In distributed systems, ensuring data consistency and preventing race conditions is a major challenge, especially when many processes or services access shared resources concurrently. A distributed lock is an effective way to handle this problem. In this article, I will help you understand what a distributed lock is, why it is needed, the different ways to implement one, and how to build it with Redis.
Have you ever wondered what keeps payment services, social networks, and delivery apps running smoothly every single day? The secret lies in the Message Broker - the "invisible connector" that moves information safely and efficiently between systems. Let's explore what a Message Broker really is!
Explore the writing by topic.
Trade-offs behind the architecture decisions that hold up at scale.
APIs, services, and the logic running behind the scenes.
Indexes, storage engines, and query internals.
Cloud infrastructure, deployment, and running things in production.
Event streaming and asynchronous messaging.
Caching, distributed locks, and in-memory data.
Container orchestration, from Linux fundamentals up.
Deep dives on backend, databases, and infrastructure.
Let's see how the container solves the Virtual Machine's weight and boot-time problem by dropping the one thing a VM never gives up: its own private kernel.
With containers now scattered across dozens or hundreds of machines, who decides which one runs where, restarts it when it dies, or scales it up under load? That's the exact job Kubernetes was built for — let's map out what's actually inside a cluster.
Before getting anywhere near Kubernetes itself, the story has to start with the one piece of software everything else in this series is built on top of: the Linux kernel. If you've never really sat down and thought about what a kernel does, what a driver is, or what "sandbox" actually means in Linux, this article is for you.
What does a physical server actually look like, and why can't we just keep deploying more onto the same one?
Let's see how the Virtual Machine solves the physical server's "one machine, one environment" problem, and the downsides of this approach.
