Auctions and Bids have been an integral part of B2B Businesses that have been managed mostly on the backend using traditional methods like Phone Calls or a physical setting. Creating an online distributed auction and bid management system would allow the corporate users to create and manage multiple auctions for the products and have the end-users bid on the products and purchase them with ease. The end goal is to have the buyers bid on the products with ease and provide real-time analysis of the bids and the probability of the bids becoming the winning bids.
This article talks about the basic architecture of building a system like above. The system is platform-agnostic and can be built on any platform like AWS, GCP, Azure, etc.
The Architecture
In order to architect this functionality and scale it to millions of users including sellers and buyers, we have to identify the services we would need and implement a microservice architecture. There are multiple advantages of Microservice Architecture that are beyond the scope of this article. You can read them here.
The microservice architecture would allow for separation of concerns by dividing the functionality into multiple self-sustained services functioning independently of each other. We will focus on achieving Consistency over Availability, as the data accuracy is the most important part of an auction system. We need to provide the users with the most accurate data all the time.
Now let’s start with the modules and the APIs needed to implement them.
Auction Module
The auction module would handle the auctions created by the admin. The module would allow the basic CRUD operations to the database. The data can be cached using a key-value store like Redis.
The APIs below addresses the basic API calls for the system.
GET /api/v1/auctions/:id
POST /api/v1/auctions/
Bid Management Module
The bid management module allows for creating and managing bids. The service allows for adding bids against an auction.
/api/v1/bids/:id
/api/v1/bids/
Analytics
Building an analytics system would complement the above system as we can analyze the bid data and provide the acceptability ratio of the placed bid. This feature would allow a user to understand what’s the probability of their bids getting accepted based on all the bid data that we have collected so far as well as the historical data for similar products. This feature would enhance the user experience and would create more accurate bids and reduce the standard deviation of the bid data.
Conclusion
To conclude, the Auction and Bid Management system can be built and scaled to handle millions of transactions using a microservice architecture. The system is a great replacement for the existing traditional systems in place. This system can be modified to handled other scenarios as well and can be implemented for multiple industries depending upon their needs.
