Edit
Bizwit-Logo-Final

Bizwit Research & Consulting LLP is a global provider of business intelligence & consulting services. We have a strong primary base of key industry leaders along with the chain of industry analysts to analyze the market trends and its future impact in order to estimates and forecast different business segments and markets. 

Global Cloud Orchestration Market to reach USD 94.02 billion by the end of 2030.

Global Cloud Orchestration Market Size study & Forecast, by Application (Cloud Service Management, Cloud DevOps, Cloud Migration, API Management) By Deployment Type (On-Premise, SaaS) By Operating Environment (Private, Public, Hybrid) By Verticals (Healthcare, Transportation & Logistics, Government, Manufacturing, IT & Telecom, Others) and Regional Analysis, 2023-2030

Product Code: ICTICTS-78896304
Publish Date: 10-06-2023
Page: 200

Global Cloud Orchestration Market is valued approximately USD 17.49 billion in 2022 and is anticipated to grow with a healthy growth rate of more than 23.4% over the forecast period 2023-2030. Cloud orchestration refers to the process of automating and coordinating the deployment, management, and operation of cloud-based resources and services. It involves using software tools and frameworks to manage the provisioning, scaling, and monitoring of various cloud resources such as virtual machines, containers, databases, storage, and networking. The Cloud Orchestration market is expanding because of factors such as increasing adoption of cloud-based applications and rising emergence of automation. Cloud orchestration helps to simplify the management of complex cloud infrastructures by enabling administrators to create and manage resources and services through a single, centralized interface. It allows organizations to optimize resource utilization, automate workflows, and achieve greater agility and scalability. Its importance has progressively increased during the last few decades.

According to the Statista, in 2021, the global cloud applications market had a value of USD 133.6 billion and projected to reach up to USD 168.6 billion by 2025. The cloud applications software market is anticipated to grow at a compound annual growth rate of 4.8%. Furthermore, in 2022, 46% of respondents were already running significant workloads on Amazon Web Services. Another important component driving space is emergence of automation. As per Statista, in 2021, the global intelligent process automation market has reached approximately USD 20 billion, at a growth rate of 16% and forecasted to reach up to USD 30 billion by the year 2024. In addition, the process automation market exceeds USD 83 billion as Industrial software alone accounts USD 43 billion in 2021. However, the high initial cost of Cloud Orchestration stifles market growth throughout the forecast period of 2023-2030.

The key regions considered for the Global Cloud Orchestration Market study includes Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the market in 2022 owing to the rising need for advanced resource management system and shifting of workloads to cloud environment. According to the Statista, the Public Cloud market is projected to reach USD 273.40 billion in 2023. Furthermore, Asia Pacific is expected to grow significantly during the forecast period, owing to factors such as rising industrial automation and rising government initiatives in digitalization in the market space.

Major market player included in this report are:
Amazon web services, inc
BMC software, inc.
Cisco Systems, inc.
DXC technologies ltd.
Hewlett packard enterprise
IBM corporation
Vmware, inc.
Rackspace us, inc.
Oracle corporation
Flexiscale technologies limited

Recent Developments in the Market:
Ø In March 2023, IBM and Wasabi Technologies, collaborates together to drive data innovation across hybrid cloud environments. This collaboration will enable organizations to run applications in any environment and help customers in accessing and utilizing key business information and analytics in real time at affordable prices.

Global Cloud Orchestration Market Report Scope:
ü Historical Data – 2020 – 2021
ü Base Year for Estimation – 2022
ü Forecast period – 2023-2030
ü Report Coverage – Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
ü Segments Covered – Application, Deployment Type, Operating Environment, Verticals, Region
ü Regional Scope – North America; Europe; Asia Pacific; Latin America; Middle East & Africa
ü Customization Scope – Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments.

By Application

Cloud Service Management
Cloud DevOps
Cloud Migration
API Management

By Deployment Type

On-Premise
SaaS

By Operating Environment

Private
Public
Hybrid

By Verticals

Healthcare
Transportation & Logistics
Government
Manufacturing
IT & Telecom
Others

By Region:

North America
U.S.
Canada

Europe
UK
Germany
France
Spain
Italy
ROE

Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC

Latin America
Brazil
Mexico

Middle East & Africa
Saudi Arabia
South Africa
Rest of Middle East & Africa

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2030 (USD Billion)
1.2.1. Cloud Orchestration Market, by Region, 2020-2030 (USD Billion)
1.2.2. Cloud Orchestration Market, by Application, 2020-2030 (USD Billion)
1.2.3. Cloud Orchestration Market, by Deployment Type, 2020-2030 (USD Billion)
1.2.4. Cloud Orchestration Market, by Operating Environment, 2020-2030 (USD Billion)
1.2.5. Cloud Orchestration Market, by Verticals, 2020-2030 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Cloud Orchestration Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Industry Evolution
2.2.2. Scope of the Study
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Cloud Orchestration Market Dynamics
3.1. Cloud Orchestration Market Impact Analysis (2020-2030)
3.1.1. Market Drivers
3.1.1.1. Increasing adoption of cloud-based applications
3.1.1.2. Rising emergence of automation
3.1.2. Market Challenges
3.1.2.1. High initial cost of cloud orchestration
3.1.3. Market Opportunities
3.1.3.1. Rising technical advancements in Cloud Orchestration
3.1.3.2. Increasing need for self-service provisioning.

Chapter 4. Global Cloud Orchestration Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.2. Porter’s 5 Force Impact Analysis
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.3.5. Environmental
4.3.6. Legal
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. COVID-19 Impact Analysis
4.7. Disruptive Trends
4.8. Industry Expert Perspective
4.9. Analyst Recommendation & Conclusion
Chapter 5. Global Cloud Orchestration Market, by Application
5.1. Market Snapshot
5.2. Global Cloud Orchestration Market by Application, Performance – Potential Analysis
5.3. Global Cloud Orchestration Market Estimates & Forecasts by Application 2020-2030 (USD Billion)
5.4. Cloud Orchestration Market, Sub Segment Analysis
5.4.1. Cloud Service Management
5.4.2. Cloud DevOps
5.4.3. Cloud Migration
5.4.4. API Management
Chapter 6. Global Cloud Orchestration Market, by Deployment Type
6.1. Market Snapshot
6.2. Global Cloud Orchestration Market by Deployment Type, Performance – Potential Analysis
6.3. Global Cloud Orchestration Market Estimates & Forecasts by Deployment Type 2020-2030 (USD Billion)
6.4. Cloud Orchestration Market, Sub Segment Analysis
6.4.1. On-Premise
6.4.2. SaaS
Chapter 7. Global Cloud Orchestration Market, by Operating Environment
7.1. Market Snapshot
7.2. Global Cloud Orchestration Market by Operating Environment, Performance – Potential Analysis
7.3. Global Cloud Orchestration Market Estimates & Forecasts by Operating Environment 2020-2030 (USD Billion)
7.4. Cloud Orchestration Market, Sub Segment Analysis
7.4.1. Private
7.4.2. Public
7.4.3. Hybrid
Chapter 8. Global Cloud Orchestration Market, by Verticals
8.1. Market Snapshot
8.2. Global Cloud Orchestration Market by Verticals, Performance – Potential Analysis
8.3. Global Cloud Orchestration Market Estimates & Forecasts by Verticals 2020-2030 (USD Billion)
8.4. Cloud Orchestration Market, Sub Segment Analysis
8.4.1. Healthcare
8.4.2. Transportation & Logistics
8.4.3. Government
8.4.4. Manufacturing
8.4.5. IT & Telecom
8.4.6. Others
Chapter 9. Global Cloud Orchestration Market, Regional Analysis
9.1. Top Leading Countries
9.2. Top Emerging Countries
9.3. Cloud Orchestration Market, Regional Market Snapshot
9.4. North America Cloud Orchestration Market
9.4.1. U.S. Cloud Orchestration Market
9.4.1.1. Application breakdown estimates & forecasts, 2020-2030
9.4.1.2. Deployment Type breakdown estimates & forecasts, 2020-2030
9.4.1.3. Operating Environment breakdown estimates & forecasts, 2020-2030
9.4.1.4. Verticals breakdown estimates & forecasts, 2020-2030
9.4.2. Canada Cloud Orchestration Market
9.5. Europe Cloud Orchestration Market Snapshot
9.5.1. U.K. Cloud Orchestration Market
9.5.2. Germany Cloud Orchestration Market
9.5.3. France Cloud Orchestration Market
9.5.4. Spain Cloud Orchestration Market
9.5.5. Italy Cloud Orchestration Market
9.5.6. Rest of Europe Cloud Orchestration Market
9.6. Asia-Pacific Cloud Orchestration Market Snapshot
9.6.1. China Cloud Orchestration Market
9.6.2. India Cloud Orchestration Market
9.6.3. Japan Cloud Orchestration Market
9.6.4. Australia Cloud Orchestration Market
9.6.5. South Korea Cloud Orchestration Market
9.6.6. Rest of Asia Pacific Cloud Orchestration Market
9.7. Latin America Cloud Orchestration Market Snapshot
9.7.1. Brazil Cloud Orchestration Market
9.7.2. Mexico Cloud Orchestration Market
9.8. Middle East & Africa Cloud Orchestration Market
9.8.1. Saudi Arabia Cloud Orchestration Market
9.8.2. South Africa Cloud Orchestration Market
9.8.3. Rest of Middle East & Africa Cloud Orchestration Market

Chapter 10. Competitive Intelligence
10.1. Key Company SWOT Analysis
10.1.1. Company 1
10.1.2. Company 2
10.1.3. Company 3
10.2. Top Market Strategies
10.3. Company Profiles
10.3.1. Amazon web services, Inc
10.3.1.1. Key Information
10.3.1.2. Overview
10.3.1.3. Financial (Subject to Data Availability)
10.3.1.4. Product Summary
10.3.1.5. Recent Developments
10.3.2. BMC software, Inc.
10.3.3. Cisco Systems, Inc.
10.3.4. DXC technologies ltd.
10.3.5. Hewlett packard enterprise
10.3.6. IBM corporation
10.3.7. Vmware, Inc.
10.3.8. Rackspace us, Inc.
10.3.9. Oracle corporation
10.3.10. Flexiscale technologies limited
Chapter 11. Research Process
11.1. Research Process
11.1.1. Data Mining
11.1.2. Analysis
11.1.3. Market Estimation
11.1.4. Validation
11.1.5. Publishing
11.2. Research Attributes
11.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

Need Assistance

Contact Person -
Krishant Mennon
Call us @
+ 91 99931 15879
Email: sales@bizwitresearch.com

Checkout

Why Choose Us?

Quality over Quantity

Backed by 60+ paid data sources our reports deliver crisp insights with no compromise quality.

Analyst Support

24x7 Chat Support plus
free analyst hours with every purchase

Flawless Methodology

Our 360-degree approach of market study, our research methods leave stones unturned.
Enquiry Now