Scaling Kubernetes Clusters with AI-Driven Observability for Improved Service Reliability
DOI:
https://doi.org/10.60087/Japmi.Vol.03.Issue.01.Id.003Keywords:
Kubernetes Scaling, AI-Driven Observability, Service Reliability, Cluster Management, Kubernetes Optimization, AI-Powered Monitoring, Scalability in Kubernetes, Observability Tools, Automated Cluster Scaling, Service Uptime, Fault ToleranceAbstract
This study introduces an AI-powered observability framework integrated with Kubernetes clusters using Prometheus and Grafana. It demonstrates how predictive analytics reduces mean time to resolution (MTTR) and optimizes resource allocation. The research outlines a case study with measurable gains in service reliability and cost-effectiveness.
Downloads
Published
2024-12-25
Issue
Section
Articles
License
Copyright (c) 2024 Journal of AI-Powered Medical Innovations and Authors
This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite
Scaling Kubernetes Clusters with AI-Driven Observability for Improved Service Reliability. (2024). Journal of AI-Powered Medical Innovations (International Online ISSN 3078-1930), 3(1), 39-52. https://doi.org/10.60087/Japmi.Vol.03.Issue.01.Id.003
