AI-Driven Observability and Reliability Framework for Multi-Cloud Financial Platforms
Authors/Creators
Contributors
Researcher:
Description
Modern financial platforms operate in highly distributed, multi-cloud environments where system reliability, performance, and cost efficiency are critical. Traditional Site Reliability Engineering (SRE) practices are predominantly reactive and lack predictive intelligence. This paper introduces the Marella Reliability Model (MRM), an AI-driven observability and incident prediction framework designed to improve system uptime, reduce Mean Time to Resolution (MTTR), and optimize operational costs. The framework integrates machine learning, real-time telemetry, and FinOps principles to create a proactive reliability ecosystem. Empirical evaluation demonstrates measurable improvements in system resilience and cost efficiency, making the model applicable to fintech and large-scale cloud-native enterprises.
Files
README (1).md
Additional details
Identifiers
- Crossref Funder ID
- https://dx.doi.org/10.2139/ssrn.6557159
- Crossref Funder ID
- 10.13140/RG.2.2.20438.41284
Related works
- Is published in
- Preprint: https://dx.doi.org/10.2139/ssrn.6557159 (Crossref Funder ID)
- Preprint: 10.13140/RG.2.2.20438.41284 (Crossref Funder ID)
Dates
- Submitted
-
2026-04-10AI-Driven Observability and Reliability Framework for Multi-Cloud Financial Platforms
Software
- Repository URL
- https://github.com/Infinity-Info-systems/ai-driven-observability-framework
- Programming language
- TypeScript
- Development Status
- Active
References
- Marella, Ramesh, AI-Driven Observability and Reliability Framework for Multi-Cloud Financial Platforms (April 10, 2026). Available at SSRN: https://ssrn.com/abstract=6557159 or http://dx.doi.org/10.2139/ssrn.6557159