Connecting Developers to Architectural Excellence
Connecting Developers to Architectural Excellence
One of the most common—and deceptively simple—questions in AI & ML interviews is: “Can you explain the difference between supervised, unsupervised, and reinforcement learning?” While it appears basic, interviewers use this question to evaluate how you conceptualize learning problems, choose modeling…
Few topics expose shallow understanding in interviews faster than the question: “What is the difference between AI, Machine Learning, and Deep Learning?” On the surface, this sounds basic. In reality, interviewers use this question to assess conceptual clarity, systems thinking, and…
AI and Machine Learning interviews are rarely about getting the “right” answer. Instead, they are designed to uncover how you think, reason, and make decisions when building intelligent systems. Interviewers use AI & ML questions as a diagnostic tool—to assess engineering…
Artificial Intelligence (AI) is no longer a niche specialization reserved for research labs or data science teams—it has become a core competency evaluated across software engineering, architecture, data, and product roles. In modern technical interviews, AI is not tested merely as a…
In this case study, we examine the design of a scalable system for managing and counting “likes” on a social media platform. Such a system must handle high volumes of user interactions efficiently, ensuring reliability, low latency, and scalability to…
1. Overview A scalable notification service is a critical backend component for modern applications, responsible for delivering timely, personalized messages to users across multiple channels (push notifications, email, SMS, in-app, WhatsApp, etc.). This system powers user engagement in products like…
1. Overview A distributed job scheduler is a system that reliably executes tasks (jobs) at specified times or intervals across a cluster of machines. It powers background processing in virtually every large-scale application: cron jobs, ETL pipelines, report generation, cache…
1. Overview A distributed rate limiter is a critical infrastructure component that enforces per-entity request quotas across a fleet of stateless application servers (e.g., microservices behind a load balancer). In a single-node system, rate limiting is trivial (in-memory counter), but…
1. Overview This case study presents a comprehensive design for a fully distributed, highly available, and linearly scalable key-value store, directly modeled after Amazon’s Dynamo technology (the foundational system behind DynamoDB, Riak, Cassandra, and Voldemort). The core philosophy is radical decentralization:…
1. Overview This case study outlines a scalable, distributed web crawler architecture capable of processing billions of pages daily. It incorporates fault tolerance, politeness policies, and deduplication. The implementation leverages .NET 8 for high performance, with components for orchestration, fetching,…