MLOps is the process of taking an experimental Machine Learning model into a production system. The word is a compound of ?Machine Learning? and the continuous development practice of DevOps in the software field. Machine Learning models are tested and developed in isolated experimental systems. When an algorithm is ready to be launched, MLOps is practiced between Data Scientists, DevOps, and Machine Learning engineers to transition the algorithm to production systems. Similar to DevOps or DataOps approaches, MLOps seeks to increase automation and improve the quality of production models, while also focusing on business and regulatory requirements. While MLOps started as a set of best practices, it is slowly evolving into an independent approach to ML lifecycle management. MLOps applies to the entire lifecycle - from integrating with model generation (software development lifecycle, continuous integration/continuous delivery), orchestration, and deployment, to health, diagnostics, governance, and business metrics.
This report contains market size and forecasts of Machine Learning Operations (MLOps) in Global, including the following market information:
Global Machine Learning Operations (MLOps) Market Size 2024-2032, ($ millions)
The global Machine Learning Operations (MLOps) market is projected to reach US$ million by 2029.
We surveyed the Machine Learning Operations (MLOps) companies, and industry experts on this industry, involving the revenue, demand, product type, recent developments and plans, industry trends, drivers, challenges, obstacles, and potential risks.
Total Market by Segment:
Global Machine Learning Operations (MLOps) Market, by Type, 2024-2032 ($ millions)
Global Machine Learning Operations (MLOps) Market Segment Percentages, by Type
On-premise
Cloud
Hybrid
Global Machine Learning Operations (MLOps) Market, by Application, 2024-2032 ($ millions)
Global Machine Learning Operations (MLOps) Market Segment Percentages, by Application
BFSI
Healthcare
Retail
Manufacturing
Public Sector
Others
Global Machine Learning Operations (MLOps) Market, By Region and Country, 2024-2032 ($ Millions)
Global Machine Learning Operations (MLOps) Market Segment Percentages, by region and country
United States
Europe
Asia
China
Rest of World
Competitor Analysis
The report also provides analysis of leading market participants including:
Further, the report presents profiles of competitors in the market, key players include:
Microsoft
Amazon
Google
IBM
Dataiku
Lguazio
Databricks
DataRobot, Inc.
Cloudera
Modzy
Algorithmia
HPE
Valohai
Allegro AI
Comet
FloydHub
Paperpace
Cnvrg.io
TABLE OF CONTENTS
1 Introduction to Research & Analysis Reports
1.1 Machine Learning Operations (MLOps) Market Definition
1.2 Market Segments
1.2.1 Market by Type
1.2.2 Market by Application
1.3 Global Machine Learning Operations (MLOps) Market Overview
1.4 Features & Benefits of This Report
1.5 Methodology & Sources of Information
1.5.1 Research Methodology
1.5.2 Research Process
1.5.3 Base Year
1.5.4 Report Assumptions & Caveats
2 Global Machine Learning Operations (MLOps) Overall Market Size
2.1 Global Machine Learning Operations (MLOps) Market Size: 2023 VS 2032
2.2 Global Machine Learning Operations (MLOps) Market Size, Prospects & Forecasts: 2023-2032
2.3 Key Market Trends, Opportunity, Drivers and Restraints
2.3.1 Market Opportunities & Trends
2.3.2 Market Drivers
2.3.3 Market Restraints
3 Company Landscape
3.1 Key Machine Learning Operations (MLOps) Players in Global Market
3.2 Global Companies Machine Learning Operations (MLOps) Product & Technology
4 Machine Learning Operations (MLOps) Companies Profiles
4.1 Microsoft
4.1.1 Microsoft Company Summary
4.1.2 Microsoft Business Overview
4.1.3 Microsoft Machine Learning Operations (MLOps) Product Offerings & Technology
4.1.4 Microsoft Machine Learning Operations (MLOps) R&D, and Plans
4.2 Amazon
4.2.1 Amazon Company Summary
4.2.2 Amazon Business Overview
4.2.3 Amazon Machine Learning Operations (MLOps) Product Offerings & Technology
4.2.4 Amazon Machine Learning Operations (MLOps) R&D, and Plans
4.3 Google
4.3.1 Google Company Summary
4.3.2 Google Business Overview
4.3.3 Google Machine Learning Operations (MLOps) Product Offerings & Technology
4.3.4 Google Machine Learning Operations (MLOps) R&D, and Plans
4.4 IBM
4.4.1 IBM Company Summary
4.4.2 IBM Business Overview
4.4.3 IBM Machine Learning Operations (MLOps) Product Offerings & Technology
4.4.4 IBM Machine Learning Operations (MLOps) R&D, and Plans
4.5 Dataiku
4.5.1 Dataiku Company Summary
4.5.2 Dataiku Business Overview
4.5.3 Dataiku Machine Learning Operations (MLOps) Product Offerings & Technology
4.5.4 Dataiku Machine Learning Operations (MLOps) R&D, and Plans
4.6 Lguazio
4.6.1 Lguazio Company Summary
4.6.2 Lguazio Business Overview
4.6.3 Lguazio Machine Learning Operations (MLOps) Product Offerings & Technology
4.6.4 Lguazio Machine Learning Operations (MLOps) R&D, and Plans
4.7 Databricks
4.7.1 Databricks Company Summary
4.7.2 Databricks Business Overview
4.7.3 Databricks Machine Learning Operations (MLOps) Product Offerings & Technology
4.7.4 Databricks Machine Learning Operations (MLOps) R&D, and Plans
4.8 DataRobot, Inc.
4.8.1 DataRobot, Inc. Company Summary
4.8.2 DataRobot, Inc. Business Overview
4.8.3 DataRobot, Inc. Machine Learning Operations (MLOps) Product Offerings & Technology
4.8.4 DataRobot, Inc. Machine Learning Operations (MLOps) R&D, and Plans
4.9 Cloudera
4.9.1 Cloudera Company Summary
4.9.2 Cloudera Business Overview
4.9.3 Cloudera Machine Learning Operations (MLOps) Product Offerings & Technology
4.9.4 Cloudera Machine Learning Operations (MLOps) R&D, and Plans
4.10 Modzy
4.10.1 Modzy Company Summary
4.10.2 Modzy Business Overview
4.10.3 Modzy Machine Learning Operations (MLOps) Product Offerings & Technology
4.10.4 Modzy Machine Learning Operations (MLOps) R&D, and Plans
4.11 Algorithmia
4.11.1 Algorithmia Company Summary
4.11.2 Algorithmia Business Overview
4.11.3 Algorithmia Machine Learning Operations (MLOps) Product Offerings & Technology
4.11.4 Algorithmia Machine Learning Operations (MLOps) R&D, and Plans
4.12 HPE
4.12.1 HPE Company Summary
4.12.2 HPE Business Overview
4.12.3 HPE Machine Learning Operations (MLOps) Product Offerings & Technology
4.12.4 HPE Machine Learning Operations (MLOps) R&D, and Plans
4.13 Valohai
4.13.1 Valohai Company Summary
4.13.2 Valohai Business Overview
4.13.3 Valohai Machine Learning Operations (MLOps) Product Offerings & Technology
4.13.4 Valohai Machine Learning Operations (MLOps) R&D, and Plans
4.14 Allegro AI
4.14.1 Allegro AI Company Summary
4.14.2 Allegro AI Business Overview
4.14.3 Allegro AI Machine Learning Operations (MLOps) Product Offerings & Technology
4.14.4 Allegro AI Machine Learning Operations (MLOps) R&D, and Plans
4.15 Comet
4.15.1 Comet Company Summary
4.15.2 Comet Business Overview
4.15.3 Comet Machine Learning Operations (MLOps) Product Offerings & Technology
4.15.4 Comet Machine Learning Operations (MLOps) R&D, and Plans
4.16 FloydHub
4.16.1 FloydHub Company Summary
4.16.2 FloydHub Business Overview
4.16.3 FloydHub Machine Learning Operations (MLOps) Product Offerings & Technology
4.16.4 FloydHub Machine Learning Operations (MLOps) R&D, and Plans
4.17 Paperpace
4.17.1 Paperpace Company Summary
4.17.2 Paperpace Business Overview
4.17.3 Paperpace Machine Learning Operations (MLOps) Product Offerings & Technology
4.17.4 Paperpace Machine Learning Operations (MLOps) R&D, and Plans
4.18 Cnvrg.io
4.18.1 Cnvrg.io Company Summary
4.18.2 Cnvrg.io Business Overview
4.18.3 Cnvrg.io Machine Learning Operations (MLOps) Product Offerings & Technology
4.18.4 Cnvrg.io Machine Learning Operations (MLOps) R&D, and Plans
5 Sights by Region
5.1 By Region - Global Machine Learning Operations (MLOps) Market Size, 2024 & 2032
5.2 By Region - Global Machine Learning Operations (MLOps) Revenue, (2024-2032)
5.3 United States
5.3.1 Key Players of Machine Learning Operations (MLOps) in United States
5.3.2 United States Machine Learning Operations (MLOps) Development Current Situation and Forecast
5.4 Europe
5.4.1 Key Players of Machine Learning Operations (MLOps) in Europe
5.4.2 Europe Machine Learning Operations (MLOps) Development Current Situation and Forecast
5.5 China
5.5.1 Key Players of Machine Learning Operations (MLOps) in China
5.5.2 China Machine Learning Operations (MLOps) Development Current Situation and Forecast
5.6 Rest of World
6 Sights by Product
6.1 By Type - Global Machine Learning Operations (MLOps) Market Size Markets, 2024 & 2032
6.2 On-premise
6.3 Cloud
6.4 Hybrid
7 Sights by Application
7.1 By Application - Global Machine Learning Operations (MLOps) Market Size, 2024 & 2032
7.2 BFSI
7.3 Healthcare
7.4 Retail
7.5 Manufacturing
7.6 Public Sector
7.7 Others
8 Conclusion
9 Appendix
9.1 Note
9.2 Examples of Clients
9.3 Disclaimer
LIST OF TABLES & FIGURES
List of Tables
Table 1. Machine Learning Operations (MLOps) Market Opportunities & Trends in Global Market
Table 2. Machine Learning Operations (MLOps) Market Drivers in Global Market
Table 3. Machine Learning Operations (MLOps) Market Restraints in Global Market
Table 4. Key Players of Machine Learning Operations (MLOps) in Global Market
Table 5. Global Companies Machine Learning Operations (MLOps) Product & Technology
Table 6. Microsoft Company Summary
Table 7. Microsoft Machine Learning Operations (MLOps) Product Offerings
Table 8. Amazon Company Summary
Table 9. Amazon Machine Learning Operations (MLOps) Product Offerings
Table 10. Google Company Summary
Table 11. Google Machine Learning Operations (MLOps) Product Offerings
Table 12. IBM Company Summary
Table 13. IBM Machine Learning Operations (MLOps) Product Offerings
Table 14. Dataiku Company Summary
Table 15. Dataiku Machine Learning Operations (MLOps) Product Offerings
Table 16. Lguazio Company Summary
Table 17. Lguazio Machine Learning Operations (MLOps) Product Offerings
Table 18. Databricks Company Summary
Table 19. Databricks Machine Learning Operations (MLOps) Product Offerings
Table 20. DataRobot, Inc. Company Summary
Table 21. DataRobot, Inc. Machine Learning Operations (MLOps) Product Offerings
Table 22. Cloudera Company Summary
Table 23. Cloudera Machine Learning Operations (MLOps) Product Offerings
Table 24. Modzy Company Summary
Table 25. Modzy Machine Learning Operations (MLOps) Product Offerings
Table 26. Algorithmia Company Summary
Table 27. Algorithmia Machine Learning Operations (MLOps) Product Offerings
Table 28. HPE Company Summary
Table 29. HPE Machine Learning Operations (MLOps) Product Offerings
Table 30. Valohai Company Summary
Table 31. Valohai Machine Learning Operations (MLOps) Product Offerings
Table 32. Allegro AI Company Summary
Table 33. Allegro AI Machine Learning Operations (MLOps) Product Offerings
Table 34. Comet Company Summary
Table 35. Comet Machine Learning Operations (MLOps) Product Offerings
Table 36. FloydHub Company Summary
Table 37. FloydHub Machine Learning Operations (MLOps) Product Offerings
Table 38. Paperpace Company Summary
Table 39. Paperpace Machine Learning Operations (MLOps) Product Offerings
Table 40. Cnvrg.io Company Summary
Table 41. Cnvrg.io Machine Learning Operations (MLOps) Product Offerings
Table 42. By Region? Global Machine Learning Operations (MLOps) Revenue, (US$, Mn), 2024 & 2032
Table 43. By Region - Global Machine Learning Operations (MLOps) Revenue, (US$, Mn), 2024-2032
Table 44. By Type ? Global Machine Learning Operations (MLOps) Market Size, (US$, Mn), 2024 & 2032
Table 45. By Application? Global Machine Learning Operations (MLOps) Market Size, (US$, Mn), 2024 & 2032
List of Figures
Figure 1. Machine Learning Operations (MLOps) Segment by Type in 2032
Figure 2. Machine Learning Operations (MLOps) Segment by Application in 2032
Figure 3. Global Machine Learning Operations (MLOps) Market Overview: 2022
Figure 4. Key Caveats
Figure 5. Global Machine Learning Operations (MLOps) Market Size: 2023 VS 2032 (US$, Mn)
Figure 6. Global Machine Learning Operations (MLOps) Revenue, 2017-2028 (US$, Mn)
Figure 7. By Region - Global Machine Learning Operations (MLOps) Revenue Market Share, 2024-2032
Figure 8. By Type - Global Machine Learning Operations (MLOps) Revenue Market Share, 2024-2032
Figure 9. By Application - Global Machine Learning Operations (MLOps) Revenue Market Share, 2024-2032
