AI-driven observability: Transforming monitoring and alerting in CI/CD platforms
AI-driven observability is transforming how organizations monitor and maintain CI/CD platforms, enabling a shift from reactive troubleshooting to proactive system management. By integrating machine learning with traditional monitoring tools, companies like Walmart are achieving significant improvements in alert quality, detection speed, and incident prevention. This article explores the limitations of conventional monitoring approaches and the potential of AI to address these challenges through pattern recognition, adaptive baselines, and predictive capabilities. It examines Walmart's implementation journey, the technical architecture required for effective AI-driven observability, and the importance of human-AI collaboration in maximizing operational effectiveness. The evolution toward business-aligned observability and observability-driven development represents a fundamental reimagining of how reliability engineering operates in cloud-native environments.
Institutions
- Walmart (United States) (US)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-04-30
- DOI
- https://doi.org/10.5281/zenodo.17205368
- Primary Topic
- Geochemistry and Elemental Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00