Articles
Deep dives on .NET, React, cloud and everything in between.
Redis Failure Under Extreme Traffic: How to Prevent a Database Crash When 1 Million Requests Hit at Once
Learn how to design a resilient caching architecture when Redis suddenly goes down and millions of requests fall back to the database. Explore cache stampede, thundering herd, circuit breakers, rate limiting, request coalescing, cache warming, graceful degradation, Redis high availability, TTL strategies, and protecting the database from sudden traffic spikes.
07 Oct 2026 · 36 views
Designing a High-Scale Railway Ticket Booking System: Handling 2 Million Users for 500 Seats
Learn how to design a highly scalable railway ticket booking system that can handle 2 million users competing for just 500 seats. Explore traffic spikes, virtual queues, rate limiting, seat inventory management, distributed locking, Redis, database consistency, reservation timeouts, payment processing, idempotency, fault tolerance, and strategies to prevent double booking.
07 Oct 2026 · 24 views
Amazon SNS with C#: Complete Guide to Topics, Publishers, Subscribers, Fan-Out & .NET Integration
Learn Amazon SNS with C# from the basics to real-world event-driven architecture. Understand SNS topics, publishers, subscribers, message publishing, subscriptions, filtering, fan-out architecture, SQS integration, Lambda integration, email and HTTP notifications, retries, security, and a practical hands-on lab using the AWS SDK for .NET.
07 Oct 2026 · 17 views
Amazon SQS with C#: Complete Guide to Queues, Messages, FIFO, DLQ & .NET Integration
Learn Amazon SQS with C# from the basics to real-world .NET applications. Understand queues, producers, consumers, message sending and receiving, visibility timeout, retries, dead-letter queues, Standard vs FIFO queues, long polling, message deletion, Lambda integration, and a practical hands-on lab using the AWS SDK for .NET.
07 Oct 2026 · 14 views
Cache-Aside — System Design
Cache-Aside is the most commonly used caching pattern in system design. Reading from the database when cache misses Putting the database result into cache.
27 Sep 2026 · 24 views
What is Caching?
Caching means storing frequently accessed data in a faster storage layer so that future requests can be served faster without repeatedly accessing the primary database or another slower system.
27 Sep 2026 · 39 views
Hot, Warm & Cold DR — Disaster Recovery
When production goes down because of a region failure, database failure, infrastructure failure, or major outage, we need a Disaster Recovery (DR) strategy.
27 Sep 2026 · 36 views
RTO — Database Scaling
RTO (Recovery Time Objective) defines how quickly a system must be restored after a failure. In simple words, RTO = How much downtime can the business tolerate?
27 Sep 2026 · 23 views
RPO — Database Scaling
RPO (Recovery Point Objective) defines how much data an application can afford to lose after a failure.
27 Sep 2026 · 23 views