Machine Learning Operations: A Survey on MLOps Tool Support
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Abstract (arXiv)
Machine Learning (ML) has become a fast-growing, trending approach in solution development in practice. Deep Learning (DL) which is a subset of ML, learns using deep neural networks to simulate the human brain. It trains machines to learn techniques and processes individually using computer algorithms, which is also considered to be a role of Artificial Intelligence (AI). In this paper, we study current technical issues related to software development and delivery in organizations that work on ML projects. Therefore, the importance of the Machine Learning Operations (MLOps) concept, which can deliver appropriate solutions for such concerns, is discussed. We investigate commercially available MLOps tool support in software development. The comparison between MLOps tools analyzes the performance of each system and its use cases. Moreover, we examine the features and usability of MLOps tools to identify the most appropriate tool support for given scenarios. Finally, we recognize that there is a shortage in the availability of a fully functional MLOps platform on which processes can be automated by reducing human intervention.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 Feb 2022.
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Citing papers per year: 2022: 2; 2023: 2; 2024: 3.
7 papers.
- 2022Machine Learning Operations (MLOps): Overview, Definition, and Architecturecited by 126
- 2023MLOps: A Reviewcited by 16
- 2023Continual Learning for Predictive Maintenance: Overview and Challengescited by 10
- 2022Continual-Learning-as-a-Service (CLaaS): On-Demand Efficient Adaptation of Predictive Modelscited by 5
- 2024Towards Trustworthy Machine Learning in Production: An Overview of the Robustness in MLOps Approachcited by 3
- 2024Towards MLOps: A DevOps Tools Recommender System for Machine Learning Systemcited by 2
- 2024KModels: Unlocking AI for Business Applicationscited by 0
- 2024Towards Trustworthy Machine Learning in Production: An Overview of the Robustness in MLOps Approach28 Oct 2024
- 2024KModels: Unlocking AI for Business Applications8 Sep 2024
- 2024Towards MLOps: A DevOps Tools Recommender System for Machine Learning System20 Feb 2024
- 2023MLOps: A Review19 Aug 2023
- 2023Continual Learning for Predictive Maintenance: Overview and Challenges29 Jan 2023
- 2022Continual-Learning-as-a-Service (CLaaS): On-Demand Efficient Adaptation of Predictive Models14 Jun 2022
- 2022Machine Learning Operations (MLOps): Overview, Definition, and Architecture4 May 2022