Service Marketplace Project

market place

Executive Summary

We were tasked with implementing an event-driven architecture called the Service Marketplace, which was structured in different phases:

 

  • Design

  • Implementation

  • Testing

  • Production Deployment

Challenges – Client Pain Points

This project was initiated due to the client’s existing architecture, which required full compliance with API management through 3scale and seamless integration with their Apache Kafka platform.

The client originally approached Red Hat with this requirement, but Red Hat confirmed that they could not deliver the solution as requested.

Client Benefits:

API Management: 3scale provides a comprehensive suite of tools and capabilities for managing APIs, including access control, rate limiting, and advanced analytics. It enables organizations to secure and monitor APIs, enforce policies, and ensure consistent governance across the enterprise.

Scalability: 3scale is designed to handle high volumes of API traffic. It can scale horizontally to meet growing API consumption and guarantee consistent, reliable performance even under heavy load.

Real-Time Data Streaming: Kafka is engineered to handle real-time data streams. It delivers high-throughput, low-latency message processing, making it ideal for data-intensive applications that demand continuous updates, analytics, and real-time responsiveness.

Elastic Scalability & Fault Tolerance: Kafka is a distributed streaming platform that scales horizontally by simply adding brokers to the cluster. It provides fault-tolerant storage and replication across multiple nodes, ensuring high availability and data durability even in the event of system failures.

 

Event-Driven Architecture: Kafka’s pub/sub messaging model empowers a fully event-driven architecture, where producers publish events to topics and consumers react to them in real time.

Data integration

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“The success of an implementation project lies in the perfect balance between strategic planning, effective execution, and adaptability in the face of challenges. With commitment and teamwork, we transform vision into reality.”

Results Achieved

Refactoring of existing Kafka topics within the project.

Architectural improvements to strengthen the event-driven model.

Full integration of 3scale API Management with Apache Kafka.

Technologies and Tools Used

Azure DevOps leveraged to run the entire process of automated deployments and continuous integration.

Containerization on OpenShift packaging applications and dependencies into isolated, portable environments for faster and more reliable deployments.

Java Backend (Java 8 & Java 11) Java was selected as the backend programming language for its robustness, platform independence, and object-oriented design. With built-in memory management and reduced error handling overhead, Java provided a stable, production-grade foundation for this solution.

In this project, the entire execution was carried out under agile approaches of the Scrum framework in accordance with Ken Schwaber & Jeff Sutherland's guide "The Scrum Guide, The Definitive Guide to Scrum: The Rules of the Game." Likewise, topics and tools related to PMI project management will be taken into account under the methodology established in the PMbook Guide. marco de trabajo Scrum de acuerdo con la guía de Ken Schwaber & Jeff Sutherland “La Guía Scrum, La Guía Definitiva de Scrum: Las Reglas del Juego”, de igual forma se tendrá en cuenta temas y herramientas referentes a la gestión de proyectos del PMI bajo la metodología establecida en el PMbook Guide.

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