Task Management System API Development Checklist

Areas to Explore

• Basic API Development

  • Setting up RESTful APIs, routing, and handling HTTP requests.
  • Creating endpoints for managing tasks

• Data Modeling and Persistence

  • Database design, SQL/NoSQL, and data persistence.
  • Designing schemas for tasks, users, and relationships.

• Concurrency and Asynchronous Processing

  • Managing concurrent processes for inventory updates.
  • Using background jobs for low-stock alerts and automated reordering.

• Authentication and Authorization

  • Securing the API with user authentication (e.g., JWT).
  • Implementing role-based access control.

• Error Handling and Validation

  • Handling errors and validating inputs for data integrity.

• Caching for Performance Optimization

  • Reducing database load by caching frequently accessed data.

• Testing and TDD (Test-Driven Development)

  • Writing unit, integration, and end-to-end tests for the API.

• Pagination, Filtering, and Sorting

  • Managing large data sets with efficient data retrieval.

• Rate Limiting and Throttling

  • Controlling access to prevent abuse and ensure resource availability.

• [V] Dependency Injection and Interfaces

  • [V] Using interfaces and dependency injection for flexibility and testability.

• [V] Microservice-Friendly Design

  • [V] Structuring the application for potential future microservices.

• Logging and Monitoring

  • Implementing structured logging and tracking key metrics.

• [V] Configuration Management

  • [V] Handling configurations for multiple environments.

• [V] Scalability and Load Balancing

  • [V] Designing your application to handle increased traffic.

• [V] Event-Driven Architecture

  • [V] Using an event-based system to handle changes in inventory.

• CQRS (Command Query Responsibility Segregation)

  • Separating read and write operations to improve performance.

• Event Sourcing

  • Storing changes to data as a series of events.

• Distributed Caching

  • Implementing a distributed cache to reduce load on your main database.

• Database Sharding and Replication

  • Splitting and replicating data across multiple databases for high availability and performance.