The Autonomous Stack: How Architects Are Enabling Self-Healing, Self-Optimizing Applications
This article explores the emerging architectural paradigm of the "Autonomous Stack," where software systems are designed to be self-healing, self-optimizing, and resilient by default. As complexity increases across distributed cloud, edge, and AI-enabled environments, architects are levera...
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Published in | European Journal of Computer Science and Information Technology Vol. 13; no. 47; pp. 11 - 20 |
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Main Author | |
Format | Journal Article |
Language | English |
Published |
26.06.2025
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Online Access | Get full text |
ISSN | 2054-0957 2054-0965 |
DOI | 10.37745/ejcsit.2013/vol13n471120 |
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Abstract | This article explores the emerging architectural paradigm of the "Autonomous Stack," where software systems are designed to be self-healing, self-optimizing, and resilient by default. As complexity increases across distributed cloud, edge, and AI-enabled environments, architects are leveraging observability, AI/ML, policy-driven orchestration, and event-driven patterns to enable systems that adapt and recover without manual intervention. The article covers key components such as service mesh, health probes, automated rollback mechanisms, and intelligent scaling. It also examines how predictive analytics, feedback loops, and agent-based automation are transforming runtime behavior into a dynamic, learning ecosystem—pushing software architecture beyond static reliability toward autonomous operational excellence. |
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AbstractList | This article explores the emerging architectural paradigm of the "Autonomous Stack," where software systems are designed to be self-healing, self-optimizing, and resilient by default. As complexity increases across distributed cloud, edge, and AI-enabled environments, architects are leveraging observability, AI/ML, policy-driven orchestration, and event-driven patterns to enable systems that adapt and recover without manual intervention. The article covers key components such as service mesh, health probes, automated rollback mechanisms, and intelligent scaling. It also examines how predictive analytics, feedback loops, and agent-based automation are transforming runtime behavior into a dynamic, learning ecosystem—pushing software architecture beyond static reliability toward autonomous operational excellence. |
Author | Vedanbhatla, Naga V K Abhinav |
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Cites_doi | 10.1007/978-3-030-05318-5_1 10.1109/MS.2017.72 10.1109/MC.2003.1160055 10.1109/CLOUD.2019.00018 10.1109/INFOCOM.2006.196 10.1145/2890784 10.1109/MS.2015.11 10.1109/MC.2012.37 10.1016/j.jss.2018.05.049 10.1145/3177854 10.1186/2192-113X-2-22 10.1145/3386252 10.1007/s11036-013-0489-0 |
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