Moving From Monolithic To Microservices Architecture for Multi-Agent Systems
- URL: http://arxiv.org/abs/2505.07838v1
- Date: Mon, 05 May 2025 09:10:46 GMT
- Title: Moving From Monolithic To Microservices Architecture for Multi-Agent Systems
- Authors: Muskaan Goyal, Pranav Bhasin,
- Abstract summary: The transition from monolithic to architecture revolutionized software development by improving scalability and maintainability.<n>This review article explores the evolution from monolithic architecture to architecture in the specific context of multi-agent systems.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The transition from monolithic to microservices architecture revolutionized software development by improving scalability and maintainability. This paradigm shift is now becoming relevant for complex multi-agent systems (MAS). This review article explores the evolution from monolithic architecture to microservices architecture in the specific context of MAS. It will highlight the limitations of traditional monolithic MAS and the benefits of adopting a microservices-based approach. The article further examines the core architectural principles and communication protocols, including Agent Communication Languages (ACLs), the Model Context Protocol (MCP), and the Application-to-Application (A2A) protocol. The article identifies emerging architectural patterns, design challenges, and considerations through a comparative lens of the paradigm shift.
Related papers
- MOD-X: A Modular Open Decentralized eXchange Framework proposal for Heterogeneous Interoperable Artificial Intelligence Agents [0.7864304771129751]
This paper introduces MOD-X, a novel architectural framework proposal for agent interoperability.<n>Unlike current approaches, MOD-X proposes a layered architecture with a Universal Message Bus.<n>Key innovations include a publish-subscribe communication model, semantic capability discovery, and dynamic workflow orchestration.
arXiv Detail & Related papers (2025-07-06T12:46:57Z) - Graft: Integrating the Domain Knowledge via Efficient Parameter Synergy for MLLMs [56.76586846269894]
Multimodal Large Language Models (MLLMs) have achieved success across various domains.<n>Despite its importance, the study of knowledge sharing among domain-specific MLLMs remains largely underexplored.<n>We propose a unified parameter integration framework that enables modular composition of expert capabilities.
arXiv Detail & Related papers (2025-06-30T15:07:41Z) - Centrality Change Proneness: an Early Indicator of Microservice Architectural Degradation [48.55946052680251]
The study of temporal networks has emerged as a way to describe and analyze evolving networks.<n>Previous research has explored how software metrics such as size, complexity, and quality are related to microservice centrality.<n>This study investigates whether temporal centrality metrics can provide insight into the early detection of architectural degradation.
arXiv Detail & Related papers (2025-06-09T12:22:12Z) - Survey of LLM Agent Communication with MCP: A Software Design Pattern Centric Review [0.9208007322096533]
The study revisits well-established patterns, including Mediator, Observer, Publish-Subscribe, and Broker.<n>The article concludes by outlining open challenges, potential security risks, and promising directions for advancing robust, interoperable, and scalable multi-agent ecosystems.
arXiv Detail & Related papers (2025-05-26T09:11:17Z) - Large Language Model Agent: A Survey on Methodology, Applications and Challenges [88.3032929492409]
Large Language Model (LLM) agents, with goal-driven behaviors and dynamic adaptation capabilities, potentially represent a critical pathway toward artificial general intelligence.<n>This survey systematically deconstructs LLM agent systems through a methodology-centered taxonomy.<n>Our work provides a unified architectural perspective, examining how agents are constructed, how they collaborate, and how they evolve over time.
arXiv Detail & Related papers (2025-03-27T12:50:17Z) - A Survey of Model Architectures in Information Retrieval [64.75808744228067]
We focus on two key aspects: backbone models for feature extraction and end-to-end system architectures for relevance estimation.<n>We trace the development from traditional term-based methods to modern neural approaches, particularly highlighting the impact of transformer-based models and subsequent large language models (LLMs)<n>We conclude by discussing emerging challenges and future directions, including architectural optimizations for performance and scalability, handling of multimodal, multilingual data, and adaptation to novel application domains beyond traditional search paradigms.
arXiv Detail & Related papers (2025-02-20T18:42:58Z) - Microkernel-Based Web Architecture: Design & Implementation Considerations [0.0]
I propose a middle-ground alternative between monolithic and microservice web architectures.<n>I revised the design of a microkernel-based web architecture, considering these challenges as well as recent architectural advancements.
arXiv Detail & Related papers (2025-02-12T21:29:18Z) - Contrastive Learning-Enhanced Large Language Models for Monolith-to-Microservice Decomposition [0.4297070083645049]
Monolithic applications become increasingly difficult to maintain and improve, leading to scaling and organizational issues.<n>Despite its advantages, migrating from a monolithic to a monolithic architecture is often costly and complex.<n>This research addresses this issue by introducing MonoEmbed, a Language Model based approach for automating the decomposition process.
arXiv Detail & Related papers (2025-02-07T01:37:20Z) - Towards More Unified In-context Visual Understanding [74.55332581979292]
We present a new ICL framework for visual understanding with multi-modal output enabled.
First, we quantize and embed both text and visual prompt into a unified representational space.
Then a decoder-only sparse transformer architecture is employed to perform generative modeling on them.
arXiv Detail & Related papers (2023-12-05T06:02:21Z) - Systematic Mapping of Monolithic Applications to Microservices
Architecture [2.608935407927351]
It discusses the advantages of and the challenges that organizations face when transitioning from a monolithic system.
It presents a case study of a financial application and proposed techniques for identifying on monolithic systems using domain-driven development concepts.
arXiv Detail & Related papers (2023-09-07T15:47:11Z) - Enhancing Architecture Frameworks by Including Modern Stakeholders and their Views/Viewpoints [48.87872564630711]
The stakeholders with data science and Machine Learning related concerns, such as data scientists and data engineers, are yet to be included in existing architecture frameworks.<n>We surveyed 61 subject matter experts from over 25 organizations in 10 countries.
arXiv Detail & Related papers (2023-08-09T21:54:34Z) - Enterprise Architecture Model Transformation Engine [0.0]
This paper presents a transformation engine to convert enterprise architecture models between several languages.
The transformation process is defined by various pattern matching techniques using a rule-based description language.
It uses set theory and first-order logic for an intuitive description as a basis.
arXiv Detail & Related papers (2021-08-15T11:10:42Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.