GenAI-driven cloud management for AWS and Kubernetes environments

Generative Artificial Intelligence (GenAI) is transforming cloud platform engineering, bringing unprecedented intelligence and automation to infrastructure management for AWS and Kubernetes environments. This article examines how GenAI technologies like Amazon Q, Q-Developer, KubeGPT, and k8sGPT are revolutionizing the entire cloud infrastructure lifecycle—from design and provisioning to operations and optimization. These tools leverage natural language processing and machine learning to simplify complex tasks, translate technical concepts into actionable insights, and enable proactive management strategies. The integration of reinforcement learning techniques further enhances resource optimization by continuously adapting to changing workload patterns and business requirements. While implementing GenAI in cloud operations presents challenges related to data quality, continuous learning, human-AI collaboration, and governance, organizations can navigate these complexities by adopting hybrid models, focusing on high-value use cases, investing in data infrastructure, and developing specialized expertise. The convergence of GenAI with cloud management heralds a new era of autonomous, self-optimizing infrastructures that anticipate needs rather than merely responding to them.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-30
DOI
https://doi.org/10.5281/zenodo.17222826
Primary Topic
Diverse Scientific and Economic Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

GenAI-driven cloud management for AWS and Kubernetes environments

Zenodo (CERN European Organization for Nuclear Research)
Diverse Scientific and Economic Studies
article

GenAI-driven cloud management for AWS and Kubernetes environments

article en

Abstract

Generative Artificial Intelligence (GenAI) is transforming cloud platform engineering, bringing unprecedented intelligence and automation to infrastructure management for AWS and Kubernetes environments. This article examines how GenAI technologies like Amazon Q, Q-Developer, KubeGPT, and k8sGPT are revolutionizing the entire cloud infrastructure lifecycle—from design and provisioning to operations and optimization. These tools leverage natural language processing and machine learning to simplify complex tasks, translate technical concepts into actionable insights, and enable proactive management strategies. The integration of reinforcement learning techniques further enhances resource optimization by continuously adapting to changing workload patterns and business requirements. While implementing GenAI in cloud operations presents challenges related to data quality, continuous learning, human-AI collaboration, and governance, organizations can navigate these complexities by adopting hybrid models, focusing on high-value use cases, investing in data infrastructure, and developing specialized expertise. The convergence of GenAI with cloud management heralds a new era of autonomous, self-optimizing infrastructures that anticipate needs rather than merely responding to them.

Zenodo (CERN European Organization for Nuclear Research)
The Ohio State University (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 34%
Diverse Scientific and Economic Studies
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