Case Studies
Feb 21, 2024

PXL - Open Source Social Network Platform

Project Summary

PXL is an open source social network platform for content creators. It enables users to create public or private spaces for any use such as any particular task base space or any other. Furthermore, users can take advantage of social features such as building connections, posting projects that pique the interest of other users, adding team members, notifications, project participation, and more. They can also manage their profiles and conduct a global search. This social network tool offers an online version where anyone can experience this free tool. PXL’s user interface is very logical, and users can easily navigate through various elements.

Problem Statement

The client’s requirement was to build a full-fledged backend application that can easily integrate with their prebuilt front-end application, and he later asked us to integrate the backend with the front-end.

We had to design and create a social platform where users can showcase their inventions and gain exposure. One can post any software project, categorize them, invite team members, and also participate in other projects.

Additionally, to meet the need for significant content uploads, a solution had to be developed that could easily handle the upload of media files while still being affordable and effective.

We also had to create a real-time notification system that monitors all network activity such as accepting requests, declining requests, and being removed from one’s network.

Our Solution

  1. With thorough testing, responsive design, and increased efficiency and performance, we concentrated on completing each task as effectively as we could.
  2. Based on the client’s requirements, we used S3 bucket, RDS, EC2, and flask microservice for media files and SES for emails.
    - Amazon S3 was used for file hosting and data persistence.
    – Amazon Relational Database Service (RDS) was used for database deployment as it simplifies the creation, operation, management, and scaling of relational databases.
    – Amazon EC2 was used for code deployment because it offers a simple web service interface for scalable application deployment.
  3. We sent emails using Amazon SES because it is a simple and cost-effective way to send and receive emails using your own email addresses and domains.
  4. Django-graphQL was used for the backend, and Next.js was used for the front end. Django includes a built-in object-relational mapping layer (ORM) for interacting with application data from various relational databases.
    – GraphQL aims to automate backend APIs by providing type-strict query language and a single API Endpoint where you can query all information that you need and trigger mutations to send data to the backend.
    – Next.js offers the best server-side rendering and static website development solutions. We utilized the flask microservice to help with high content uploads since flask upload files give your application the flexibility and efficiency to manage file uploading and serving.
  5. Using Github’s automated CI/CD pipeline we have triggers for code lookup and deployment.


Django-GraphQL, Next.js, PostgreSQL, AWS S3, EC2, SES and RDS

Success Metrics

  • All deliverables were completed on time and exceeded expectations.
  • Met all the expectations of the client and with positive feedback.
  • The client was constantly updated on the status of the project.