mlsanityData to 7 Oct 2026

MLOps -- Definitions, Tools and Challenges

arXiv 2201.00162 ↗First posted 1 Jan 2022cs.LG cs.SEcited by 25

Not on the map. Why?

Abstract (arXiv)

This paper is an overview of the Machine Learning Operations (MLOps) area. Our aim is to define the operation and the components of such systems by highlighting the current problems and trends. In this context, we present the different tools and their usefulness in order to provide the corresponding guidelines. Moreover, the connection between MLOps and AutoML (Automated Machine Learning) is identified and how this combination could work is proposed.

Key facts. Cited by 25 papers in the map (data through 7 Oct 2026). Builds on 10 of its 54 references that are in the map. First posted on arXiv 1 Jan 2022.

Builds on

10 of 54 references.

References · 10

  1. 2020Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learningcited by 174
  2. 2019An Open Source AutoML Benchmarkcited by 85
  3. 2020Auto-PyTorch Tabular: Multi-Fidelity MetaLearning for Efficient and Robust AutoDLcited by 67
  4. 2020AutoML to Date and Beyond: Challenges and Opportunitiescited by 63
  5. 2021Who Needs MLOps: What Data Scientists Seek to Accomplish and How Can MLOps Help?cited by 37
  6. 2021A Data Quality-Driven View of MLOpscited by 31
  7. 2020Monitoring and explainability of models in productioncited by 23
  8. 2021MLOps Challenges in Multi-Organization Setup: Experiences from Two Real-World Casescited by 10
  9. 2021SensiX++: Bringing MLOPs and Multi-tenant Model Serving to Sensory Edge Devicescited by 7
  10. 2020The Collective Knowledge project: making ML models more portable and reproducible with open APIs, reusable best practices and MLOpscited by 4

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 12; 2024: 3; 2025: 7; 2026: 1.

25 papers.

Sort:

By area:

  1. 2023MLOps: A Reviewcited by 16
  2. 2022DC-Check: A Data-Centric AI checklist to guide the development of reliable machine learning systemscited by 14
  3. 2023Machine Learning with Requirements: a Manifestocited by 8
  4. 2023MLOps for Scarce Image Data: A Use Case in Microscopic Image Analysiscited by 4
  5. 2023OceanBench: The Sea Surface Height Editioncited by 4
  6. 2025Architecting Digital Twins for Intelligent Transportation Systemscited by 3
  7. 2025Securing RAG: A Risk Assessment and Mitigation Frameworkcited by 3
  8. 2023MLHOps: Machine Learning for Healthcare Operationscited by 2
  9. 2023MLOps: A Step Forward to Enterprise Machine Learningcited by 2
  10. 2023Towards an MLOps Architecture for XAI in Industrial Applicationscited by 2
  11. 2023Mithridates: Auditing and Boosting Backdoor Resistance of Machine Learning Pipelinescited by 1
  12. 2023Extending Variability-Aware Model Selection with Bias Detection in Machine Learning Projectscited by 1
13 more
  1. 2024Backward Compatibility in Attributive Explanation and Enhanced Model Training Methodcited by 1
  2. 2024Machine Learning Operations: A Mapping Studycited by 1
  3. 2025End-to-End Data Quality-Driven Framework for Machine Learning in Production Environmentcited by 1
  4. 2022A Data Source Dependency Analysis Framework for Large Scale Data Science Projectscited by 0
  5. 2023Good Tools are Half the Work: Tool Usage in Deep Learning Projectscited by 0
  6. 2023Seeing the random forest through the decision trees. Supporting learning health systems from histopathology with machine learning models: Challenges and opportunitiescited by 0
  7. 2023Performance of externally validated machine learning models based on histopathology images for the diagnosis, classification, prognosis, or treatment outcome prediction in female breast cancer: A systematic reviewcited by 0
  8. 2024Automating Code Adaptation for MLOps -- A Benchmarking Study on LLMscited by 0
  9. 2025HarmonE: A Self-Adaptive Approach to Architecting Sustainable MLOpscited by 0
  10. 2025Getting In Contract with Large Language Models -- An Agency Theory Perspective On Large Language Model Alignmentcited by 0
  11. 2025Embedding the MLOps Lifecycle into OT Reference Modelscited by 0
  12. 2025Model Gateway: Management Platform for Model-Driven Drug Discoverycited by 0
  13. 2026Trustworthy Data- and ML-Ops for Intelligent Transportation Systems and Logisticscited by 0