Software Engineering Lifecycle

The Software Engineering Lifecycle (also known as Software Development Life Cycle or SDLC) is a structured process that defines the steps involved in creating high-quality software. In the context of backend systems for a social media application, the major phases include:

1. Requirement Analysis:
   • Identify and gather requirements from stakeholders.
   • Example: Users need to create profiles, post content, like, comment, and follow others.
2. System Design:
   • Define system architecture, databases, APIs, and component interactions.
   • Example: Designing a database for storing user profiles, posts, likes, and comments with tables for Users, Posts, and Interactions.
3. Implementation (Development):
   • Write the code for backend logic, API endpoints, and database integration.
   • Example: Developing RESTful APIs for user registration, login, posting, and fetching feeds.
4. Testing:
   • Validate the functionality, performance, and security of the backend system.
   • Example: Unit testing for individual API routes, integration testing for user-post interaction, and load testing for handling high traffic.
5. Deployment:
   • Deploy the backend system to production using tools like Docker or Kubernetes.
   • Example: Deploying the social media backend on AWS with auto-scaling to handle millions of users.
6. Maintenance & Monitoring:
   • Continuously monitor system performance and handle bugs or feature updates.
   • Example: Using Prometheus and Grafana for real-time monitoring and updating the database schema to add new features like story posts.

Major Components of a Backend System

1. Computing Capabilities:

• Refers to the system's ability to process data, execute logic, and handle user requests.
• Involves servers, CPUs, memory management, load balancing, and scalability.
• Example (Social Media App): When a user posts an image, the backend processes the request, verifies data, compresses the image, and updates the database.
• Key Concepts:
  • Scalability: Vertical (adding resources to a single server) and horizontal (adding more servers).
  • Concurrency: Handling multiple requests simultaneously.
  • Fault Tolerance: Ensuring the system continues to operate despite failures.

2. Storage Capabilities:

• Focuses on how data is stored, retrieved, and managed efficiently.
• Involves databases, caching systems, and data redundancy.
• Example (Social Media App): Storing user profiles, posts, likes, and comments in a database like MongoDB or MySQL.
• Key Concepts:
  • Database Systems: SQL (structured) and NoSQL (unstructured) databases.
  • Caching: Redis or Memcached for faster data access.
  • Data Replication: Ensuring data availability by copying it across servers.
  • Backup and Recovery: Preventing data loss in case of failures.

Storage Options on a Computer