Global Deployment Automation Market

Deployment Automation Comprehensive Study by Type (Cloud Based, On-Premise), Application (SMEs, Large Enterprises), End-User (Software developers, Software engineers), Approaches (Scripting, Development with CI system, Basic deployment tools, Model-driven deployment, Continuous deployment) Players and Region - Global Market Outlook to 2028

Deployment Automation Market by XX Submarkets | Forecast Years 2023-2028  

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  • Summary
  • Market Segments
  • Table of Content
  • List of Table & Figures
  • Players Profiled
About Deployment Automation
Deployment automation allows the application to be deployed across the across various environments used in the development process, as well as the final production environments. Deployment Automation is the procedure of provisioning or placing the application positioning and configurations to the operating environments across the system development life cycle.

AttributesDetails
Study Period2018-2028
Base Year2022
UnitValue (USD Million)


The software tools are blooming in a market the competition between leading firm is high as the new launches as well as innovation in the product are going on for consumer-friendly. The companies also merging and acquiring firms to earn more profit and rule the market. The top firms acquiring local firms to penetrate the local market. Analyst at AMA Research estimates that United States Players will contribute the maximum growth to Global Deployment Automation market throughout the forecasted period. Established and emerging Players should take a closer view at their existing organizations and reinvent traditional business and operating models to adapt to the future.

Microsoft (United States), JetBrains (Czechia), Octopus deploy (Australia), GitLab Inc (United States), Appveyor (Canada), Atlassian (Australia), Stackify (United States), XebiaLabs develops (United States), PDQ (United States) and Chef (United States) are some of the key players that are part of study coverage. Additionally, the Players which are also part of the research coverage are DeployBot (United States), CircleCI (United States), Amazon (United States) and Codeship (United States).

Segmentation Overview
AMA Research has segmented the market of Global Deployment Automation market by Type (Cloud Based and On-Premise), Application (SMEs and Large Enterprises) and Region.



On the basis of geography, the market of Deployment Automation has been segmented into South America (Brazil, Argentina, Rest of South America), Asia Pacific (China, Japan, India, South Korea, Taiwan, Australia, Rest of Asia-Pacific), Europe (Germany, France, Italy, United Kingdom, Netherlands, Rest of Europe), MEA (Middle East, Africa), North America (United States, Canada, Mexico). If we see Market by End-User, the sub-segment i.e. Software developers will boost the Deployment Automation market. Additionally, the rising demand from SMEs and various industry verticals gives enough cushion to market growth. If we see Market by Approaches, the sub-segment i.e. Scripting will boost the Deployment Automation market. Additionally, the rising demand from SMEs and various industry verticals gives enough cushion to market growth.

Influencing Trend:
Highly Recommended As Developers Can Spend Time Working On New Features, Not On Fixes For Manual Deployments

Market Growth Drivers:
Growing Use As It Removes Manual Steps Reduces Human Error and Highly Installed As There Is No Need Expert To Work

Challenges:
Job Cuttings Unemployment

Restraints:
Initially High Costs For Investment and Loss Of Flexibility

Opportunities:
Highly Demanded As It Fulfills Customer Satisfaction Frequent Updates With New Features and Requires Lower Costs Fewer Errors, Fewer Human Hours Needed For Deployments Means Lower Cost

Market Leaders and their expansionary development strategies
On 23rd January, Microsoft and Genesys expand partnership to help enterprises seize the power of the cloud for better customer experiences. Microsoft and Genesys have expanded their partnership to provide enterprises with a new cloud service for contact centers that enables them to deliver superior interactions for customers. With the omnichannel customer experience solution, Genesys Engage running on Microsoft Azure, enterprises have the security and scalability they need to manage the complexities involved with connecting every touchpoint throughout the customer journey.
In November 2023, The Devops approach to software development helps SMBs accelerate the delivery of high-quality software by making it easier to write, test, secure, and deploy code. Through DevOps automation, repetitive and manual tasks are performed with little or no human interaction—to streamline the entire software development lifecycle (SDLC).


Key Target Audience
Software Firms, Information Technology firms, IT directors/consultants, Government organizations and Consultants/advisory firms

About Approach
To evaluate and validate the market size various sources including primary and secondary analysis is utilized. AMA Research follows regulatory standards such as NAICS/SIC/ICB/TRCB, to have a better understanding of the market. The market study is conducted on basis of more than 200 companies dealing in the market regional as well as global areas with the purpose to understand the companies positioning regarding the market value, volume, and their market share for regional as well as global.

Further to bring relevance specific to any niche market we set and apply a number of criteria like Geographic Footprints, Regional Segments of Revenue, Operational Centres, etc. The next step is to finalize a team (In-House + Data Agencies) who then starts collecting C & D level executives and profiles, Industry experts, Opinion leaders, etc., and work towards appointment generation.

The primary research is performed by taking the interviews of executives of various companies dealing in the market as well as using the survey reports, research institute, and latest research reports. Meanwhile, the analyst team keeps preparing a set of questionnaires, and after getting the appointee list; the target audience is then tapped and segregated with various mediums and channels that are feasible for making connections that including email communication, telephonic, skype, LinkedIn Group & InMail, Community Forums, Community Forums, open Survey, SurveyMonkey, etc.

Report Objectives / Segmentation Covered

By Type
  • Cloud Based
  • On-Premise
By Application
  • SMEs
  • Large Enterprises
By End-User
  • Software developers
  • Software engineers

By Approaches
  • Scripting
  • Development with CI system
  • Basic deployment tools
  • Model-driven deployment
  • Continuous deployment

By Regions
  • South America
    • Brazil
    • Argentina
    • Rest of South America
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Taiwan
    • Australia
    • Rest of Asia-Pacific
  • Europe
    • Germany
    • France
    • Italy
    • United Kingdom
    • Netherlands
    • Rest of Europe
  • MEA
    • Middle East
    • Africa
  • North America
    • United States
    • Canada
    • Mexico
  • 1. Market Overview
    • 1.1. Introduction
    • 1.2. Scope/Objective of the Study
      • 1.2.1. Research Objective
  • 2. Executive Summary
    • 2.1. Introduction
  • 3. Market Dynamics
    • 3.1. Introduction
    • 3.2. Market Drivers
      • 3.2.1. Growing Use As It Removes Manual Steps Reduces Human Error
      • 3.2.2. Highly Installed As There Is No Need Expert To Work
    • 3.3. Market Challenges
      • 3.3.1. Job Cuttings Unemployment
    • 3.4. Market Trends
      • 3.4.1. Highly Recommended As Developers Can Spend Time Working On New Features, Not On Fixes For Manual Deployments
  • 4. Market Factor Analysis
    • 4.1. Porters Five Forces
    • 4.2. Supply/Value Chain
    • 4.3. PESTEL analysis
    • 4.4. Market Entropy
    • 4.5. Patent/Trademark Analysis
  • 5. Global Deployment Automation, by Type, Application, End-User, Approaches and Region (value) (2017-2022)
    • 5.1. Introduction
    • 5.2. Global Deployment Automation (Value)
      • 5.2.1. Global Deployment Automation by: Type (Value)
        • 5.2.1.1. Cloud Based
        • 5.2.1.2. On-Premise
      • 5.2.2. Global Deployment Automation by: Application (Value)
        • 5.2.2.1. SMEs
        • 5.2.2.2. Large Enterprises
      • 5.2.3. Global Deployment Automation by: End-User (Value)
        • 5.2.3.1. Software developers
        • 5.2.3.2. Software engineers
      • 5.2.4. Global Deployment Automation by: Approaches (Value)
        • 5.2.4.1. Scripting
        • 5.2.4.2. Development with CI system
        • 5.2.4.3. Basic deployment tools
        • 5.2.4.4. Model-driven deployment
        • 5.2.4.5. Continuous deployment
      • 5.2.5. Global Deployment Automation Region
        • 5.2.5.1. South America
          • 5.2.5.1.1. Brazil
          • 5.2.5.1.2. Argentina
          • 5.2.5.1.3. Rest of South America
        • 5.2.5.2. Asia Pacific
          • 5.2.5.2.1. China
          • 5.2.5.2.2. Japan
          • 5.2.5.2.3. India
          • 5.2.5.2.4. South Korea
          • 5.2.5.2.5. Taiwan
          • 5.2.5.2.6. Australia
          • 5.2.5.2.7. Rest of Asia-Pacific
        • 5.2.5.3. Europe
          • 5.2.5.3.1. Germany
          • 5.2.5.3.2. France
          • 5.2.5.3.3. Italy
          • 5.2.5.3.4. United Kingdom
          • 5.2.5.3.5. Netherlands
          • 5.2.5.3.6. Rest of Europe
        • 5.2.5.4. MEA
          • 5.2.5.4.1. Middle East
          • 5.2.5.4.2. Africa
        • 5.2.5.5. North America
          • 5.2.5.5.1. United States
          • 5.2.5.5.2. Canada
          • 5.2.5.5.3. Mexico
  • 6. Deployment Automation: Manufacturers/Players Analysis
    • 6.1. Competitive Landscape
      • 6.1.1. Market Share Analysis
        • 6.1.1.1. Top 3
        • 6.1.1.2. Top 5
    • 6.2. Peer Group Analysis (2022)
    • 6.3. BCG Matrix
    • 6.4. Company Profile
      • 6.4.1. Microsoft (United States)
        • 6.4.1.1. Business Overview
        • 6.4.1.2. Products/Services Offerings
        • 6.4.1.3. Financial Analysis
        • 6.4.1.4. SWOT Analysis
      • 6.4.2. JetBrains (Czechia)
        • 6.4.2.1. Business Overview
        • 6.4.2.2. Products/Services Offerings
        • 6.4.2.3. Financial Analysis
        • 6.4.2.4. SWOT Analysis
      • 6.4.3. Octopus deploy (Australia)
        • 6.4.3.1. Business Overview
        • 6.4.3.2. Products/Services Offerings
        • 6.4.3.3. Financial Analysis
        • 6.4.3.4. SWOT Analysis
      • 6.4.4. GitLab Inc (United States)
        • 6.4.4.1. Business Overview
        • 6.4.4.2. Products/Services Offerings
        • 6.4.4.3. Financial Analysis
        • 6.4.4.4. SWOT Analysis
      • 6.4.5. Appveyor (Canada)
        • 6.4.5.1. Business Overview
        • 6.4.5.2. Products/Services Offerings
        • 6.4.5.3. Financial Analysis
        • 6.4.5.4. SWOT Analysis
      • 6.4.6. Atlassian (Australia)
        • 6.4.6.1. Business Overview
        • 6.4.6.2. Products/Services Offerings
        • 6.4.6.3. Financial Analysis
        • 6.4.6.4. SWOT Analysis
      • 6.4.7. Stackify (United States)
        • 6.4.7.1. Business Overview
        • 6.4.7.2. Products/Services Offerings
        • 6.4.7.3. Financial Analysis
        • 6.4.7.4. SWOT Analysis
      • 6.4.8. XebiaLabs develops (United States)
        • 6.4.8.1. Business Overview
        • 6.4.8.2. Products/Services Offerings
        • 6.4.8.3. Financial Analysis
        • 6.4.8.4. SWOT Analysis
      • 6.4.9. PDQ (United States)
        • 6.4.9.1. Business Overview
        • 6.4.9.2. Products/Services Offerings
        • 6.4.9.3. Financial Analysis
        • 6.4.9.4. SWOT Analysis
      • 6.4.10. Chef (United States)
        • 6.4.10.1. Business Overview
        • 6.4.10.2. Products/Services Offerings
        • 6.4.10.3. Financial Analysis
        • 6.4.10.4. SWOT Analysis
  • 7. Global Deployment Automation Sale, by Type, Application, End-User, Approaches and Region (value) (2023-2028)
    • 7.1. Introduction
    • 7.2. Global Deployment Automation (Value)
      • 7.2.1. Global Deployment Automation by: Type (Value)
        • 7.2.1.1. Cloud Based
        • 7.2.1.2. On-Premise
      • 7.2.2. Global Deployment Automation by: Application (Value)
        • 7.2.2.1. SMEs
        • 7.2.2.2. Large Enterprises
      • 7.2.3. Global Deployment Automation by: End-User (Value)
        • 7.2.3.1. Software developers
        • 7.2.3.2. Software engineers
      • 7.2.4. Global Deployment Automation by: Approaches (Value)
        • 7.2.4.1. Scripting
        • 7.2.4.2. Development with CI system
        • 7.2.4.3. Basic deployment tools
        • 7.2.4.4. Model-driven deployment
        • 7.2.4.5. Continuous deployment
      • 7.2.5. Global Deployment Automation Region
        • 7.2.5.1. South America
          • 7.2.5.1.1. Brazil
          • 7.2.5.1.2. Argentina
          • 7.2.5.1.3. Rest of South America
        • 7.2.5.2. Asia Pacific
          • 7.2.5.2.1. China
          • 7.2.5.2.2. Japan
          • 7.2.5.2.3. India
          • 7.2.5.2.4. South Korea
          • 7.2.5.2.5. Taiwan
          • 7.2.5.2.6. Australia
          • 7.2.5.2.7. Rest of Asia-Pacific
        • 7.2.5.3. Europe
          • 7.2.5.3.1. Germany
          • 7.2.5.3.2. France
          • 7.2.5.3.3. Italy
          • 7.2.5.3.4. United Kingdom
          • 7.2.5.3.5. Netherlands
          • 7.2.5.3.6. Rest of Europe
        • 7.2.5.4. MEA
          • 7.2.5.4.1. Middle East
          • 7.2.5.4.2. Africa
        • 7.2.5.5. North America
          • 7.2.5.5.1. United States
          • 7.2.5.5.2. Canada
          • 7.2.5.5.3. Mexico
  • 8. Appendix
    • 8.1. Acronyms
  • 9. Methodology and Data Source
    • 9.1. Methodology/Research Approach
      • 9.1.1. Research Programs/Design
      • 9.1.2. Market Size Estimation
      • 9.1.3. Market Breakdown and Data Triangulation
    • 9.2. Data Source
      • 9.2.1. Secondary Sources
      • 9.2.2. Primary Sources
    • 9.3. Disclaimer
List of Tables
  • Table 1. Deployment Automation: by Type(USD Million)
  • Table 2. Deployment Automation Cloud Based , by Region USD Million (2017-2022)
  • Table 3. Deployment Automation On-Premise , by Region USD Million (2017-2022)
  • Table 4. Deployment Automation: by Application(USD Million)
  • Table 5. Deployment Automation SMEs , by Region USD Million (2017-2022)
  • Table 6. Deployment Automation Large Enterprises , by Region USD Million (2017-2022)
  • Table 7. Deployment Automation: by End-User(USD Million)
  • Table 8. Deployment Automation Software developers , by Region USD Million (2017-2022)
  • Table 9. Deployment Automation Software engineers , by Region USD Million (2017-2022)
  • Table 10. Deployment Automation: by Approaches(USD Million)
  • Table 11. Deployment Automation Scripting , by Region USD Million (2017-2022)
  • Table 12. Deployment Automation Development with CI system , by Region USD Million (2017-2022)
  • Table 13. Deployment Automation Basic deployment tools , by Region USD Million (2017-2022)
  • Table 14. Deployment Automation Model-driven deployment , by Region USD Million (2017-2022)
  • Table 15. Deployment Automation Continuous deployment , by Region USD Million (2017-2022)
  • Table 16. South America Deployment Automation, by Country USD Million (2017-2022)
  • Table 17. South America Deployment Automation, by Type USD Million (2017-2022)
  • Table 18. South America Deployment Automation, by Application USD Million (2017-2022)
  • Table 19. South America Deployment Automation, by End-User USD Million (2017-2022)
  • Table 20. South America Deployment Automation, by Approaches USD Million (2017-2022)
  • Table 21. Brazil Deployment Automation, by Type USD Million (2017-2022)
  • Table 22. Brazil Deployment Automation, by Application USD Million (2017-2022)
  • Table 23. Brazil Deployment Automation, by End-User USD Million (2017-2022)
  • Table 24. Brazil Deployment Automation, by Approaches USD Million (2017-2022)
  • Table 25. Argentina Deployment Automation, by Type USD Million (2017-2022)
  • Table 26. Argentina Deployment Automation, by Application USD Million (2017-2022)
  • Table 27. Argentina Deployment Automation, by End-User USD Million (2017-2022)
  • Table 28. Argentina Deployment Automation, by Approaches USD Million (2017-2022)
  • Table 29. Rest of South America Deployment Automation, by Type USD Million (2017-2022)
  • Table 30. Rest of South America Deployment Automation, by Application USD Million (2017-2022)
  • Table 31. Rest of South America Deployment Automation, by End-User USD Million (2017-2022)
  • Table 32. Rest of South America Deployment Automation, by Approaches USD Million (2017-2022)
  • Table 33. Asia Pacific Deployment Automation, by Country USD Million (2017-2022)
  • Table 34. Asia Pacific Deployment Automation, by Type USD Million (2017-2022)
  • Table 35. Asia Pacific Deployment Automation, by Application USD Million (2017-2022)
  • Table 36. Asia Pacific Deployment Automation, by End-User USD Million (2017-2022)
  • Table 37. Asia Pacific Deployment Automation, by Approaches USD Million (2017-2022)
  • Table 38. China Deployment Automation, by Type USD Million (2017-2022)
  • Table 39. China Deployment Automation, by Application USD Million (2017-2022)
  • Table 40. China Deployment Automation, by End-User USD Million (2017-2022)
  • Table 41. China Deployment Automation, by Approaches USD Million (2017-2022)
  • Table 42. Japan Deployment Automation, by Type USD Million (2017-2022)
  • Table 43. Japan Deployment Automation, by Application USD Million (2017-2022)
  • Table 44. Japan Deployment Automation, by End-User USD Million (2017-2022)
  • Table 45. Japan Deployment Automation, by Approaches USD Million (2017-2022)
  • Table 46. India Deployment Automation, by Type USD Million (2017-2022)
  • Table 47. India Deployment Automation, by Application USD Million (2017-2022)
  • Table 48. India Deployment Automation, by End-User USD Million (2017-2022)
  • Table 49. India Deployment Automation, by Approaches USD Million (2017-2022)
  • Table 50. South Korea Deployment Automation, by Type USD Million (2017-2022)
  • Table 51. South Korea Deployment Automation, by Application USD Million (2017-2022)
  • Table 52. South Korea Deployment Automation, by End-User USD Million (2017-2022)
  • Table 53. South Korea Deployment Automation, by Approaches USD Million (2017-2022)
  • Table 54. Taiwan Deployment Automation, by Type USD Million (2017-2022)
  • Table 55. Taiwan Deployment Automation, by Application USD Million (2017-2022)
  • Table 56. Taiwan Deployment Automation, by End-User USD Million (2017-2022)
  • Table 57. Taiwan Deployment Automation, by Approaches USD Million (2017-2022)
  • Table 58. Australia Deployment Automation, by Type USD Million (2017-2022)
  • Table 59. Australia Deployment Automation, by Application USD Million (2017-2022)
  • Table 60. Australia Deployment Automation, by End-User USD Million (2017-2022)
  • Table 61. Australia Deployment Automation, by Approaches USD Million (2017-2022)
  • Table 62. Rest of Asia-Pacific Deployment Automation, by Type USD Million (2017-2022)
  • Table 63. Rest of Asia-Pacific Deployment Automation, by Application USD Million (2017-2022)
  • Table 64. Rest of Asia-Pacific Deployment Automation, by End-User USD Million (2017-2022)
  • Table 65. Rest of Asia-Pacific Deployment Automation, by Approaches USD Million (2017-2022)
  • Table 66. Europe Deployment Automation, by Country USD Million (2017-2022)
  • Table 67. Europe Deployment Automation, by Type USD Million (2017-2022)
  • Table 68. Europe Deployment Automation, by Application USD Million (2017-2022)
  • Table 69. Europe Deployment Automation, by End-User USD Million (2017-2022)
  • Table 70. Europe Deployment Automation, by Approaches USD Million (2017-2022)
  • Table 71. Germany Deployment Automation, by Type USD Million (2017-2022)
  • Table 72. Germany Deployment Automation, by Application USD Million (2017-2022)
  • Table 73. Germany Deployment Automation, by End-User USD Million (2017-2022)
  • Table 74. Germany Deployment Automation, by Approaches USD Million (2017-2022)
  • Table 75. France Deployment Automation, by Type USD Million (2017-2022)
  • Table 76. France Deployment Automation, by Application USD Million (2017-2022)
  • Table 77. France Deployment Automation, by End-User USD Million (2017-2022)
  • Table 78. France Deployment Automation, by Approaches USD Million (2017-2022)
  • Table 79. Italy Deployment Automation, by Type USD Million (2017-2022)
  • Table 80. Italy Deployment Automation, by Application USD Million (2017-2022)
  • Table 81. Italy Deployment Automation, by End-User USD Million (2017-2022)
  • Table 82. Italy Deployment Automation, by Approaches USD Million (2017-2022)
  • Table 83. United Kingdom Deployment Automation, by Type USD Million (2017-2022)
  • Table 84. United Kingdom Deployment Automation, by Application USD Million (2017-2022)
  • Table 85. United Kingdom Deployment Automation, by End-User USD Million (2017-2022)
  • Table 86. United Kingdom Deployment Automation, by Approaches USD Million (2017-2022)
  • Table 87. Netherlands Deployment Automation, by Type USD Million (2017-2022)
  • Table 88. Netherlands Deployment Automation, by Application USD Million (2017-2022)
  • Table 89. Netherlands Deployment Automation, by End-User USD Million (2017-2022)
  • Table 90. Netherlands Deployment Automation, by Approaches USD Million (2017-2022)
  • Table 91. Rest of Europe Deployment Automation, by Type USD Million (2017-2022)
  • Table 92. Rest of Europe Deployment Automation, by Application USD Million (2017-2022)
  • Table 93. Rest of Europe Deployment Automation, by End-User USD Million (2017-2022)
  • Table 94. Rest of Europe Deployment Automation, by Approaches USD Million (2017-2022)
  • Table 95. MEA Deployment Automation, by Country USD Million (2017-2022)
  • Table 96. MEA Deployment Automation, by Type USD Million (2017-2022)
  • Table 97. MEA Deployment Automation, by Application USD Million (2017-2022)
  • Table 98. MEA Deployment Automation, by End-User USD Million (2017-2022)
  • Table 99. MEA Deployment Automation, by Approaches USD Million (2017-2022)
  • Table 100. Middle East Deployment Automation, by Type USD Million (2017-2022)
  • Table 101. Middle East Deployment Automation, by Application USD Million (2017-2022)
  • Table 102. Middle East Deployment Automation, by End-User USD Million (2017-2022)
  • Table 103. Middle East Deployment Automation, by Approaches USD Million (2017-2022)
  • Table 104. Africa Deployment Automation, by Type USD Million (2017-2022)
  • Table 105. Africa Deployment Automation, by Application USD Million (2017-2022)
  • Table 106. Africa Deployment Automation, by End-User USD Million (2017-2022)
  • Table 107. Africa Deployment Automation, by Approaches USD Million (2017-2022)
  • Table 108. North America Deployment Automation, by Country USD Million (2017-2022)
  • Table 109. North America Deployment Automation, by Type USD Million (2017-2022)
  • Table 110. North America Deployment Automation, by Application USD Million (2017-2022)
  • Table 111. North America Deployment Automation, by End-User USD Million (2017-2022)
  • Table 112. North America Deployment Automation, by Approaches USD Million (2017-2022)
  • Table 113. United States Deployment Automation, by Type USD Million (2017-2022)
  • Table 114. United States Deployment Automation, by Application USD Million (2017-2022)
  • Table 115. United States Deployment Automation, by End-User USD Million (2017-2022)
  • Table 116. United States Deployment Automation, by Approaches USD Million (2017-2022)
  • Table 117. Canada Deployment Automation, by Type USD Million (2017-2022)
  • Table 118. Canada Deployment Automation, by Application USD Million (2017-2022)
  • Table 119. Canada Deployment Automation, by End-User USD Million (2017-2022)
  • Table 120. Canada Deployment Automation, by Approaches USD Million (2017-2022)
  • Table 121. Mexico Deployment Automation, by Type USD Million (2017-2022)
  • Table 122. Mexico Deployment Automation, by Application USD Million (2017-2022)
  • Table 123. Mexico Deployment Automation, by End-User USD Million (2017-2022)
  • Table 124. Mexico Deployment Automation, by Approaches USD Million (2017-2022)
  • Table 125. Company Basic Information, Sales Area and Its Competitors
  • Table 126. Company Basic Information, Sales Area and Its Competitors
  • Table 127. Company Basic Information, Sales Area and Its Competitors
  • Table 128. Company Basic Information, Sales Area and Its Competitors
  • Table 129. Company Basic Information, Sales Area and Its Competitors
  • Table 130. Company Basic Information, Sales Area and Its Competitors
  • Table 131. Company Basic Information, Sales Area and Its Competitors
  • Table 132. Company Basic Information, Sales Area and Its Competitors
  • Table 133. Company Basic Information, Sales Area and Its Competitors
  • Table 134. Company Basic Information, Sales Area and Its Competitors
  • Table 135. Deployment Automation: by Type(USD Million)
  • Table 136. Deployment Automation Cloud Based , by Region USD Million (2023-2028)
  • Table 137. Deployment Automation On-Premise , by Region USD Million (2023-2028)
  • Table 138. Deployment Automation: by Application(USD Million)
  • Table 139. Deployment Automation SMEs , by Region USD Million (2023-2028)
  • Table 140. Deployment Automation Large Enterprises , by Region USD Million (2023-2028)
  • Table 141. Deployment Automation: by End-User(USD Million)
  • Table 142. Deployment Automation Software developers , by Region USD Million (2023-2028)
  • Table 143. Deployment Automation Software engineers , by Region USD Million (2023-2028)
  • Table 144. Deployment Automation: by Approaches(USD Million)
  • Table 145. Deployment Automation Scripting , by Region USD Million (2023-2028)
  • Table 146. Deployment Automation Development with CI system , by Region USD Million (2023-2028)
  • Table 147. Deployment Automation Basic deployment tools , by Region USD Million (2023-2028)
  • Table 148. Deployment Automation Model-driven deployment , by Region USD Million (2023-2028)
  • Table 149. Deployment Automation Continuous deployment , by Region USD Million (2023-2028)
  • Table 150. South America Deployment Automation, by Country USD Million (2023-2028)
  • Table 151. South America Deployment Automation, by Type USD Million (2023-2028)
  • Table 152. South America Deployment Automation, by Application USD Million (2023-2028)
  • Table 153. South America Deployment Automation, by End-User USD Million (2023-2028)
  • Table 154. South America Deployment Automation, by Approaches USD Million (2023-2028)
  • Table 155. Brazil Deployment Automation, by Type USD Million (2023-2028)
  • Table 156. Brazil Deployment Automation, by Application USD Million (2023-2028)
  • Table 157. Brazil Deployment Automation, by End-User USD Million (2023-2028)
  • Table 158. Brazil Deployment Automation, by Approaches USD Million (2023-2028)
  • Table 159. Argentina Deployment Automation, by Type USD Million (2023-2028)
  • Table 160. Argentina Deployment Automation, by Application USD Million (2023-2028)
  • Table 161. Argentina Deployment Automation, by End-User USD Million (2023-2028)
  • Table 162. Argentina Deployment Automation, by Approaches USD Million (2023-2028)
  • Table 163. Rest of South America Deployment Automation, by Type USD Million (2023-2028)
  • Table 164. Rest of South America Deployment Automation, by Application USD Million (2023-2028)
  • Table 165. Rest of South America Deployment Automation, by End-User USD Million (2023-2028)
  • Table 166. Rest of South America Deployment Automation, by Approaches USD Million (2023-2028)
  • Table 167. Asia Pacific Deployment Automation, by Country USD Million (2023-2028)
  • Table 168. Asia Pacific Deployment Automation, by Type USD Million (2023-2028)
  • Table 169. Asia Pacific Deployment Automation, by Application USD Million (2023-2028)
  • Table 170. Asia Pacific Deployment Automation, by End-User USD Million (2023-2028)
  • Table 171. Asia Pacific Deployment Automation, by Approaches USD Million (2023-2028)
  • Table 172. China Deployment Automation, by Type USD Million (2023-2028)
  • Table 173. China Deployment Automation, by Application USD Million (2023-2028)
  • Table 174. China Deployment Automation, by End-User USD Million (2023-2028)
  • Table 175. China Deployment Automation, by Approaches USD Million (2023-2028)
  • Table 176. Japan Deployment Automation, by Type USD Million (2023-2028)
  • Table 177. Japan Deployment Automation, by Application USD Million (2023-2028)
  • Table 178. Japan Deployment Automation, by End-User USD Million (2023-2028)
  • Table 179. Japan Deployment Automation, by Approaches USD Million (2023-2028)
  • Table 180. India Deployment Automation, by Type USD Million (2023-2028)
  • Table 181. India Deployment Automation, by Application USD Million (2023-2028)
  • Table 182. India Deployment Automation, by End-User USD Million (2023-2028)
  • Table 183. India Deployment Automation, by Approaches USD Million (2023-2028)
  • Table 184. South Korea Deployment Automation, by Type USD Million (2023-2028)
  • Table 185. South Korea Deployment Automation, by Application USD Million (2023-2028)
  • Table 186. South Korea Deployment Automation, by End-User USD Million (2023-2028)
  • Table 187. South Korea Deployment Automation, by Approaches USD Million (2023-2028)
  • Table 188. Taiwan Deployment Automation, by Type USD Million (2023-2028)
  • Table 189. Taiwan Deployment Automation, by Application USD Million (2023-2028)
  • Table 190. Taiwan Deployment Automation, by End-User USD Million (2023-2028)
  • Table 191. Taiwan Deployment Automation, by Approaches USD Million (2023-2028)
  • Table 192. Australia Deployment Automation, by Type USD Million (2023-2028)
  • Table 193. Australia Deployment Automation, by Application USD Million (2023-2028)
  • Table 194. Australia Deployment Automation, by End-User USD Million (2023-2028)
  • Table 195. Australia Deployment Automation, by Approaches USD Million (2023-2028)
  • Table 196. Rest of Asia-Pacific Deployment Automation, by Type USD Million (2023-2028)
  • Table 197. Rest of Asia-Pacific Deployment Automation, by Application USD Million (2023-2028)
  • Table 198. Rest of Asia-Pacific Deployment Automation, by End-User USD Million (2023-2028)
  • Table 199. Rest of Asia-Pacific Deployment Automation, by Approaches USD Million (2023-2028)
  • Table 200. Europe Deployment Automation, by Country USD Million (2023-2028)
  • Table 201. Europe Deployment Automation, by Type USD Million (2023-2028)
  • Table 202. Europe Deployment Automation, by Application USD Million (2023-2028)
  • Table 203. Europe Deployment Automation, by End-User USD Million (2023-2028)
  • Table 204. Europe Deployment Automation, by Approaches USD Million (2023-2028)
  • Table 205. Germany Deployment Automation, by Type USD Million (2023-2028)
  • Table 206. Germany Deployment Automation, by Application USD Million (2023-2028)
  • Table 207. Germany Deployment Automation, by End-User USD Million (2023-2028)
  • Table 208. Germany Deployment Automation, by Approaches USD Million (2023-2028)
  • Table 209. France Deployment Automation, by Type USD Million (2023-2028)
  • Table 210. France Deployment Automation, by Application USD Million (2023-2028)
  • Table 211. France Deployment Automation, by End-User USD Million (2023-2028)
  • Table 212. France Deployment Automation, by Approaches USD Million (2023-2028)
  • Table 213. Italy Deployment Automation, by Type USD Million (2023-2028)
  • Table 214. Italy Deployment Automation, by Application USD Million (2023-2028)
  • Table 215. Italy Deployment Automation, by End-User USD Million (2023-2028)
  • Table 216. Italy Deployment Automation, by Approaches USD Million (2023-2028)
  • Table 217. United Kingdom Deployment Automation, by Type USD Million (2023-2028)
  • Table 218. United Kingdom Deployment Automation, by Application USD Million (2023-2028)
  • Table 219. United Kingdom Deployment Automation, by End-User USD Million (2023-2028)
  • Table 220. United Kingdom Deployment Automation, by Approaches USD Million (2023-2028)
  • Table 221. Netherlands Deployment Automation, by Type USD Million (2023-2028)
  • Table 222. Netherlands Deployment Automation, by Application USD Million (2023-2028)
  • Table 223. Netherlands Deployment Automation, by End-User USD Million (2023-2028)
  • Table 224. Netherlands Deployment Automation, by Approaches USD Million (2023-2028)
  • Table 225. Rest of Europe Deployment Automation, by Type USD Million (2023-2028)
  • Table 226. Rest of Europe Deployment Automation, by Application USD Million (2023-2028)
  • Table 227. Rest of Europe Deployment Automation, by End-User USD Million (2023-2028)
  • Table 228. Rest of Europe Deployment Automation, by Approaches USD Million (2023-2028)
  • Table 229. MEA Deployment Automation, by Country USD Million (2023-2028)
  • Table 230. MEA Deployment Automation, by Type USD Million (2023-2028)
  • Table 231. MEA Deployment Automation, by Application USD Million (2023-2028)
  • Table 232. MEA Deployment Automation, by End-User USD Million (2023-2028)
  • Table 233. MEA Deployment Automation, by Approaches USD Million (2023-2028)
  • Table 234. Middle East Deployment Automation, by Type USD Million (2023-2028)
  • Table 235. Middle East Deployment Automation, by Application USD Million (2023-2028)
  • Table 236. Middle East Deployment Automation, by End-User USD Million (2023-2028)
  • Table 237. Middle East Deployment Automation, by Approaches USD Million (2023-2028)
  • Table 238. Africa Deployment Automation, by Type USD Million (2023-2028)
  • Table 239. Africa Deployment Automation, by Application USD Million (2023-2028)
  • Table 240. Africa Deployment Automation, by End-User USD Million (2023-2028)
  • Table 241. Africa Deployment Automation, by Approaches USD Million (2023-2028)
  • Table 242. North America Deployment Automation, by Country USD Million (2023-2028)
  • Table 243. North America Deployment Automation, by Type USD Million (2023-2028)
  • Table 244. North America Deployment Automation, by Application USD Million (2023-2028)
  • Table 245. North America Deployment Automation, by End-User USD Million (2023-2028)
  • Table 246. North America Deployment Automation, by Approaches USD Million (2023-2028)
  • Table 247. United States Deployment Automation, by Type USD Million (2023-2028)
  • Table 248. United States Deployment Automation, by Application USD Million (2023-2028)
  • Table 249. United States Deployment Automation, by End-User USD Million (2023-2028)
  • Table 250. United States Deployment Automation, by Approaches USD Million (2023-2028)
  • Table 251. Canada Deployment Automation, by Type USD Million (2023-2028)
  • Table 252. Canada Deployment Automation, by Application USD Million (2023-2028)
  • Table 253. Canada Deployment Automation, by End-User USD Million (2023-2028)
  • Table 254. Canada Deployment Automation, by Approaches USD Million (2023-2028)
  • Table 255. Mexico Deployment Automation, by Type USD Million (2023-2028)
  • Table 256. Mexico Deployment Automation, by Application USD Million (2023-2028)
  • Table 257. Mexico Deployment Automation, by End-User USD Million (2023-2028)
  • Table 258. Mexico Deployment Automation, by Approaches USD Million (2023-2028)
  • Table 259. Research Programs/Design for This Report
  • Table 260. Key Data Information from Secondary Sources
  • Table 261. Key Data Information from Primary Sources
List of Figures
  • Figure 1. Porters Five Forces
  • Figure 2. Supply/Value Chain
  • Figure 3. PESTEL analysis
  • Figure 4. Global Deployment Automation: by Type USD Million (2017-2022)
  • Figure 5. Global Deployment Automation: by Application USD Million (2017-2022)
  • Figure 6. Global Deployment Automation: by End-User USD Million (2017-2022)
  • Figure 7. Global Deployment Automation: by Approaches USD Million (2017-2022)
  • Figure 8. South America Deployment Automation Share (%), by Country
  • Figure 9. Asia Pacific Deployment Automation Share (%), by Country
  • Figure 10. Europe Deployment Automation Share (%), by Country
  • Figure 11. MEA Deployment Automation Share (%), by Country
  • Figure 12. North America Deployment Automation Share (%), by Country
  • Figure 13. Global Deployment Automation share by Players 2022 (%)
  • Figure 14. Global Deployment Automation share by Players (Top 3) 2022(%)
  • Figure 15. Global Deployment Automation share by Players (Top 5) 2022(%)
  • Figure 16. BCG Matrix for key Companies
  • Figure 17. Microsoft (United States) Revenue, Net Income and Gross profit
  • Figure 18. Microsoft (United States) Revenue: by Geography 2022
  • Figure 19. JetBrains (Czechia) Revenue, Net Income and Gross profit
  • Figure 20. JetBrains (Czechia) Revenue: by Geography 2022
  • Figure 21. Octopus deploy (Australia) Revenue, Net Income and Gross profit
  • Figure 22. Octopus deploy (Australia) Revenue: by Geography 2022
  • Figure 23. GitLab Inc (United States) Revenue, Net Income and Gross profit
  • Figure 24. GitLab Inc (United States) Revenue: by Geography 2022
  • Figure 25. Appveyor (Canada) Revenue, Net Income and Gross profit
  • Figure 26. Appveyor (Canada) Revenue: by Geography 2022
  • Figure 27. Atlassian (Australia) Revenue, Net Income and Gross profit
  • Figure 28. Atlassian (Australia) Revenue: by Geography 2022
  • Figure 29. Stackify (United States) Revenue, Net Income and Gross profit
  • Figure 30. Stackify (United States) Revenue: by Geography 2022
  • Figure 31. XebiaLabs develops (United States) Revenue, Net Income and Gross profit
  • Figure 32. XebiaLabs develops (United States) Revenue: by Geography 2022
  • Figure 33. PDQ (United States) Revenue, Net Income and Gross profit
  • Figure 34. PDQ (United States) Revenue: by Geography 2022
  • Figure 35. Chef (United States) Revenue, Net Income and Gross profit
  • Figure 36. Chef (United States) Revenue: by Geography 2022
  • Figure 37. Global Deployment Automation: by Type USD Million (2023-2028)
  • Figure 38. Global Deployment Automation: by Application USD Million (2023-2028)
  • Figure 39. Global Deployment Automation: by End-User USD Million (2023-2028)
  • Figure 40. Global Deployment Automation: by Approaches USD Million (2023-2028)
  • Figure 41. South America Deployment Automation Share (%), by Country
  • Figure 42. Asia Pacific Deployment Automation Share (%), by Country
  • Figure 43. Europe Deployment Automation Share (%), by Country
  • Figure 44. MEA Deployment Automation Share (%), by Country
  • Figure 45. North America Deployment Automation Share (%), by Country
List of companies from research coverage that are profiled in the study
  • Microsoft (United States)
  • JetBrains (Czechia)
  • Octopus deploy (Australia)
  • GitLab Inc (United States)
  • Appveyor (Canada)
  • Atlassian (Australia)
  • Stackify (United States)
  • XebiaLabs develops (United States)
  • PDQ (United States)
  • Chef (United States)
Additional players considered in the study are as follows:
DeployBot (United States) , CircleCI (United States) , Amazon (United States) , Codeship (United States)
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Key Highlights of Report


Dec 2023 203 Pages 80 Tables Base Year: 2022 Coverage: 15+ Companies; 18 Countries

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Global Deployment Automation Market Quantitative research analysis
Global Deployment Automation Market Qualitative Industry Analysis
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Frequently Asked Questions (FAQ):

The standard version of the report profiles players such as Microsoft (United States), JetBrains (Czechia), Octopus deploy (Australia), GitLab Inc (United States), Appveyor (Canada), Atlassian (Australia), Stackify (United States), XebiaLabs develops (United States), PDQ (United States) and Chef (United States) etc.
The Study can be customized subject to feasibility and data availability. Please connect with our sales representative for further information.
"Highly Recommended As Developers Can Spend Time Working On New Features, Not On Fixes For Manual Deployments" is seen as one of major influencing trends for Deployment Automation Market during projected period 2022-2028.
The Deployment Automation market study includes a random mix of players, including both market leaders and some top growing emerging players. Connect with our sales executive to get a complete company list in our research coverage.

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