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市场调查报告书
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1857044

全球人工智慧赋能的DevOps自动化市场：预测至2032年－按组件、部署方式、组织规模、应用、最终用户和地区进行分析

AI-Powered DevOps Automation Market Forecasts to 2032 - Global Analysis By Component, Deployment Mode, Organization Size, Application, End User, and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 的数据，全球 AI 驱动的 DevOps 自动化市场预计到 2025 年将达到 105 亿美元，到 2032 年将达到 478 亿美元，预测期内复合年增长率为 24.1%。

AI驱动的DevOps自动化平台整合了AI技术，用于自动化和增强软体开发（Dev）和IT运维（Ops）。 AI演算法能够分析程式码、预测系统故障，并自动化测试、配置和事件回应。这可以加快发布週期、提高程式码品质并最大限度地减少人工操作。随着企业寻求数位转型，以加快产品上市速度，并透过智慧自动化和预测分析实现更稳定、更有效率的软体交付流程，该市场正在蓬勃发展。

据 Linux 基金会称，75% 的大型企业正在采用 AI 驱动的 DevOps 自动化工具，以更频繁地部署软体并将事件解决时间缩短 50%。

对更快软体交付速度和营运效率的需求

缩短产品上市时间的巨大压力是推动市场发展的主要动力。为了保持竞争力，企业不得不缩短开发週期并提高应用程式品质。人工智慧驱动的DevOps工具透过自动化复杂的测试、监控和部署流程，最大限度地减少人为错误并简化工作流程，从而直接解决这个问题。这种自动化不仅加快了交付速度，还优化了资源利用率，显着降低了营运成本，并建立了更稳定的生产环境，从而推动了各行业在追求数​​位敏捷性的过程中广泛采用这些工具。

与旧有系统和工具整合的挑战

阻碍人工智慧工具普及的一大障碍在于，将新型人工智慧主导工具与现有传统基础设施进行复杂的整合。许多组织仍在使用由各种老旧系统拼凑而成的系统，这些系统并非为现代的、API驱动的自动化工作流程而设计。维修这些环境需要大量的客製化和专家资源，这可能会导致营运中断。这种复杂性增加了部署成本和时间，往往会阻碍或延迟人工智慧工具的普及，尤其是在大型传统企业中，系统全面改造并非短期内可行的选择。

拓展至边缘运算与物联网应用领域

边缘运算和物联网 (IoT) 设备的快速普及带来了巨大的成长机会。管理大规模分散式边缘环境本身就十分复杂，需要自动化配置、监控和安全通讯协定。人工智慧驱动的 DevOps 具有独特的优势，能够自动化管理这些分散式系统的生命週期，并确保边缘的可靠性和效能。除了传统的资料中心之外，製造业、汽车业和智慧城市等新兴垂直领域也正在被探索，为 DevOps 解决方案提供者创造了新的收入来源。

工具氾滥与供应商锁定风险

市场面临新的威胁：工具氾滥，各种分散的、小众的AI工具导致工作流程分散且效率低。此外，依赖单一供应商的专有生态系统可能导致锁定，降低灵活性并增加长期成本。这种情况使得企业难以更换供应商或整合最佳解决方案，从而削弱了AI驱动的DevOps所承诺的敏捷性和效率优势。

新冠疫情的影响：

疫情大大推动了人工智慧驱动的DevOps市场的发展。封锁措施和远距办公的兴起迫使企业迅速实现营运数位化，并高度依赖云端基础服务。这种对强大、扩充性且可远端管理的软体交付管道的突如其来的需求，凸显了自动化的紧迫性。因此，企业优先投资于人工智慧主导的DevOps工具，以确保业务永续营运、加速数位转型，并在分散式工作环境中维护软体可靠性，从而在疫情期间及之后推动了市场成长。

预计在预测期内，解决方案板块将成为最大的板块。

预计在预测期内，解决方案领域将占据最大的市场份额，因为它涵盖了为人工智慧提供关键功能的核心创收软体平台。这些整合平台透过自动化持续整合、配置和监控 (CI/CD) 等关键 DevOps 阶段，提供即时的实际价值。企业正在优先考虑这些综合解决方案，以建立基础自动化层。对统一且强大的自动化套件的需求正在巩固其在该领域的领先地位。

预计在预测期内，云端基础的细分市场将以最高的复合年增长率成长。

预计在预测期内，云端基础方案将实现最高成长率。这一快速成长得益于其固有的扩充性、较低的前期成本和易于部署等优势，这些优势对于采用 DevOps 实践的企业至关重要。云端基础AI-DevOps 工具能够实现无缝更新，并可轻鬆与其他云端原生服务集成，使其成为现代敏捷开发环境的理想选择。此外，随着企业寻求灵活且便利的自动化解决方案，全球范围内向云端优先策略和混合办公模式的转变也持续推动着这一领域的扩张。

比最大的地区

预计北美将在预测期内占据最大的市场份额。这一领先地位可归功于主要技术供应商的强大实力、对新兴技术的早期采用以及在银行、金融服务和保险（BFSI）和通讯等关键行业的大规模IT投资。此外，成熟的云端基础设施和众多具有复杂软体交付需求的企业聚集，为人工智慧驱动的DevOps解决方案创造了肥沃的土壤。该地区对提升营运效率和安全性的高度重视，进一步巩固了其在全球市场的主导地位。

复合年增长率最高的地区：

预计亚太地区在预测期内将呈现最高的复合年增长率。这项加速成长主要得益于快速的数位转型、IT和BPO产业的扩张，以及中国、印度和东南亚等新兴经济体云端运算应用的日益普及。该地区各国政府也积极支持技术现代化，而本地企业则大力投资DevOps以提升其全球竞争力。经济活力与技术投资的结合，为自动化解决方案创造了高成长环境。

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  • 公司简介
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    • 基于产品系列、地域覆盖和策略联盟对主要企业基准化分析

目录

第一章执行摘要

第二章 引言

  • 概述
  • 相关利益者
  • 分析范围
  • 分析方法
    • 资料探勘
    • 数据分析
    • 数据检验
    • 分析方法
  • 分析材料
    • 原始研究资料
    • 二手研究资讯来源
    • 先决条件

第三章 市场趋势分析

  • 司机
  • 抑制因素
  • 市场机会
  • 威胁
  • 应用分析
  • 终端用户分析
  • 新兴市场
  • 新冠疫情的感染疾病

第四章 波特五力分析

  • 供应商的议价能力
  • 买方议价能力
  • 替代产品的威胁
  • 新参与企业的威胁
  • 公司间的竞争

第五章 全球人工智慧赋能的DevOps自动化市场（按组件划分）

  • 解决方案
    • 平台
    • 工具/软体
  • 服务
    • 专业服务
    • 託管服务

第六章 全球人工智慧赋能的DevOps自动化市场（以部署方式划分）

  • 云端基础的
  • 本地部署

第七章 全球人工智慧驱动的DevOps自动化市场：依组织规模划分

  • 大公司
  • 小型企业

第八章 由全球人工智慧驱动的DevOps自动化市场：按应用划分

  • 预测分析、主动主动监测
  • 异常检测、根本原因分析 (RCA)
  • 自动化测试、品质保证 (QA)
  • 智慧警报管理和事件回应
  • 自动程式码产生和优化
  • 基础设施最佳化、成本管理（财务营运）
  • 安全自动化（DevSecOps）
  • 发布管理、配置自动化
  • 流程挖掘与优化

第九章：全球人工智慧赋能的DevOps自动化市场（按最终用户划分）

  • 资讯科技/通讯
  • 银行、金融服务和保险业 (BFSI)
  • 医学与生命科​​学
  • 零售与电子商务
  • 製造业
  • 媒体与娱乐
  • 政府/公共部门
  • 其他最终用户

第十章：全球人工智慧赋能的DevOps自动化市场（按地区划分）

  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 亚太其他地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美洲
  • 中东和非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲地区

第十一章：主要趋势

  • 合约、商业伙伴关係和合资企业
  • 企业合併（M&A）
  • 新产品发布
  • 业务拓展
  • 其他关键策略

第十二章：公司简介

  • Microsoft Corporation
  • International Business Machines Corporation
  • Amazon Web Services, Inc.
  • Google LLC
  • ServiceNow, Inc.
  • Dynatrace, Inc.
  • Datadog, Inc.
  • CloudBees, Inc.
  • GitLab Inc.
  • Atlassian Corporation Plc
  • HashiCorp, Inc.
  • Puppet, Inc.
  • Progress Software Corporation
  • Broadcom Inc.
  • Splunk Inc.
  • New Relic, Inc.
  • PagerDuty, Inc.
  • Elastic NV
Product Code: SMRC31909

According to Stratistics MRC, the Global AI-Powered DevOps Automation Market is accounted for $10.5 billion in 2025 and is expected to reach $47.8 billion by 2032 growing at a CAGR of 24.1% during the forecast period. AI-Powered DevOps Automation involves platforms integrating AI to automate and enhance software development (Dev) and IT operations (Ops). AI algorithms analyze code, predict system failures, and automate testing, deployment, and incident response. This accelerates release cycles, improves code quality, and minimizes manual toil. The market is expanding as organizations pursue digital transformation, seeking to achieve faster time-to-market and more stable, efficient software delivery pipelines through intelligent automation and predictive analytics.

According to The Linux Foundation, 75% of large enterprises have adopted AI-powered DevOps automation tools, increasing software deployment frequency and reducing incident resolution time by 50%.

Market Dynamics:

Driver:

Need for faster software delivery and operational efficiency

The relentless pressure to accelerate time-to-market is a primary market catalyst. Businesses are compelled to shorten development cycles and enhance application quality to maintain a competitive edge. AI-powered DevOps tools directly address this by automating complex testing, monitoring, and deployment processes, which minimizes manual errors and streamlines workflows. This automation not only speeds up delivery but also optimizes resource utilization, leading to significant operational cost savings and more stable production environments, thereby fueling widespread adoption across industries seeking digital agility.

Restraint:

Integration challenges with legacy systems and tools

A significant barrier to adoption is the complex integration of new AI-driven tools with established legacy infrastructure. Many organizations operate on a patchwork of older systems that are not designed for modern, API-driven, automated workflows. Retrofitting these environments requires substantial customization, expert resources, and can lead to operational downtime. This complexity increases implementation costs and timelines, often discouraging or delaying adoption, particularly in large, traditional enterprises where a complete system overhaul is not a feasible short-term option.

Opportunity:

Expansion into edge computing and IoT deployments

The rapid proliferation of edge computing and Internet of Things (IoT) devices presents a substantial growth avenue. Managing distributed, large-scale edge environments is inherently complex, requiring automated deployment, monitoring, and security protocols. AI-powered DevOps is uniquely positioned to automate lifecycle management for these decentralized systems, ensuring reliability and performance at the edge. This expansion beyond traditional data centers opens up new verticals like manufacturing, automotive, and smart cities, creating a fresh revenue stream for DevOps solution providers.

Threat:

Tool sprawl and vendor lock-in risks

The market faces the emerging threat of tool sprawl, where an overabundance of disparate, niche AI tools creates fragmented and inefficient workflows. Moreover, reliance on a single vendor's proprietary ecosystem can lead to lock-in, reducing flexibility and increasing long-term costs. This situation makes it difficult for organizations to switch providers or integrate best-of-breed solutions, potentially eroding the very agility and efficiency benefits that AI-powered DevOps promises to deliver, thus posing a strategic risk to market growth and customer satisfaction.

Covid-19 Impact:

The pandemic acted as a significant accelerant for the AI-Powered DevOps market. Lockdowns and the shift to remote work forced enterprises to rapidly digitize operations and rely heavily on cloud-based services. This sudden demand for robust, scalable, and remotely manageable software delivery pipelines highlighted the critical need for automation. Consequently, organizations prioritized investments in AI-driven DevOps tools to ensure business continuity, accelerate digital transformation initiatives, and maintain software reliability in a distributed work environment, boosting market growth during and beyond the crisis.

The solutions segment is expected to be the largest during the forecast period

The solutions segment is expected to account for the largest market share during the forecast period, as it encompasses the core, revenue-generating software platforms that deliver essential AI functionalities. These integrated platforms offer immediate, tangible value by automating key DevOps phases like continuous integration, deployment, and monitoring (CI/CD). Enterprises are prioritizing these comprehensive solutions to build a foundational automation layer, as they provide a more cohesive and manageable environment compared to assembling disparate point tools. This demand for unified, powerful automation suites solidifies the segment's dominant position.

The cloud-based segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the cloud-based segment is predicted to witness the highest growth rate. This surge is driven by its inherent scalability, lower upfront costs, and ease of implementation, which are critical for businesses adopting DevOps practices. Cloud-based AI-DevOps tools facilitate seamless updates and integrate effortlessly with other cloud-native services, making them ideal for modern, agile development environments. Furthermore, the global shift toward cloud-first strategies and hybrid work models continues to propel this segment's expansion as organizations seek flexible and accessible automation solutions.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share. This leadership is attributed to the strong presence of major technology vendors, early adoption of advanced technologies, and significant IT investments across key sectors like BFSI and telecom. Moreover, a mature cloud infrastructure and a high concentration of enterprises with complex software delivery needs create a fertile ground for AI-powered DevOps solutions. The region's stringent focus on achieving superior operational efficiency and security further consolidates its dominant position in the global market.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR. This accelerated growth is fueled by rapid digital transformation, expanding IT and BPO industries, and increasing cloud adoption in emerging economies such as China, India, and Southeast Asia. Governments in the region are also actively supporting technological modernization, while local businesses are investing heavily in DevOps to improve their global competitiveness. This combination of economic dynamism and technological investment creates a high-growth environment for automation solutions.

Key players in the market

Some of the key players in AI-Powered DevOps Automation Market include Microsoft Corporation, International Business Machines Corporation, Amazon Web Services, Inc., Google LLC, ServiceNow, Inc., Dynatrace, Inc., Datadog, Inc., CloudBees, Inc., GitLab Inc., Atlassian Corporation Plc, HashiCorp, Inc., Puppet, Inc., Progress Software Corporation, Broadcom Inc., Splunk Inc., New Relic, Inc., PagerDuty, Inc., and Elastic N.V.

Key Developments:

In June 2025, Datadog, Inc. the monitoring and security platform for cloud applications, today introduced three new AI agents that perform interactive investigations and asynchronous code fixes for development, security and operations teams. Today's launch of the Bits AI SRE, Bits AI Dev Agent and Bits AI Security Analyst agents, alongside the new Proactive App Recommendations and APM Investigator capabilities, marks the continued evolution of Bits AI, Datadog's generative AI assistant that helps engineers resolve application issues in real time.

Components Covered:

  • Solutions
  • Services

Deployment Modes Covered:

  • Cloud-Based
  • On-Premises

Organization Sizes Covered:

  • Large Enterprises
  • Small and Medium-sized Enterprises (SMEs)

Applications Covered:

  • Predictive Analytics & Proactive Monitoring
  • Anomaly Detection & Root Cause Analysis (RCA)
  • Automated Testing & Quality Assurance (QA)
  • Intelligent Alert Management & Incident Response
  • Automated Code Generation & Optimization
  • Infrastructure Optimization & Cost Management (FinOps)
  • Security Automation (DevSecOps)
  • Release Management & Deployment Automation
  • Process Mining & Optimization

End Users Covered:

  • IT & Telecommunications
  • BFSI (Banking, Financial Services, and Insurance)
  • Healthcare & Life Sciences
  • Retail & E-commerce
  • Manufacturing
  • Media & Entertainment
  • Government & Public Sector
  • Other End Users

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Application Analysis
  • 3.7 End User Analysis
  • 3.8 Emerging Markets
  • 3.9 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global AI-Powered DevOps Automation Market, By Component

  • 5.1 Introduction
  • 5.2 Solutions
    • 5.2.1 Platforms
    • 5.2.2 Tools/Software
  • 5.3 Services
    • 5.3.1 Professional Services
    • 5.3.2 Managed Services

6 Global AI-Powered DevOps Automation Market, By Deployment Mode

  • 6.1 Introduction
  • 6.2 Cloud-Based
  • 6.3 On-Premises

7 Global AI-Powered DevOps Automation Market, By Organization Size

  • 7.1 Introduction
  • 7.2 Large Enterprises
  • 7.3 Small and Medium-sized Enterprises (SMEs)

8 Global AI-Powered DevOps Automation Market, By Application

  • 8.1 Introduction
  • 8.2 Predictive Analytics & Proactive Monitoring
  • 8.3 Anomaly Detection & Root Cause Analysis (RCA)
  • 8.4 Automated Testing & Quality Assurance (QA)
  • 8.5 Intelligent Alert Management & Incident Response
  • 8.6 Automated Code Generation & Optimization
  • 8.7 Infrastructure Optimization & Cost Management (FinOps)
  • 8.8 Security Automation (DevSecOps)
  • 8.9 Release Management & Deployment Automation
  • 8.10 Process Mining & Optimization

9 Global AI-Powered DevOps Automation Market, By End User

  • 9.1 Introduction
  • 9.2 IT & Telecommunications
  • 9.3 BFSI (Banking, Financial Services, and Insurance)
  • 9.4 Healthcare & Life Sciences
  • 9.5 Retail & E-commerce
  • 9.6 Manufacturing
  • 9.7 Media & Entertainment
  • 9.8 Government & Public Sector
  • 9.9 Other End Users

10 Global AI-Powered DevOps Automation Market, By Geography

  • 10.1 Introduction
  • 10.2 North America
    • 10.2.1 US
    • 10.2.2 Canada
    • 10.2.3 Mexico
  • 10.3 Europe
    • 10.3.1 Germany
    • 10.3.2 UK
    • 10.3.3 Italy
    • 10.3.4 France
    • 10.3.5 Spain
    • 10.3.6 Rest of Europe
  • 10.4 Asia Pacific
    • 10.4.1 Japan
    • 10.4.2 China
    • 10.4.3 India
    • 10.4.4 Australia
    • 10.4.5 New Zealand
    • 10.4.6 South Korea
    • 10.4.7 Rest of Asia Pacific
  • 10.5 South America
    • 10.5.1 Argentina
    • 10.5.2 Brazil
    • 10.5.3 Chile
    • 10.5.4 Rest of South America
  • 10.6 Middle East & Africa
    • 10.6.1 Saudi Arabia
    • 10.6.2 UAE
    • 10.6.3 Qatar
    • 10.6.4 South Africa
    • 10.6.5 Rest of Middle East & Africa

11 Key Developments

  • 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 11.2 Acquisitions & Mergers
  • 11.3 New Product Launch
  • 11.4 Expansions
  • 11.5 Other Key Strategies

12 Company Profiling

  • 12.1 Microsoft Corporation
  • 12.2 International Business Machines Corporation
  • 12.3 Amazon Web Services, Inc.
  • 12.4 Google LLC
  • 12.5 ServiceNow, Inc.
  • 12.6 Dynatrace, Inc.
  • 12.7 Datadog, Inc.
  • 12.8 CloudBees, Inc.
  • 12.9 GitLab Inc.
  • 12.10 Atlassian Corporation Plc
  • 12.11 HashiCorp, Inc.
  • 12.12 Puppet, Inc.
  • 12.13 Progress Software Corporation
  • 12.14 Broadcom Inc.
  • 12.15 Splunk Inc.
  • 12.16 New Relic, Inc.
  • 12.17 PagerDuty, Inc.
  • 12.18 Elastic N.V.

List of Tables

  • Table 1 Global AI-Powered DevOps Automation Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global AI-Powered DevOps Automation Market Outlook, By Component (2024-2032) ($MN)
  • Table 3 Global AI-Powered DevOps Automation Market Outlook, By Solutions (2024-2032) ($MN)
  • Table 4 Global AI-Powered DevOps Automation Market Outlook, By Platforms (2024-2032) ($MN)
  • Table 5 Global AI-Powered DevOps Automation Market Outlook, By Tools/Software (2024-2032) ($MN)
  • Table 6 Global AI-Powered DevOps Automation Market Outlook, By Services (2024-2032) ($MN)
  • Table 7 Global AI-Powered DevOps Automation Market Outlook, By Professional Services (2024-2032) ($MN)
  • Table 8 Global AI-Powered DevOps Automation Market Outlook, By Managed Services (2024-2032) ($MN)
  • Table 9 Global AI-Powered DevOps Automation Market Outlook, By Deployment Mode (2024-2032) ($MN)
  • Table 10 Global AI-Powered DevOps Automation Market Outlook, By Cloud-Based (2024-2032) ($MN)
  • Table 11 Global AI-Powered DevOps Automation Market Outlook, By On-Premises (2024-2032) ($MN)
  • Table 12 Global AI-Powered DevOps Automation Market Outlook, By Organization Size (2024-2032) ($MN)
  • Table 13 Global AI-Powered DevOps Automation Market Outlook, By Large Enterprises (2024-2032) ($MN)
  • Table 14 Global AI-Powered DevOps Automation Market Outlook, By Small and Medium-sized Enterprises (SMEs) (2024-2032) ($MN)
  • Table 15 Global AI-Powered DevOps Automation Market Outlook, By Application (2024-2032) ($MN)
  • Table 16 Global AI-Powered DevOps Automation Market Outlook, By Predictive Analytics & Proactive Monitoring (2024-2032) ($MN)
  • Table 17 Global AI-Powered DevOps Automation Market Outlook, By Anomaly Detection & Root Cause Analysis (RCA) (2024-2032) ($MN)
  • Table 18 Global AI-Powered DevOps Automation Market Outlook, By Automated Testing & Quality Assurance (QA) (2024-2032) ($MN)
  • Table 19 Global AI-Powered DevOps Automation Market Outlook, By Intelligent Alert Management & Incident Response (2024-2032) ($MN)
  • Table 20 Global AI-Powered DevOps Automation Market Outlook, By Automated Code Generation & Optimization (2024-2032) ($MN)
  • Table 21 Global AI-Powered DevOps Automation Market Outlook, By Infrastructure Optimization & Cost Management (FinOps) (2024-2032) ($MN)
  • Table 22 Global AI-Powered DevOps Automation Market Outlook, By Security Automation (DevSecOps) (2024-2032) ($MN)
  • Table 23 Global AI-Powered DevOps Automation Market Outlook, By Release Management & Deployment Automation (2024-2032) ($MN)
  • Table 24 Global AI-Powered DevOps Automation Market Outlook, By Process Mining & Optimization (2024-2032) ($MN)
  • Table 25 Global AI-Powered DevOps Automation Market Outlook, By End User (2024-2032) ($MN)
  • Table 26 Global AI-Powered DevOps Automation Market Outlook, By IT & Telecommunications (2024-2032) ($MN)
  • Table 27 Global AI-Powered DevOps Automation Market Outlook, By BFSI (Banking, Financial Services, and Insurance) (2024-2032) ($MN)
  • Table 28 Global AI-Powered DevOps Automation Market Outlook, By Healthcare & Life Sciences (2024-2032) ($MN)
  • Table 29 Global AI-Powered DevOps Automation Market Outlook, By Retail & E-commerce (2024-2032) ($MN)
  • Table 30 Global AI-Powered DevOps Automation Market Outlook, By Manufacturing (2024-2032) ($MN)
  • Table 31 Global AI-Powered DevOps Automation Market Outlook, By Media & Entertainment (2024-2032) ($MN)
  • Table 32 Global AI-Powered DevOps Automation Market Outlook, By Government & Public Sector (2024-2032) ($MN)
  • Table 33 Global AI-Powered DevOps Automation Market Outlook, By Other End Users (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.