Automation of Monitoring and Optimization of Docker Containers Using Artificial Intelligence

The increasing adoption of Docker containers in modern software development requires effective monitoring and optimization to ensure high performance and efficient resource utilization. This paper provides an overview of the various tools and technologies that leverage artificial intelligence (AI) to automate the monitoring and optimization of Docker containers. The authors explore the capabilities of AI-driven tools such as machine learning-based anomaly detection, predictive analytics, and automated resource management. By examining these tools, the authors highlight their benefits in enhancing container performance, scalability, and availability. Through comparative analysis, the strengths and limitations of each tool and their impact on container management are discussed. The findings underscore the potential of AI to revolutionize container monitoring and optimization, leading to more efficient and robust IT infrastructure.

Authors

Institutions

Publication Details

Published
2025-03-19
DOI
https://doi.org/10.1109/infoteh64129.2025.10959216
Citations
3
Primary Topic
Advanced Data Processing Techniques
Type
article
Field-Weighted Citation Impact
3.64
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Automation of Monitoring and Optimization of Docker Containers Using Artificial Intelligence

Vanja Luković, Sava Stanišić, Branislav Belotić
3 citations
Advanced Data Processing Techniques
3.64
article

Automation of Monitoring and Optimization of Docker Containers Using Artificial Intelligence

Vanja Luković, Sava Stanišić, Branislav Belotić
article en
3 citations

Abstract

The increasing adoption of Docker containers in modern software development requires effective monitoring and optimization to ensure high performance and efficient resource utilization. This paper provides an overview of the various tools and technologies that leverage artificial intelligence (AI) to automate the monitoring and optimization of Docker containers. The authors explore the capabilities of AI-driven tools such as machine learning-based anomaly detection, predictive analytics, and automated resource management. By examining these tools, the authors highlight their benefits in enhancing container performance, scalability, and availability. Through comparative analysis, the strengths and limitations of each tool and their impact on container management are discussed. The findings underscore the potential of AI to revolutionize container monitoring and optimization, leading to more efficient and robust IT infrastructure.

Institute of Technical Sciences of SASA (RS)
Openalex Percentile: Top 8%
Advanced Data Processing Techniques
3.64
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.