IDEAS home Printed from https://ideas.repec.org/a/abu/abuabu/v3y2024i1p39-52id19.html
   My bibliography  Save this article

Scaling Kubernetes Clusters with AI-Driven Observability for Improved Service Reliability

Author

Listed:
  • Sandeep Pochu
  • Sai Rama Krishna Nersu
  • Srikanth Reddy Kathram

Abstract

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.

Suggested Citation

  • Sandeep Pochu & Sai Rama Krishna Nersu & Srikanth Reddy Kathram, 2024. "Scaling Kubernetes Clusters with AI-Driven Observability for Improved Service Reliability," Journal of AI-Powered Medical Innovations (International online ISSN 3078-1930), Open Knowledge, vol. 3(1), pages 39-52.
  • Handle: RePEc:abu:abuabu:v:3:y:2024:i:1:p:39-52:id:19
    as

    Download full text from publisher

    File URL: https://japmi.org/index.php/japmi/article/view/19/17
    Download Restriction: no
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:abu:abuabu:v:3:y:2024:i:1:p:39-52:id:19. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: By Openjournaltheme (email available below). General contact details of provider: https://japmi.org/index.php/japmi/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.