This week: NoSQL interview questions and answers, YouTube Shorts generation via AI, Pinterest’s recommendation quality improvements, and Uber’s real-time OLAP with Apache Pinot.

This article explains how to identify service boundaries using Domain-Driven Design and Bounded Contexts. It shows how to move from a messy business domain to clear, well-defined contexts, and then to microservices, using a realistic domain map and bounded context diagrams

This chapter explores NoSQL Databases questions that  .NET engineers should be able to answer in an interview.

This week, we look at consistency models in distributed systems, Uber’s adaptive benchmarking framework, LinkedIn’s evolution of its Venice ingestion pipeline, and Meta’s new open-source platform for adaptive experimentation.

Weekly tech digest: CAP theorem basics, Uber’s probabilistic heatmaps, Dropbox’s context-aware AI, and Lyft’s modern ML platform architecture.

An article with a comparison between the dot-com bubble and today’s AI boom, highlighting the hype, the parallels, the fundamental differences, and why some AI companies will thrive while others will vanish during the inevitable market correction.

In this article, we explore practical patterns for data versioning and schema evolution in NoSQL systems.

This week: MongoDB best practices, Netflix’s ML platform, Uber’s I/O observability at petabyte scale, and Google’s Coral NPU for edge AI.

 Walk through consistency models in distributed systems: Strong, bounded staleness, session, causal, and eventual consistency, explain how they work with examples, and help you understand when each model makes sense.

In this article, we explain the CAP theorem in simple terms: what Consistency, Availability, and Partition Tolerance mean, why you can’t have all three, and how real systems balance them in practice.

This week, we dive into SQL performance tips, Uber’s approach to fault-tolerant analytics, and how TikTok cut AI costs in half with smart caching.

Practical MongoDB best practices guide for developers. Covers schema design, indexing, performance, queries, transactions, sharding, and common mistakes with examples and links to official docs.