Computer Science Engineering Archives

Design Patterns Simplified: A Practical Guide to Core Principles and Key Patterns (Part-1)

Design Patterns Simplified: A Practical Guide to Core Principles and Key Patterns (Part 1)

Are you looking to simplify your software design and write clean, scalable code? In this first part of my series on design patterns, we’ll dive deep into the basics of Object-Oriented Programming (OOP), explore essential design principles, and lay the groundwork for understanding patterns. From encapsulation to polymorphism, this blog is packed with practical examples (Java included!) that show how OOP principles make your code more flexible and maintainable. We’ll also cover how big companies rely on design patterns to build scalable systems. Whether you’re just starting out or brushing up, this is a great starting point to enhance your software design skills. Stay tuned for the upcoming posts where we’ll explore the most used design patterns in real-world scenarios!

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Understanding Zero Trust Architecture: Enhancing Security with ‘Never Trust, Always Verify’

Computer Science Engineering, Software Engineering, System Design / 10 minutes of reading

Zero Trust Architecture (ZTA) is a cybersecurity model based on the principle of “never trust, always verify.” It ensures that every user, device, and data packet is authenticated and authorized before accessing network resources. Key principles include explicit verification, least privilege access, micro-segmentation, continuous monitoring, and encryption. Implementing ZTA can enhance security, reduce data breach risks, and improve access control, though it requires significant infrastructure changes and user education. As cyber threats evolve, integrating AI and machine learning with ZTA will be crucial in securing cloud computing, edge computing, and IoT environments.

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Mastering Event-Driven Architecture with Apache Kafka: Harnessing Asynchronous Communication for Real-Time Data Processing

Computer Science Engineering, Software Engineering, System Design / 7 minutes of reading

This comprehensive guide dives into Event-Driven Architecture (EDA) and its champion, Apache Kafka. You’ll learn how EDA fosters scalability, responsiveness, and loose coupling in your systems. As an expert in high-throughput streaming, Kafka empowers real-time data processing. Explore Kafka’s architecture, hands-on tutorials, and best practices to architect, build, and deploy robust event-driven applications.

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Making the Switch: Transitioning from REST to gRPC

Computer Science Engineering, Software Engineering / 5 minutes of reading

Unveiling gRPC: High-Performance RPC Framework for Distributed Applications

gRPC is a powerful open-source framework by Google that simplifies building distributed applications. It allows clients to invoke methods on servers as if they were local, promoting seamless communication between services. This article explores gRPC’s core concepts, its advantages over REST APIs, and when to choose gRPC for optimal performance in your projects.

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HTTP/2: The Next Generation of Web Communication

Computer Science Engineering, Software Engineering / 9 minutes of reading

This passage explores the evolution of Hyper Text Transfer Protocol (HTTP) from HTTP1.1 to HTTP/2. It explains how HTTP/2 offers significant improvements in web performance through features like multiplexed streams, server push, binary protocols, and stream prioritization. These features address limitations of HTTP1.1 such as head-of-line blocking and inefficient resource transmission, resulting in faster page load times and a better user experience. The document also highlights the security benefits of HTTP/2 compared to text-based HTTP1.1. Overall, HTTP/2 is a major advancement in web communication, crucial for businesses and web users alike.

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System Design: Rate Limiting Monitoring Aspect

Computer Science Engineering, Software Engineering, System Design / 3 minutes of reading

Rate limiting is a technique used to control the rate of requests made to a system, such as an API or website. It is used to prevent denial-of-service attacks, resource exhaustion, and unstable performance. Rate limiting works by setting a limit on the number of requests that can be made from a single IP address or user within a specific timeframe. When this limit is exceeded, the system will throttle or block the requests.

Here are some of the benefits of rate limiting:

* Prevents denial-of-service attacks
* Protects against API abuse
* Optimizes resource utilization
* Ensures user fairness

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