TradeFlux
Cloud-native trading infrastructure simulation built with event-driven microservices, Kafka, and observability tooling.
Backend Engineer
I'm Yash Chauhan, a backend engineer passionate about distributed systems, cloud-native infrastructure, and scalable software architecture. This website documents the systems I've built, the architectural decisions I made, the trade-offs I encountered, and the lessons learned while building production-inspired software.
Engineering Work
A collection of production-inspired backend systems, distributed architectures, cloud-native applications, and software engineering projects. Each case study documents the problem, architecture, engineering decisions, implementation details, and lessons learned throughout the development process.
Cloud-native trading infrastructure simulation built with event-driven microservices, Kafka, and observability tooling.
Production-inspired distributed URL shortening platform designed around scalable microservices, event-driven communication, caching, rate limiting, and cloud-native deployment.
Low-latency bidding engine built with Kafka and distributed microservices.
Workflow orchestration engine with event-driven execution.
AI-native travel platform built with cloud-native microservices, event-driven architecture, and an intelligent orchestration service that provides context-aware travel assistance.
AI-assisted logistics and inventory optimization platform.
Kafka-powered event ingestion and real-time data processing platform.
Production-ready payment backend with event-driven settlement and distributed transactions.
Scalable Reddit-style backend featuring nested comments, voting, feeds, and community-driven discussions.
Engineering Notes
Articles on backend engineering, distributed systems, cloud-native architecture, databases, messaging systems, and software design.
Learn how Continuous Integration and Continuous Delivery automate software builds, testing, and deployments to improve development speed and reliability.
Learn how Kubernetes automates container deployment, scaling, self-healing, and orchestration for modern cloud-native applications.
Learn how Docker packages applications into containers, why containers are different from virtual machines, and how Docker simplifies development and deployment.
Learn how the Saga Pattern manages distributed transactions across multiple microservices without relying on traditional two-phase commit protocols.
Learn how Command Query Responsibility Segregation (CQRS) separates read and write operations to improve scalability, performance, and maintainability in distributed systems.
Learn how API Gateways simplify microservice communication by handling routing, authentication, rate limiting, request aggregation, and security.
Learn how load balancers distribute traffic, improve availability, eliminate single points of failure, and enable modern distributed systems to scale efficiently.
Learn how database sharding enables horizontal scalability, distributes data across multiple servers, and helps backend systems handle millions of users efficiently.
Learn how database indexes improve query performance, how B-Tree indexes work, and the trade-offs every backend engineer should understand before adding an index.
Understand how Kafka partitions enable horizontal scalability, message ordering, fault tolerance, and parallel event processing in distributed systems.
Learn how Kafka Consumer Groups enable horizontal scalability, fault tolerance, and parallel event processing in modern distributed systems.
A practical look at using Redis in a distributed URL shortener to reduce database load, improve redirect latency, handle cache misses, and design an efficient cache-aside strategy.
Comparing relational and document databases, their trade-offs, and when to choose PostgreSQL or MongoDB for production systems.
Understanding how Redis is used for caching, distributed locking, pub/sub, rate limiting, and session management in modern backend systems.
A practical comparison between Kafka and RabbitMQ, covering architecture, scalability, ordering guarantees, throughput, and when each technology should be used.