Global Automated Cloud Cost Optimization Platform 麻豆原创 Research Report 2025

Publication ID:

PB503250468

Publication Date:

March 6, 2025

Pages:

Publisher:

MRRPB5

Countries:

Global [1]

USD 2,900.00

IT Services [2]

Computing & Electronics [3]

Description:

The global market for Automated Cloud Cost Optimization Platform was valued at US$ 1506 million in the year 2024 and is projected to reach a revised size of US$ 3031 million by 2031, growing at a CAGR of 10.6% during the forecast period.
The automated cloud cost optimization platform is an intelligent tool based on the cloud computing environment, which is designed to automatically analyze, monitor and optimize the use of cloud service resources to reduce the cost of enterprises on the cloud platform. The platform identifies overuse or idle resources through real-time data analysis, and provides automated adjustment suggestions or directly schedules resources to achieve reasonable resource allocation and cost control. By optimizing the use of cloud infrastructure, enterprises can reduce unnecessary expenses while ensuring the efficiency and scalability of business operations.
North American market for Automated Cloud Cost Optimization Platform is estimated to increase from $ million in 2024 to reach $ million by 2031, at a CAGR of % during the forecast period of 2025 through 2031.
Asia-Pacific market for Automated Cloud Cost Optimization Platform is estimated to increase from $ million in 2024 to reach $ million by 2031, at a CAGR of % during the forecast period of 2025 through 2031.
The global market for Automated Cloud Cost Optimization Platform in Financial Industry is estimated to increase from $ million in 2024 to $ million by 2031, at a CAGR of % during the forecast period of 2025 through 2031.
The major global companies of Automated Cloud Cost Optimization Platform include CloudHealth by VMware, Kubecost, Microsoft, Amazon Web Services, Flexera, ParkMyCloud, Apptio, etc. In 2024, the world's top three vendors accounted for approximately % of the revenue.
This report aims to provide a comprehensive presentation of the global market for Automated Cloud Cost Optimization Platform, with both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Automated Cloud Cost Optimization Platform.
The Automated Cloud Cost Optimization Platform market size, estimations, and forecasts are provided in terms of and revenue ($ millions), considering 2024 as the base year, with history and forecast data for the period from 2020 to 2031. This report segments the global Automated Cloud Cost Optimization Platform market comprehensively. Regional market sizes, concerning products by Type, by Application, and by players, are also provided.
For a more in-depth understanding of the market, the report provides profiles of the competitive landscape, key competitors, and their respective market ranks. The report also discusses technological trends and new product developments.
The report will help the Automated Cloud Cost Optimization Platform companies, new entrants, and industry chain related companies in this market with information on the revenues for the overall market and the sub-segments across the different segments, by company, by Type, by Application, and by regions.
麻豆原创 Segmentation
By Company
CloudHealth by VMware
Kubecost
Microsoft
Amazon Web Services
Flexera
ParkMyCloud
Apptio
Segment by Type
Single Cloud Cost Optimization Platform
Multi-Cloud Cost Optimization Platform
Segment by Application
Financial Industry
Manufacturing Industry
Medical Industry
Education Industry
By Region
North America
United States
Canada
Asia-Pacific
China
Japan
South Korea
Southeast Asia
India
Australia
Rest of Asia
Europe
Germany
France
U.K.
Italy
Russia
Nordic Countries
Rest of Europe
Latin America
Mexico
Brazil
Rest of Latin America
Middle East & Africa
Turkey
Saudi Arabia
UAE
Rest of MEA
Chapter Outline
Chapter 1: Introduces the report scope of the report, executive summary of different market segments (by Type, by Application, etc), including the market size of each market segment, future development potential, and so on. It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter 2: Introduces executive summary of global market size, regional market size, this section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter 3: Detailed analysis of Automated Cloud Cost Optimization Platform company competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 4: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 5: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 6, 7, 8, 9, 10: North America, Europe, Asia Pacific, Latin America, Middle East and Africa segment by country. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space, and capacity of each country in the world.
Chapter 11: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product sales, revenue, price, gross margin, product introduction, recent development, etc.
Chapter 12: The main points and conclusions of the report.

Please Note - This is an on demand report and will be delivered in 2 business days (48 hours) post payment.

Table Of Contents:

1 Report Overview
1.1 Study Scope
1.2 麻豆原创 Analysis by Type
1.2.1 Global Automated Cloud Cost Optimization Platform 麻豆原创 Size Growth Rate by Type: 2020 VS 2024 VS 2031
1.2.2 Single Cloud Cost Optimization Platform
1.2.3 Multi-Cloud Cost Optimization Platform
1.3 麻豆原创 by Application
1.3.1 Global Automated Cloud Cost Optimization Platform 麻豆原创 Growth by Application: 2020 VS 2024 VS 2031
1.3.2 Financial Industry
1.3.3 Manufacturing Industry
1.3.4 Medical Industry
1.3.5 Education Industry
1.4 Assumptions and Limitations
1.5 Study Objectives
1.6 Years Considered
2 Global Growth Trends
2.1 Global Automated Cloud Cost Optimization Platform 麻豆原创 Perspective (2020-2031)
2.2 Global Automated Cloud Cost Optimization Platform Growth Trends by Region
2.2.1 Global Automated Cloud Cost Optimization Platform 麻豆原创 Size by Region: 2020 VS 2024 VS 2031
2.2.2 Automated Cloud Cost Optimization Platform Historic 麻豆原创 Size by Region (2020-2025)
2.2.3 Automated Cloud Cost Optimization Platform Forecasted 麻豆原创 Size by Region (2026-2031)
2.3 Automated Cloud Cost Optimization Platform 麻豆原创 Dynamics
2.3.1 Automated Cloud Cost Optimization Platform Industry Trends
2.3.2 Automated Cloud Cost Optimization Platform 麻豆原创 Drivers
2.3.3 Automated Cloud Cost Optimization Platform 麻豆原创 Challenges
2.3.4 Automated Cloud Cost Optimization Platform 麻豆原创 Restraints
3 Competition Landscape by Key Players
3.1 Global Top Automated Cloud Cost Optimization Platform Players by Revenue
3.1.1 Global Top Automated Cloud Cost Optimization Platform Players by Revenue (2020-2025)
3.1.2 Global Automated Cloud Cost Optimization Platform Revenue 麻豆原创 Share by Players (2020-2025)
3.2 Global Top Automated Cloud Cost Optimization Platform Players by Company Type and 麻豆原创 Share by Company Type (Tier 1, Tier 2, and Tier 3)
3.3 Global Key Players Ranking by Automated Cloud Cost Optimization Platform Revenue
3.4 Global Automated Cloud Cost Optimization Platform 麻豆原创 Concentration Ratio
3.4.1 Global Automated Cloud Cost Optimization Platform 麻豆原创 Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by Automated Cloud Cost Optimization Platform Revenue in 2024
3.5 Global Key Players of Automated Cloud Cost Optimization Platform Head office and Area Served
3.6 Global Key Players of Automated Cloud Cost Optimization Platform, Product and Application
3.7 Global Key Players of Automated Cloud Cost Optimization Platform, Date of Enter into This Industry
3.8 Mergers & Acquisitions, Expansion Plans
4 Automated Cloud Cost Optimization Platform Breakdown Data by Type
4.1 Global Automated Cloud Cost Optimization Platform Historic 麻豆原创 Size by Type (2020-2025)
4.2 Global Automated Cloud Cost Optimization Platform Forecasted 麻豆原创 Size by Type (2026-2031)
5 Automated Cloud Cost Optimization Platform Breakdown Data by Application
5.1 Global Automated Cloud Cost Optimization Platform Historic 麻豆原创 Size by Application (2020-2025)
5.2 Global Automated Cloud Cost Optimization Platform Forecasted 麻豆原创 Size by Application (2026-2031)
6 North America
6.1 North America Automated Cloud Cost Optimization Platform 麻豆原创 Size (2020-2031)
6.2 North America Automated Cloud Cost Optimization Platform 麻豆原创 Growth Rate by Country: 2020 VS 2024 VS 2031
6.3 North America Automated Cloud Cost Optimization Platform 麻豆原创 Size by Country (2020-2025)
6.4 North America Automated Cloud Cost Optimization Platform 麻豆原创 Size by Country (2026-2031)
6.5 United States
6.6 Canada
7 Europe
7.1 Europe Automated Cloud Cost Optimization Platform 麻豆原创 Size (2020-2031)
7.2 Europe Automated Cloud Cost Optimization Platform 麻豆原创 Growth Rate by Country: 2020 VS 2024 VS 2031
7.3 Europe Automated Cloud Cost Optimization Platform 麻豆原创 Size by Country (2020-2025)
7.4 Europe Automated Cloud Cost Optimization Platform 麻豆原创 Size by Country (2026-2031)
7.5 Germany
7.6 France
7.7 U.K.
7.8 Italy
7.9 Russia
7.10 Nordic Countries
8 Asia-Pacific
8.1 Asia-Pacific Automated Cloud Cost Optimization Platform 麻豆原创 Size (2020-2031)
8.2 Asia-Pacific Automated Cloud Cost Optimization Platform 麻豆原创 Growth Rate by Region: 2020 VS 2024 VS 2031
8.3 Asia-Pacific Automated Cloud Cost Optimization Platform 麻豆原创 Size by Region (2020-2025)
8.4 Asia-Pacific Automated Cloud Cost Optimization Platform 麻豆原创 Size by Region (2026-2031)
8.5 China
8.6 Japan
8.7 South Korea
8.8 Southeast Asia
8.9 India
8.10 Australia
9 Latin America
9.1 Latin America Automated Cloud Cost Optimization Platform 麻豆原创 Size (2020-2031)
9.2 Latin America Automated Cloud Cost Optimization Platform 麻豆原创 Growth Rate by Country: 2020 VS 2024 VS 2031
9.3 Latin America Automated Cloud Cost Optimization Platform 麻豆原创 Size by Country (2020-2025)
9.4 Latin America Automated Cloud Cost Optimization Platform 麻豆原创 Size by Country (2026-2031)
9.5 Mexico
9.6 Brazil
10 Middle East & Africa
10.1 Middle East & Africa Automated Cloud Cost Optimization Platform 麻豆原创 Size (2020-2031)
10.2 Middle East & Africa Automated Cloud Cost Optimization Platform 麻豆原创 Growth Rate by Country: 2020 VS 2024 VS 2031
10.3 Middle East & Africa Automated Cloud Cost Optimization Platform 麻豆原创 Size by Country (2020-2025)
10.4 Middle East & Africa Automated Cloud Cost Optimization Platform 麻豆原创 Size by Country (2026-2031)
10.5 Turkey
10.6 Saudi Arabia
10.7 UAE
11 Key Players Profiles
11.1 CloudHealth by VMware
11.1.1 CloudHealth by VMware Company Details
11.1.2 CloudHealth by VMware Business Overview
11.1.3 CloudHealth by VMware Automated Cloud Cost Optimization Platform Introduction
11.1.4 CloudHealth by VMware Revenue in Automated Cloud Cost Optimization Platform Business (2020-2025)
11.1.5 CloudHealth by VMware Recent Development
11.2 Kubecost
11.2.1 Kubecost Company Details
11.2.2 Kubecost Business Overview
11.2.3 Kubecost Automated Cloud Cost Optimization Platform Introduction
11.2.4 Kubecost Revenue in Automated Cloud Cost Optimization Platform Business (2020-2025)
11.2.5 Kubecost Recent Development
11.3 Microsoft
11.3.1 Microsoft Company Details
11.3.2 Microsoft Business Overview
11.3.3 Microsoft Automated Cloud Cost Optimization Platform Introduction
11.3.4 Microsoft Revenue in Automated Cloud Cost Optimization Platform Business (2020-2025)
11.3.5 Microsoft Recent Development
11.4 Amazon Web Services
11.4.1 Amazon Web Services Company Details
11.4.2 Amazon Web Services Business Overview
11.4.3 Amazon Web Services Automated Cloud Cost Optimization Platform Introduction
11.4.4 Amazon Web Services Revenue in Automated Cloud Cost Optimization Platform Business (2020-2025)
11.4.5 Amazon Web Services Recent Development
11.5 Flexera
11.5.1 Flexera Company Details
11.5.2 Flexera Business Overview
11.5.3 Flexera Automated Cloud Cost Optimization Platform Introduction
11.5.4 Flexera Revenue in Automated Cloud Cost Optimization Platform Business (2020-2025)
11.5.5 Flexera Recent Development
11.6 ParkMyCloud
11.6.1 ParkMyCloud Company Details
11.6.2 ParkMyCloud Business Overview
11.6.3 ParkMyCloud Automated Cloud Cost Optimization Platform Introduction
11.6.4 ParkMyCloud Revenue in Automated Cloud Cost Optimization Platform Business (2020-2025)
11.6.5 ParkMyCloud Recent Development
11.7 Apptio
11.7.1 Apptio Company Details
11.7.2 Apptio Business Overview
11.7.3 Apptio Automated Cloud Cost Optimization Platform Introduction
11.7.4 Apptio Revenue in Automated Cloud Cost Optimization Platform Business (2020-2025)
11.7.5 Apptio Recent Development
12 Analyst's Viewpoints/Conclusions
13 Appendix
13.1 Research Methodology
13.1.1 Methodology/Research Approach
13.1.1.1 Research Programs/Design
13.1.1.2 麻豆原创 Size Estimation
13.1.1.3 麻豆原创 Breakdown and Data Triangulation
13.1.2 Data Source
13.1.2.1 Secondary Sources
13.1.2.2 Primary Sources
13.2 Author Details
13.3 Disclaimer

Companies Mentioned:

CloudHealth by VMware
Kubecost
Microsoft
Amazon Web Services
Flexera
ParkMyCloud
Apptio

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