Databases

Weekly tech digest: DDD bounded contexts, Netflix Live Origin streaming infrastructure, Uber’s shift to cloud-native observability, and Lyft’s evolving feature store architecture

In this article, we explore microservices and distributed systems interview questions and answers, and what every .NET engineer should know, from service boundaries and BFF to sagas, events, service discovery, and communication patterns.

Weekend Reading: A weekly roundup of interesting Software Architecture and Programming articles from tech companies. Find fresh ideas and insights every weekend.

A practical guide to the Outbox and Inbox patterns for reliable asynchronous messaging in distributed systems. Learn how Outbox ensures safe event publishing and Inbox ensures idempotent event processing, with step-by-step diagrams and implementation insights.

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 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.

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.