Event-driven Architecture Research Articles

Cloud-Native Microservices for Real-Time Data Systems: A Technical Deep Dive

Cloud-native microservices have emerged as a transformative solution for organizations facing the challenges of real-time data processing and analysis in today's digital landscape. This comprehensive article explores the fundamental components of cloud-native architectures, from their foundational principles to implementation best practices. The article examines how containerization, orchestration, and event-driven architectures enable unprecedented scalability and efficiency in handling modern data processing requirements. Through a detailed examination of microservices as building blocks, the research demonstrates how these architectural patterns significantly improve system reliability, performance, and maintainability. The article encompasses advanced monitoring and observability practices, highlighting their crucial role in maintaining robust cloud-native systems. By investigating real-world implementations across various industries, this study provides valuable insights into the practical benefits and challenges of adopting cloud-native approaches.

Event-Driven Architecture: Harnessing Kafka and Spring Boot for Scalable, Real-Time Applications

This comprehensive article explores the transformative impact of Event-Driven Architecture (EDA) in modern financial services, focusing on its implementation using Apache Kafka and Spring Boot. The article examines how financial institutions have revolutionized their transaction processing capabilities through EDA adoption, achieving significant improvements in system performance, reliability, and customer experience. Through a detailed examination of real-world implementations, the analysis demonstrates how EDA has enabled banks to handle unprecedented transaction volumes while substantially reducing system latency and improving resource utilization. The integration of Kafka and Spring Boot has proven particularly effective, with major financial institutions leveraging these technologies to achieve superior performance metrics and system availability. The article further explores critical patterns, including event sourcing, CQRS, and saga patterns, alongside cloud-based best practices for monitoring, performance optimization, and security implementations. By examining various implementation strategies and their outcomes, this article provides a comprehensive framework for building scalable, resilient financial systems that meet the demanding requirements of modern banking operations while ensuring regulatory compliance and maintaining high security and reliability standards.

Configuring Real-Time Event Processing of Api Gateway with Aws and Websocket Api’s

This monitor explores how to leverage AWS API Gateway's WebSocket APIs for building real-time event processing systems. Unlike traditional HTTP-based APIs, WebSocket APIs allow bidirectional communication, enabling instant data exchange between clients and servers. This setup is ideal for applications that require low-latency interactions, such as chat applications, IoT monitoring, gaming, and live notifications. By configuring API Gateway's WebSocket integration with AWS services like Lambda and DynamoDB, developers can create responsive and scalable event-driven architectures. The document also covers strategies for managing connection states, handling errors, and ensuring secure access, offering a complete framework for real-time data processing in AWS environments. Configuring real-time event processing with AWS API Gateway and WebSocket APIs enables dynamic, bidirectional communication between clients and servers, facilitating instant data transmission. “Unlike traditional REST APIs, WebSocket APIs allow for continuous, persistent connections, making them ideal for applications that require real-time updates, such as chat applications, gaming platforms, financial tickers, and IoT systems. AWS API Gateway provides a fully managed WebSocket solution that simplifies setup, scaling, and management of real-time APIs. By integrating WebSocket APIs with AWS Lambda, DynamoDB, or Amazon Kinesis, developers can process events in real time, store data, or trigger workflows based on incoming messages. This approach not only reduces latency but also enhances application responsiveness and scalability, leveraging AWS’s serverless architecture to handle high volumes of real-time events efficiently.

Event-Driven Data Pipelines : A Cloud-Based Approach to Real-Time Data Processing

This article comprehensively analyzes event-driven data pipelines in cloud computing environments, examining their architecture, implementation considerations, and real-world applications. The article explores the fundamental components of event-driven systems, from event sources and message brokers to processing layers, while evaluating their performance characteristics and reliability mechanisms. Through detailed analysis of system architectures, we investigate the integration of various cloud services and their role in enabling scalable, real-time data processing. The article demonstrates how modern event-driven architectures achieve sub-millisecond processing times and handle millions of events per second while maintaining system resilience. Our findings reveal significant improvements in operational efficiency across various industries, including financial services, marketing automation, and IoT monitoring solutions. The article also addresses critical implementation aspects, including security frameworks, integration protocols, and best practices for system optimization. These insights provide valuable guidance for organizations leveraging event-driven architectures in their digital transformation initiatives. The article concludes that event-driven data pipelines represent a crucial advancement in data processing technology, offering unprecedented capabilities in handling real-time data streams while maintaining scalability, reliability, and cost-effectiveness.

Event-Driven Data Integration to Automate Elevator Service Contract Booking Between MS Dynamics and Oracle JDE with Operational MDM for Master Data Integration

With increasing digitization in industries, data driven integration between enterprise systems is critical for automating business processes and improving efficiency. This paper presents a novel approach to automate elevator service contract bookings by integrating Microsoft Dynamics (MS Dynamics) with Oracle JD Edwards EnterpriseOne (JDE) through event-driven data integration. A key aspect of this integration is the utilization of an Operational Master Data Management (MDM) system to ensure consistency of master data across both platforms. This event-driven architecture significantly reduces manual intervention and improves data accuracy by ensuring near real-time synchronization of data across systems. Paper will also explore a case study where this event driven automation was implemented for a large elevator and escalator manufacturing and services company to reduce overall contract booking turnaround time from 45 days to 5 days and save more than $1M in labor cost over 3 years. Keywords Event-driven integration, master data management (MDM), enterprise resource planning (ERP), MS Dynamics, Oracle JDE, automation, service contract booking, data synchronization.

Software architecture for implementing a personal budget manager with artificial intelligence

The rapid adoption of artificial intelligence (AI) in consumer markets has led to the need for extensive research into its impact on consumer behavior, particularly in how it exploits cognitive biases. This raises ethical questions and highlights the need to balance such influences with AI systems that help consumers, not manipulate them. The development and implementation of an intelligent financial management system, which not only automates financial processes, but also integrates AI-driven tools to support better financial decision-making, contributes to solving these problems. The work contains a description of the development of the architecture of an intelligent financial management system, which is aimed at solving problems related to financial illiteracy, the complexity of financial markets, and the impact of cognitive biases on financial decision-making. The system provides for the use of modern technologies of artificial intelligence and machine learning to automate financial processes and provide users with personalized recommendations. The development of a system based on microservice architecture requires the use of certain architectural patterns that ensure efficiency, reliability and scalability, so the work was based on a critical analysis of modern architectural paradigms, such as microservice architecture and Event-Driven Architecture. The implementation of AI supports ethical guidelines that prioritize transparency, fairness and consumer autonomy, i.e. ensure that the AI ​​system is free from bias, actions can be easily interpreted by users. The methodology of this research is based on an interdisciplinary approach that combines the analysis of architectural solutions, methods of machine learning and artificial intelligence with methods of ensuring the reliability and scalability of software systems.

Real-Time Document Collaboration—System Architecture and Design

This article explores the world of dependable systems, specifically focusing on system design, software solutions, and architectural decisions that facilitate collaborative work on shared text documents across multiple users in near real time. It aims to dive into the intricacies of designing robust and effective document collaboration software focusing on understanding the requirements of such a system, the working principle of collaborative text editing, software architecture, technology stack selection, and tooling that can sustain such a system. To examine the pros and cons of the proposed system, the paper will detail how collaborative text editing software can benefit from such an architecture regarding availability, elasticity, and scaling. The intricate nature of this system renders this paper a valuable resource for prospective investigations within the domain of dependable systems and distributed systems. This research first examines the requirements of a real-time collaboration system and the necessary core features. Then, it analyzes the design, the application structure, and the system organization while also considering key architectural requirements as the necessity of scaling, the usage of microservices, cross-service communications, and client–server communication. For the technology stack of the implementation, this research considers the alternatives at each layer, from client to server. Once these decisions are made, it follows system development while examining possible improvements for the issues previously encountered. To validate the architecture, a testing strategy is developed, to examine the key capabilities of the system, such as resource consumption and throughput. The conclusions review the combination of modern and conventional application development principles needed to address the challenges of conflict-free document replication, decoupled and stateless event-driven architecture, idempotency, and data consistency. This paper not only showcases the design and implementation process but also sets a foundation for future research and innovation in dependable systems, collaborative technologies, sustainable solutions, and distributed system architecture.

Developing Scalable APIs for Data Synchronization in Salesforce Environments

In the modern business landscape, Salesforce has become an essential platform for managing customer relationships, driving sales, and fostering business growth. However, as organizations grow and their data volumes increase, the need for efficient and scalable data synchronization across various systems becomes paramount. Developing scalable APIs for data synchronization in Salesforce environments presents a significant challenge due to the complexity of integrating multiple data sources, ensuring real-time updates, and maintaining data integrity across diverse systems. This paper explores the design and implementation of scalable APIs specifically tailored for data synchronization within Salesforce environments. It delves into the architectural considerations necessary for creating robust, high-performance APIs capable of handling large volumes of data while ensuring consistency and reliability. The discussion begins with an overview of Salesforce’s ecosystem, highlighting the importance of data synchronization in maintaining seamless operations across various departments and systems. A critical component of this study is the examination of different API design patterns that support scalability, such as RESTful services, GraphQL, and event-driven architectures. Each approach is analyzed for its suitability in handling the unique challenges of Salesforce data synchronization, such as managing API limits, optimizing data transfer, and ensuring that data synchronization processes do not disrupt ongoing business activities. The paper also explores the role of middleware solutions, like Enterprise Service Bus (ESB) and API gateways, in facilitating seamless data flow between Salesforce and other systems.

Analyzing AWS Edge Computing Solutions to Enhance IoT Deployments

This paper explores integrating Internet of Things (IoT) deployments with edge computing, focusing on Amazon Web Services (AWS) as a key facilitator. It provides an analysis of AWS IoT services and their integration with edge computing technologies, addressing challenges, and practical applications across industries, and outlining future research directions. IoT and edge computing revolutionize data processing by enabling real-time analytics, reduced latency, and enhanced operational efficiency. IoT involves interconnected devices autonomously gathering and exchanging data, while edge computing processes data near its source, decentralizing data processing and minimizing data transmission to centralized servers. AWS facilitates scalable and secure infrastructures for IoT and edge computing. AWS IoT Core manages IoT device connectivity and data ingestion, AWS Greengrass extends AWS capabilities to edge devices, and AWS Lambda enables serverless computing, empowering efficient deployment and scaling of IoT applications. Centralized cloud architectures often struggle with vast IoT data. Edge computing decentralizes data processing, reducing latency, enhancing real-time capabilities, and minimizing bandwidth. AWS ensures secure device connectivity through AWS IoT Core, supporting various protocols for seamless integration with IoT devices. AWS Greengrass allows local data processing and machine learning at the edge, vital for environments with limited connectivity or stringent latency requirements. AWS Lambda supports serverless computing, enabling scalable, event-driven architectures without server management, crucial for fluctuating IoT workloads. In conclusion, AWS advances IoT capabilities at the edge, with practical implementations across industries. As IoT evolves, AWS remains pivotal, innovating to meet dynamic IoT deployment demands.

Designing Claim Systems in Health Insurance Companies with Microservices and Event-Driven Architecture Approach

Through digital transformation, insurance companies, especially in the health sector, are increasingly adopting modern technologies to enhance efficiency and service quality. Health insurance allows individuals or families to mitigate the financial risks associated with high and unexpected medical expenses. One crucial area is insurance claim, where a fast and accurate process is key to customer satisfaction. This study proposes the design and architecture of an insurance claim system using a microservices and event-driven approach. This approach enables insurance companies to break down applications into separate components, facilitating scalability, flexibility, and easier maintenance. Additionally, with an event-driven approach, the system can quickly respond to changes and events in the business environment. A comprehensive analysis shows that implementing microservices and event-driven architecture in the insurance claim system can enhance overall system performance, scalability, and resilience. For insurance companies, adopting microservices and event-driven architecture can lead to increased operational efficiency, reduced time to market for new products, and improved customer experiences through faster claim processing. Policyholders will benefit from quicker claim resolutions and a more transparent and responsive claim process. This study provides valuable insights for health insurance companies looking to upgrade their IT infrastructure to meet future challenges. The findings from this research will be documented to support the development of insurance business technology, specifically for health insurance claims in Indonesia.

Unlocking Interactive Learning: Building a Robust Quiz Portal with MERN Stack Technology"

Online learning has become increasingly popular in the digital era, necessitating innovative platforms to effectively engage students. This research outlines the development and implementation of an interactive quiz portal utilizing the MERN (MongoDB, Express.js, React.js, and Node.js) stack to enhance learning outcomes. The portal features a user-friendly interface for easy navigation and access to a diverse range of quizzes on various subjects. To ensure scalability, performance, and real-time interactions, Node.js handles backend operations, React.js manages dynamic interfaces, Express.js is used for server-side development, and MongoDB stores data. The portal includes instant feedback mechanisms, gamification elements, and personalized user profiles to enhance user motivation and involvement. Furthermore, adaptive algorithms are employed to adjust quiz content based on user proficiency levels. This paper presents the design, development, and implementation of an online test platform using the MERN (MongoDB, Express, React, and Node.js) stack. The portal functions as an all-inclusive platform for administering tests, assessments, and learning evaluations in an online setting. The portal provides smooth integration of frontend and backend activities, guaranteeing strong performance and user interaction, by utilizing the adaptability and scalability of the MERN stack. The portal enables quick development and deployment cycles with the help of MongoDB's document-based data storage, Express.js's effective middleware and routing, React.js's dynamic UI components, and Node.js's event-driven architecture. To improve user experience and learning results, features including interactive feedback mechanisms, real-time performance monitoring, quiz design and administration, and user authentication are easily integrated.

Research and Design of One-stop Intelligent Elderly Care Comprehensive Service Platform Based on Event-driven Architecture

In the context of an aging population, innovative development of smart elderly care as a pension model not only offers a novel solution to address the increasing aging issue but also provides an alternative choice to cater to the expanding requirements of elderly care services. This study accomplished system design by conducting research and analysis on China's existing smart pension market while leveraging available information technology. Furthermore, Java Eclipse and MySQL were employed for system construction along with intelligent health monitoring devices to enable real-time health monitoring, collection of vital signs data, and artificial intelligence-based disease prediction within home environments for older adults. Consequently, this approach can fulfill the demands of elderly care services while facilitating intelligent, convenient, and humanized homecare experiences that allow seniors to enjoy their golden years while alleviating burdens on their children.

Checking Temporal Constraints of Events in EBS at Runtime

Abstract As a kind of software system, the Event-Based Systems (EBS) respond to events rather than executing a predefined sequence of instructions. Events usually occur in real time, so it is crucial that they are processed in the correct order and within temporal constraints. The objective of this work is to propose an approach to check if events of EBS at runtime preserve the specification of temporal constraints. To form the approach by logic process, we have formalized the EBS model, through which, we have proved that the complexity of the checking algorithms is only polynomial. The approach has been implemented as a tool (VER) to check EBS at runtime automatically. The results of the proposed method are illustrated by checking a real-world Event Driven Architecture (EDA) application, an Intelligent transportation system.

A Synergistic Elixir-EDA-MQTT Framework for Advanced Smart Transportation Systems

This paper proposes a novel event-driven architecture for enhancing edge-based vehicular systems within smart transportation. Leveraging the inherent real-time, scalable, and fault-tolerant nature of the Elixir language, we present an innovative architecture tailored for edge computing. This architecture employs MQTT for efficient event transport and utilizes Elixir’s lightweight concurrency model for distributed processing. Robustness and scalability are further ensured through the EMQX broker. We demonstrate the effectiveness of our approach through two smart transportation case studies: a traffic light system for dynamically adjusting signal timing, and a cab dispatch prototype designed for high concurrency and real-time data processing. Evaluations on an Apple M1 chip reveal consistently low latency responses below 5 ms and efficient multicore utilization under load. These findings showcase the system’s robust throughput and multicore programming capabilities, confirming its suitability for real-time, distributed edge computing applications in smart transportation. Therefore, our work suggests that integrating Elixir with an event-driven model represents a promising approach for developing scalable, responsive applications in edge computing. This opens avenues for further exploration and adoption of Elixir in addressing the evolving demands of edge-based smart transportation systems.

Containerized Event-Driven Microservice Architecture

توفر بنية الخدمات الصغيرة العديد من المزايا، خاصة لتطبيقات الأعمال، نظرًا لمرونتها وقابليتها للتوسيع وبنيتها المترابطة بشكل غير محكم لسهولة الصيانة. ومع ذلك، هناك العديد من العيوب التي تنبع من ميزات الخدمات الصغيرة، مثل حقيقة أن الخدمات الصغيرة مستقلة بطبيعتها يمكن أن تعيق التواصل الهادف وتجعل مزامنة البيانات أكثر صعوبة. تتناول هذه الورقة المشكلات من خلال اقتراح خدمات مصغرة مضمنة في حاوية في بنية غير متزامنة تعتمد على الأحداث. تحتوي هذه البنية على خدمات صغيرة في حاويات وتقوم بتنفيذ مدير الأحداث لتتبع جميع الأحداث في سجل الأحداث لتقليل الأخطاء في التطبيق. تظهر نتائج التجربة انخفاضًا في وقت الاستجابة مقارنةً بمبنيين معياريين آخرين، بالإضافة إلى انخفاض في معدل الخطأ.

Mechanism for Efficient Media Propagation in Event-Driven Cyber-Physical Systems

Many key applications in Cyber-Physical Systems require the transmission of speech, audio, or video. These scenarios involve the use of traditional Real-Time Communication (RTC) protocols and technologies, which cannot always be used in the context of core networks. This is particularly critical in the context of Event-Driven Architectures (EDAs), where RTC protocols require the use of complex topologies that rely on costly infrastructure. One way to avoid this is by encapsulating all media traffic in EDA protocols. However, this approach does not come without challenges. Specifically, the nature of the transport protocols causes the media to be heavily affected by application layer impairments that render their usage highly impractical. To prevent this from happening, this paper introduces a unified scheme that supports the efficient encapsulation of media traffic in EDA scenarios. This is accomplished through a mechanism that relies on a Machine Learning (ML) model that is exercised in an experimental framework.

OPTIMIZING NODE.JS APPLICATION PERFORMANCE THROUGH MAIN THREAD OFFLOADING

Node.js is a JavaScript runtime environment that allows you to run JavaScript code outside of a web browser. It works by using a single thread to handle multiple requests using a callback-based event loop. This means that Node.js operates in an event-driven, non-blocking I/O model. One potential weak point of Node.js is that it is designed to be a single-threaded runtime environment, which means that it may not be the best choice for applications that require a high degree of parallelism or multi-threading. While Node.js can handle multiple I/O operations simultaneously through its event-driven architecture, it can struggle with CPU-bound tasks that require heavy computation. This academic article investigates the concept of "offloading" the main thread in Node.js, which refers to the process of delegating heavy computational tasks to worker threads to improve the overall performance and responsiveness Node. js application. The article provides a comprehensive analysis of different techniques for offloading the main thread, such as using worker threads, child processes, and cluster modules. It also explores the potential trade-offs and performance implications of each technique, and provides recommendations for selecting the most suitable approach for different use cases. The article highlights the importance of optimizing the use of CPU resources and avoiding blocking the event loop, which can lead to degraded performance and poor user experience. It also emphasizes the need for careful monitoring and profiling of Node.js applications to identify performance bottlenecks and optimize the use of available resources. Overall, this article provides valuable insights and practical recommendations for developers and system architects who want to improve the performance and scalability of their Node.js applications by unloading the main thread.

Technologies that are Anchored on Event Driven Architecture and their Impact on the Digital Economy

Event-Driven Architecture (EDA) has emerged as a pivotal framework in the digital economy, revolutionizing how systems are designed, implemented, and operated. By focusing on the production, detection, and reaction to events, EDA enables systems to be more responsive, scalable, and flexible. This research paper explores various technologies anchored on Event-Driven Architecture and examines their profound impact on the digital economy. Key technologies such as artificial intelligence (AI), the Internet of things (IoT), big data, block chain, 5G, 3Dprinting, robotics and drones are analyzed to understand their roles in enhancing real-time data processing, enabling micro services, and facilitating seamless integration across diverse systems. The study highlights how these technologies contribute to operational efficiency, customer experience, and business agility, while also addressing challenges related to implementation and management. The findings provide insights into how leveraging EDA can drive innovation and competitiveness in the digital economy, offering a roadmap for organizations aiming to harness the full potential of event-driven systems.

On the impact of event-driven architecture on performance: An exploratory study

Event-driven architecture has been widely adopted in the software industry in recent years. This adoption is motivated by the increase in software modularity, and mainly the desired performance of decomposed monolithic applications. Although it has become popular, the current literature lacks studies that demonstrate the impact of event-driven architecture on performance. Hence, developers and architects end up adopting event-driven architecture without empirical evidence, but considering “expert advice.” This study, therefore, reports an empirical study on the impact of the adoption of event-driven architecture on performance. For this, the performance of an application implemented with an event-based architecture was compared with the performance of the same application implemented using a monolithic architecture. The comparison was made using metrics such as CPU usage, memory, response time, throughput, and total packages sent and received. The results, supported by statistical tests, show that the monolithic architecture, compared to the event-driven architecture, consumes less computational resources and has better response times. Finally, this study reflects on the adoption of event-driven architecture, as well as points out challenges and implications that need to be considered by the scientific community in future research.

Flow and unified information-based DDoS attack detection system for multi-topology IoT networks

Internet of Things (IoT) networks are vulnerable to Distributed Denial of Service (DDoS) attacks, which can degrade their Quality of Service (QoS). In general, DDoS attacks are classified into high- and low-volume attacks. Existing statistical-based methods for DDoS attack detection in IoT networks are effective only for high-volume or low-volume attacks, but not for both. The majority of research in this domain relies on single-dimensional analysis and static thresholds. In response to these limitations, this paper introduces a Flow and Unified Information-based DDoS (FLUID) attack detection system, a lightweight statistical approach, for DDoS attack detection in IoT networks. The FLUID system incorporates multi-dimensional analysis by integrating unified information and flow behavior to effectively identify both high- and low-volume DDoS attacks. FLUID utilizes entropy and distance metrics, such as Kullback–Leibler (KL) divergence and greedy bin-packing, as unified information measures to distinguish legitimate traffic from malicious activity. Additionally, it examines flow behavior to gain insights into network traffic patterns. Notably, the FLUID system maintains its lightweight nature through a streamlined set of network features and optimized computational efficiency. Evaluations on real-world IoT client/server and Event-Driven Architecture (EDA) testbeds with the ToN-IoT, CICIDS 2017, CICIDS 2019, and DoS/DDoS-MQTT-IoT datasets show that the FLUID system can achieve over 90% detection accuracy for both high- and low-volume DDoS attacks.