System Design & Distributed Systems

Practical notes on designing reliable, scalable backend systems and data platforms.

System design is the practice of turning product requirements into reliable software architecture. This guide collects the areas I use most often when designing backend systems: service boundaries, APIs, storage, messaging, observability, failure handling, and operational trade-offs.

Backend system design fundamentals

A good backend system design starts with the workload: traffic shape, latency targets, consistency requirements, data retention, and failure tolerance. From there, choose simple interfaces and explicit ownership boundaries before selecting infrastructure. Scalability is useful only when it preserves correctness and keeps the system operable.

Distributed systems and microservices

Distributed systems introduce partial failure, retries, duplicate delivery, clock differences, and coordination costs. Microservices can help teams scale ownership, but only when contracts, idempotency, timeouts, tracing, and data ownership are designed together. Start with a modular boundary and split services when the operational benefit is clear.

Cloud computing and infrastructure

Cloud computing makes capacity, networking, storage, and managed services available on demand. In practice, cloud infrastructure still needs careful decisions about availability zones, security, backups, cost, deployment safety, and disaster recovery. AWS, Kubernetes, Terraform, and observability tooling are most valuable when they make those decisions visible and repeatable.

Data engineering and event-driven architecture

Data engineering systems must make freshness, quality, lineage, and replay behavior explicit. Event-driven architecture with Kafka or similar brokers can decouple producers and consumers, while batch and streaming pipelines built with Apache Beam, PySpark, Dataflow, and BigQuery turn events into trustworthy data products.

Related work

Explore the backend systems projects for examples across data platforms, cloud infrastructure, and realtime services, or read the full engineering profile.