Appendix • Links • MicroServices Repos • Demo • Badges • Project requirements • Ports • Technologies
Looking for a hassle-free way to get tickets to your favorite events? Look no further! Our state-of-the-art ticket sales application is here to make your life easier. Built using event-driven architecture and the latest security best practices, our app is fast, secure, and reliable. Plus, with our commitment to test-driven development, you can trust that every feature has been rigorously tested to ensure a seamless experience. Don't miss out on the fun – get your tickets today with our cutting-edge application!
In each repo there is the documentation for each api
Here are some videos from our project!
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NodeJS - JS runtime environment
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Express - The web framework used
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PostgreSQL - Relational database management system
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Prisma - Node.js and TypeScript ORM
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SupaBase - Cloud database service
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KafkaJs - For pub/sub comunnication
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ReactJs - Front-end JavaScript library
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Algolia - Scalable, secure, digital search and discovery experiences that are ultrafast and reliable powered by AI, index and search across dataset
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JSON Web Token - Security token
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Stripe - Online payment API
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Postman - API testing
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Jest - Unit testing JavaScript Framework
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Vercel - Cloud platform
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Developed a Ticket Sales application using Node.js, Express.js, Kafka, PostgreSQL, and React.
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Implemented a full-stack web application with a scalable architecture to manage ticket sales.
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Utilized Node.js to build the backend REST APIs, Express.js as the web framework, and PostgreSQL for data storage.
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Designed and implemented efficient database schema to store customer and ticket information.
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Incorporated Apache Kafka for real-time data streaming and integrated it with the Node.js backend.
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Implemented secure payment processing using Stripe API.
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Built a responsive user interface using React, allowing users to efficiently purchase tickets.
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Employed JWT for user authentication and authorization.
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Implemented server-side rendering for improved performance and SEO optimization.
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Conducted testing and debugging to ensure high-quality delivery of the application.
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Deployed the application on a cloud-based platform for easy scalability and maintenance.
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Utilized agile methodologies to manage project development and ensure timely delivery.
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Followed best practices for code organization and documentation to maintain a high level of code quality.
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Stayed current with emerging technologies and industry trends to continuously improve the application.
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Participated in code reviews to ensure adherence to coding standards and best practices.
- Introduction
Your team is tasked with building backend services to handle ticket sales for the Fifa 2022 World Cup in Qatar. Given the huge demand on tickets, it has been decided by the Fifa governance committee that ticket sales can be purchased through several approved websites instead of having one single website to handle all the sales. As such, each team will serve as a separate website that provides a platform for buying official tickets. Each team will start with a master list of games which consists of all the games and total occupancy allowed, amongst other useful information. It is expected that each team will maintain their own copy of the master list and keep it updated. For example, if team/website #1 makes a reservation, that change should be reflected in teams 2..N. Each team can have up to 5 individuals.
- Technology
The technology stack for the backend services is comprised of:
- Node.js (Server-Side)
- MongoDB (NoSQL Database) or PostgresQL (RDBMS)
- Vercel (Cloud Platform Provider)
- Requirements
The system shall support the following services:
| Name | Backend |
|---|---|
| Shop | ✓ |
| Shop Consumer | ✓ |
| Reservations | ✓ |
| Payments | ✓ |
| Analytics | ✓ |
| Security | ✓ |
| Below, you will find a general description of each microservice and its respective purpose. More details will be provided in the upcoming milestone. |
Shop Microservice:
The shop microservice is responsible for providing ticket availability, recommendations, and prices.
Shop Consumer:
The shop consumer is responsible for listening to messages that are sent over a kafka broker and processing them accordingly. There will be two topics created. The first topic will be used once for sending the initial master list. The second topic will be used by all shop consumers across all teams to share ticket sales.
Reservations Microservice:
The reservations microservice is responsible for booking and allocating tickets. When a ticket is booked, the reservations microservice should produce a message that can be consumed by the shop consumer across all teams so they can update their master list accordingly.
Payments Microservice:
The payments microservice is responsible for processing payments.
Analytics Microservice:
The analytics microservice is responsible for aggregating all bookings and storing them in a data lake to train a machine learning model that can provide interesting recommendations to the shop microservice. For example, if a user is logging in from Latin America, they may be interested in booking tickets for Argentina, Brazil, Costa Rica, Ecuador, Mexico, or Uruguay games. This service can be extended to handle other use-cases which can be defined by each team.
Security Microservice:
The security microservice is responsible for protecting against fraud and/or malicious attacks. It will be up to the team to figure out how to protect their services accordingly. Although, more detail will be provided in upcoming milestones. When evaluating your system, we will try to exploit it for gain or attempt to bring the service down.
** milestone 2 info
- Introduction A portion of your flow requires an asynchronous implementation to facilitate the sale of tickets across other similar marketplace platforms.
- Masterlist The masterlist contains all details related to the games, availability, and pricing. This list will be published once over a specific kafka topic once the services have been deployed. The message will be published to the following topics:
- fifa-world-cup-2022-masterlist-dev
- fifa-world-cup-2022-masterlist-prod
- Shop Consumer The shop consumer is responsible for listening to messages that are sent over a kafka broker and processing them accordingly. There will be two topics created. The first topic will be used once for sending the initial master list. The second topic will be used by all shop consumers across all teams to share ticket sales. The second topic will handle at least three types of messages:
- TICKET_PENDING
- TICKET_RESERVED
- TICKET_CANCELLED When a ticket has been submitted for purchase, the /reservation endpoint should publish a message indicating the ticket is pending. This message will be received by all (ticket platform) consumers at which point a synchronous call will be made to sp-shop-api to update the masterlist indicating the ticket is pending. Each ticket is uniquely identified by the matchNumber and category. As taught in your OS course, we will treat each ticket sale as a “shared resource” and as such follow a semaphore/mutex approach. Thus, when a ticket is pending, we should have a field/column which maintains PENDING available count. Initially the reserved & pending count should be the same. If we receive 5 messages for pending ticket sales on other platforms, we should decrement our pending field/column by 5. Assuming the initial reserved count was 10, it means we can safely sell 5 tickets on our platform. However, if the pending count reaches 0, we should indicate “ticket is temporarily unavailable” in the UI. Once the served count is 0, we should indicate “ticket is sold out” on the UI. I have created a sample project for your consumer, which can be found here: https://github.com/desoukya/sp-shop-consumer One important feature needed in your consumer is to add code to not process messages that have been published by your producer. This can be accomplished by adding the clientId to the message.
- Shop API & Producer The shop service will expose the endpoints needed to allow a user to see available tickets, but also the necessary endpoints to handle incoming messages from kafka when a message is:
- Pending
- Cancelled
- Reserved (can be same endpoint used by UI) I have created a sample project for your api & producer, which can be found here: https://github.com/desoukya/sp-shop-api
- Security Service The security service should protect against malicious or suspect activity. As such, each incoming request into the system should check with the security service if the request is suspect or Ok to process. I will not provide specific requirements on what the security service should do; however, some sanity checks could include checking if:
- Request is from bot or belongs to a botnet
- Request is from to a blacklisted ip address
- Request exceeds API rate limit
- Request is suspect so require UI to perform captcha
- Topics All the topics in the system are:
- fifa-world-cup-2022-masterlist-dev | fifa-world-cup-2022-masterlist-prod
- fifa-world-cup-2022-ticket-sales-dev | fifa-world-cup-2022-ticket-sales-prod
3. Project Schedule & Deliverables
Your project will consist of four milestones, each worth 25%.
Milestone #1 (Due 11/25): UML component or architecture diagrams showing how your systems will interface and sequence diagrams for each microservice except Security and Analytics. In addition, all database tables/collections should be created with their respective schema/entity relationship.
Milestone #2 (Due 12/09): Create Shop, Shop Consumer, and Reservations Backend Services.
Milestone #3 (Due 12/23): Create Backend Payments, Security, and Analytics Services.
Milestone #4 (Due 01/03): Create Frontend Shop and Reservation Screens. \
Project Evaluations 01/04 - 01/05.
The monorepo uses the following ports:
Frontend
- Client: 9000
Backend
- Shop: 3000
- Consumer: 3010
- Reservations: 3020
- User: 3030
- Payments: 3040
- Security: 3050
Contributions are always welcome!
See contributing.md for ways to get started.
Please adhere to this project's code of conduct.
If you have any feedback, please reach out to us at https://ticktaka-client.vercel.app/contact