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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: September 2025
Volume 10 | Issue 9
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Impact Factor : 8.14
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| Paper Title: | Agentic AI Executors in Java Microservices for Autonomous Task Decomposition and Orchestration |
| Authors Name: | Sohith Sri Ammineedu Yalamati |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_206339
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| Published Paper Id: | IJRTI2509109 |
| Published In: | Volume 10 Issue 9, September-2025 |
| DOI: | https://doi.org/10.56975/ijrti.v10i9.206339 |
| Abstract: | With the growing complexity of enterprise systems, software engineering as well as artificial intelligence circles are converging towards newer paradigms of automating not just the creation of codes, but also the handling and coordination of tasks. The recent development that is worth noting is the combination of Agentic AI and Java-based microservice architecture to create autonomous task decomposition and orchestration. Older microservices have always offered a high degree of modularity, scalability and independence among services, but they are extremely manual in nature and they have no cognitive capabilities. Conversely, Agentic AI proposes self-directed AI systems, which can learn and comprehend high-level objectives and formulate plans to achieve them, attention to tools, and can change strategies according to real-time feedback. This study discusses an innovative model that integrates Agentic AI Executors into Java microservices to make the statical service boundaries dynamically and intelligently active agents. The architecture is based on architectural concepts of MAPE-K (Monitor, Analyze, Plan, Execute with Knowledge), includes the autonomous agent developed on the basis of LLMs, and provides easy interoperability with developer tools, CI/CD pipelines, and external APIs. One of the contributions of this paper is the creation of a modular framework that enables Agentic Executors to manage autonomously task decomposition, inter-agent coordination and fault-tolerant coordination in a microservice environment. This study assesses the performance of the proposed system based on execution metrics, recovery time standards, and task throughput in comparison with conventional orchestrated services through a case study examining tenant refactoring of legacy systems. The results show measurable benefits in terms of scalability, adaptability and reducing developer effort. The combination of Agentic AI and Java microservices creates a new trajectory for intelligent service ecosystems characterized by autonomous reasoning, distributed control and self-healing behavior. The paper concludes with implications for DevOps practices; challenges for agent safety and explainability; and future directions for hybrid cognitive microservices. |
| Keywords: | Agentic AI, Microservices, Java, Autonomous Orchestration, Task Decomposition, MAPE-K Architecture |
| Cite Article: | "Agentic AI Executors in Java Microservices for Autonomous Task Decomposition and Orchestration", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 9, page no.b52-b65, September-2025, Available :http://www.ijrti.org/papers/IJRTI2509109.pdf |
| Downloads: | 000369 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
| Publication Details: |
Published Paper ID: IJRTI2509109
Registration ID:206339
Published In: Volume 10 Issue 9, September-2025
DOI (Digital Object Identifier): https://doi.org/10.56975/ijrti.v10i9.206339
Page No: b52-b65 Country: -, -, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2509109 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2509109 |
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