esiepe / kejani

Real estate app using MERN and tailwind css

A passionate full stack developer. Let's make tech work

• 🔭 I’m currently working on KEJANI

• 🌱 I’m currently learning IoT, ML & AI

• 🤝 I’m looking for help with KABU CS HUB

• 👨‍💻 All of my projects are available at esiepe.github.io

• 💬 Ask me about Vanilla JS, Python

• 📫 How to reach me [email protected]

• ⚡ Fun fact I love chapati

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kejani's Issues

Implement Environment-Specific Configurations

Current State: The application uses a single configuration for all environments (development, testing, production). This might lead to sensitive information (API keys, passwords) being exposed in non-production environments.
Impact:
Potential security vulnerabilities if sensitive data is leaked accidentally.
Difficulty in managing different configurations for different environments.
Risk of accidentally deploying a development configuration to production.

Transition contacting landlords from emailjs to real-time chat using Socket.IO.

Integrate Socket.IO on both the client-side and server-side of the app.
Chat Interface Design:

Design a chat interface accessible to both tenants and landlords, allowing them to initiate and respond to conversations.
Consider features like:
Role identification (tenant/landlord labels) for clarity.
Typing indicators for a smoother chat experience.
File attachments for sharing documents (e.g., maintenance requests, lease agreements).
Optional chat history for reference (weighed against storage and privacy implications).
Server-Side Implementation:
Upon receiving a message:
Identify the sender's role (tenant/landlord).
Route the message to the appropriate recipient(s) within the app, depending on the sender and intended recipient.
Benefits:

Real-time communication for both tenants and landlords.
Increased efficiency in resolving issues and inquiries.
Improved transparency through shared chat history.
Streamlined workflows for landlords (managing conversations within the app).

Dockerize the Application

Current State: The application is not currently containerized using Docker. This means it might be difficult to deploy consistently across different environments or require manual setup on each server.
Impact:
Inconsistency in application behavior across environments.
Difficulty in scaling the application if needed.
Increased complexity during deployment and maintenance.