Popular System Design Posts

This case study describes a production blog platform backed entirely by Amazon DynamoDB . The system serves typical blog workloads such as “latest posts”, “most popular posts”, “posts by author”, and “posts by tag”, while also supporting administrative queries like user moderation and contact messag

What availability means, how it's measured, architecturalavailability patterns, practical trade-offs, and how to validate an availability target. Availabilityis the probability that a system performs its required function at a given point in time. Practically, it answers the question:“Is the service

Caching is the process of temporarily storing frequently accessed data in a faster storage layer to reduce latency, save computation, and improve system scalability. Instead of recomputing or refetching data from a slower source like a database or API, a cache serves it quickly from memory or nearby

Scalability is the ability of a system to handle increased load — such as more users, data, or requests — without unacceptable performance degradation. It can be achieved in two main ways: It also includes operational, cost, and development scalability — how the system, budget, and team scale with g

SQL databases (also known as relational databases) are systems designed to store, organize, and query structured data using a predefined schema. They are built around the relational model, where data is stored in tables and relationships between entities are explicitly defined.

The Domain Name System (DNS) is a distributed naming system that translates human-readable domain names (like example.com) into IP addresses used by machines to communicate over the internet.

A Content Delivery Network (CDN) is a distributed network of servers that cache and deliver content closer to users. Instead of serving every request from a single origin server, a CDN uses geographically distributed edge locations to reduce latency and improve performance.

CAP theorem defines three guarantees in distributed systems: consistency , availability , and partition tolerance, with the constraint that only two can be fully satisfied during a network partition. In real-world architectures, partition tolerance is unavoidable, which forces systems to choose betw

This benchmark comparesPostgreSQLandClickHouseusing identical data and queries to evaluate performance in a read-heavy analytical workload. Each query was executed once. Both PostgreSQL and ClickHouse were run with default configurations (no custom tuning). The goal of this article is to demonstrate

Relational Database Management Systems (RDBMS)remain foundational infrastructure in modern distributed systems because they provide strong consistency, transactional guarantees, and mature tooling for data integrity. Large-scale systems such as payment platforms, logistics networks, and SaaS product

Modern distributed systems rely on communication protocols that define how services exchange data. As a software developer designing APIs, microservices, real-time systems, or event-driven platforms, choosing the correct protocol directly impacts latency, scalability, observability, cost, and develo

Consistency patternsdescribe how systems behave when multiple actors read and write shared data, especially under concurrency, failure, or distribution. Database transactions are one of the strongest tools for enforcing consistency, but they coexist with weaker models that trade correctness guarante

Domain Name System (DNS) is a distributed naming system that translates human-readable domain names into IP addresses used for routing. In system design, DNS is a hidden dependency that directly affects latency, availability, and security . For example, a stale DNS record in a regional resolver can

TheCAP theoremis one of the most fundamental principles in distributed system design. It defines the trade-offs between three key properties —Consistency,Availability, andPartition tolerance— and explains why it’s impossible to achieve all three simultaneously in a distributed data system. Formally

Consistency is one of the foundational concerns when designing distributed systems. It answers the question:when a client reads data, how fresh or correct should that data be compared to the most recent write?Different applications have different tolerances for stale or conflicting data. This articl

Caches can exist on the client (OS or browser), on the server, or in a dedicated cache layer. Content delivery networks (CDNs) act as distributed caches to improve performance and availability. Reverse proxies and caching servers like Varnish can serve static and dynamic content directly. Web server