.1.1 United States
      • 5.5.1.2 Canada
      • 5.5.1.3 Mexico
    • 5.5.2 Europe
      • 5.5.2.1 United Kingdom
      • 5.5.2.2 Germany
      • 5.5.2.3 France
      • 5.5.2.4 Italy
      • 5.5.2.5 Spain
      • 5.5.2.6 Rest of Europe
    • 5.5.3 Asia-Pacific
      • 5.5.3.1 China
      • 5.5.3.2 Japan
      • 5.5.3.3 India
      • 5.5.3.4 Singapore
      • 5.5.3.5 Australia
      • 5.5.3.6 Malaysia
      • 5.5.3.7 Rest of Asia-Pacific
    • 5.5.4 South America
      • 5.5.4.1 Brazil
      • 5.5.4.2 Chile
      • 5.5.4.3 Argentina
      • 5.5.4.4 Rest of South America
    • 5.5.5 Middle East
      • 5.5.5.1 United Arab Emirate
      • 5.5.5.2 Saudi Arabia
      • 5.5.5.3 Turkey
      • 5.5.5.4 Rest of Middle East
    • 5.5.6 Africa
      • 5.5.6.1 South Africa
      • 5.5.6.2 Nigeria
      • 5.5.6.3 Rest of Africa

6 COMPETITIVE LANDSCAPE

  • 6.1 Market Concentration
  • 6.2 Strategic Moves
  • 6.3 Market Share Analysis
  • 6.4 Company Profiles (includes Global level Overview, Market level overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share for key companies, Products and Services, and Recent Developments)
    • 6.4.1 Cisco Systems Inc.
    • 6.4.2 VMware Inc.
    • 6.4.3 Microsoft Corporation
    • 6.4.4 IBM Corporation
    • 6.4.5 Hewlett Packard Enterprise (HPE)
    • 6.4.6 Dell Technologies Inc.
    • 6.4.7 BMC Software Inc.
    • 6.4.8 ServiceNow Inc.
    • 6.4.9 Oracle Corporation
    • 6.4.10 Fujitsu Ltd.
    • 6.4.11 Juniper Networks Inc.
    • 6.4.12 ABB Ltd.
    • 6.4.13 Citrix Systems Inc.
    • 6.4.14 Chef Software Inc. (Progress Software)
    • 6.4.15 Brocade Communications Systems
    • 6.4.16 HashiCorp Inc.
    • 6.4.17 Puppet Labs LLC
    • 6.4.18 Micro Focus Intl. plc
    • 6.4.19 Huawei Technologies Co. Ltd.
    • 6.4.20 Schneider Electric SE
    • 6.4.21 NetApp Inc.

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

  • 7.1 White-space and Unmet-need Assessment