Bookmundi

Client

Bookmundi

Link

Check the website

Brand Overview

Bookmundi, an online travel booking platform, initially faced challenges with slow website performance, limited scalability, and the absence of features like map integration and high-resolution images. To address these issues, the platform was restructured using a microservices architecture, augmented with a queuing mechanism for efficient request handling. Further enhancements included dockerizing the platform components for environment consistency and deploying them via Kubernetes to ensure scalability and robustness.

Project Goals

  1. Performance Improvement: Enhance the website's speed to provide a seamless user experience.

  2. Scalability: Ensure that the platform can handle an increase in user traffic without compromising performance.

  3. Feature Enhancement: Integrate advanced features like map integration, 2x resolution images, and enhance the overall server capabilities.

Problems

  1. Website Performance: The website initially suffered from slow loading times, which affected user experience.

  2. Scalability Issues: The platform was not designed to scale efficiently with an increase in user traffic.

  3. Feature Limitations: There was a lack of certain key features like map integration and high-resolution images which limited the website's utility.

Solutions

  • Microservices Integration: To tackle the issues of scalability and performance, the monolithic architecture was broken down into smaller, manageable microservices. This not only made the system more modular but also improved its performance.

  • Queuing Mechanism: To manage the server requests efficiently and ensure that no single request overwhelms the system, a queuing mechanism was put in place.

  • Dockerization: The platform components were dockerized, which means they were packaged into containers. This ensured consistency in deployment, irrespective of the environment, and also made scaling individual components easier.

  • Kubernetes Deployment: The dockerized components were then deployed using Kubernetes, an orchestration tool for containerized applications. This allowed for easy scaling, self-healing, and load balancing, ensuring high availability and resilience.

The Approach

  1. Assessment Phase

    Started by analyzing the existing system to pinpoint bottlenecks and areas of improvement.

  2. Architecture Redesign

    Moved from a monolithic architecture to a microservices-based design to improve modularity and scalability.

  3. Integration of Queuing

    To handle the server requests more efficiently, a queuing system was integrated to manage the traffic and ensure smooth operations.

  4. Containerization

    Adopted a container-centric approach by dockerizing the platform components. This ensured that the application runs consistently across different environments.

  5. Orchestration with Kubernetes

    Deployed the dockerized components in a Kubernetes cluster. This helped in automating deployment, scaling, and management of containerized applications.