MrComputerScience.com
Blog For Marketing And Tech Nerds
Distributed systems power the modern internet, from cloud platforms to large-scale applications serving users around the world. In this category, I explore scalability, fault tolerance, consensus, replication, reliability, and the engineering challenges that appear as soon as software runs across multiple machines.
Distributed computing sounds straightforward until networks fail, servers crash, and data must stay correct across many nodes at once. If you want to understand how real internet-scale systems are designed and operated, this is one of the most important areas of computer science to study.
Browse the articles below to explore distributed systems and large-scale infrastructure.
When Stripe processes a payment, it needs to notify your application, update its own internal systems, trigger fraud analysis, and record the event for audit purposes. Calling each destination …
Continue Reading about Why Does Stripe Use Kafka Instead of Just Calling Your API? →
A network partition is when nodes in a distributed system can no longer communicate with each other. The nodes are not down, the network between them is broken. Every distributed system must choose …
Continue Reading about What Happens When a Network Partition Hits Your Distributed System? →
Cassandra defaults to eventual consistency because strong consistency requires coordination between replicas, and coordination costs latency and availability. At its default consistency level of ONE, …
Continue Reading about Why Does Cassandra Let You Read Stale Data by Default? →
