This negatively affected how quickly the monolith application could serve a user request. As more users used an application, the demand for the host machine’s compute resources equally increased.Īs users interacted with an application even more, developers realized that the host machine was being pushed to its limit. A monolithic application with a separate databaseĮven with that, they noticed that just moving the database to a separate machine wasn’t enough. To solve that, developers figured it’d be great if the application and its database could be hosted on different machines. The database quickly became a resource hog, eating up the server’s memory and compute power. Limitations of the monolithic architectureįirst, with the increasing number of users, developers realized that having an application and its database hosted on the same machine wasn’t great. Over time, as more and more people embraced the internet, these monolith applications began to experience an explosion in the number of their users - a good thing, right? But this unmasked some limitations of the monolithic architecture. Illustration of a monolithic style of architecture You would bundle all these components, and the application’s database, into a tightly-coupled unit that’s deployed as one application - a monolith. As a result, they were developed and deployed as a unit that runs on a single process.įor example, let's say you were working on an application that does authentication, processes orders, and, eventually, handles payments. In the early days, software systems were relatively simple and small. Note: for brevity’s sake, this article will interchangeably use the term distributed systems and microservices. To begin, let’s look at the evolution from monoliths to distributed systems. This article will cover what they are and, more importantly, explore the link between message queues and distributed systems. Synchronous, asynchronous, message queues, distributed systems - what are all these terms? And, more importantly, how this can help us realize a more reliable and scalable architecture. We can put these different communication patterns into two broad categories: synchronous and asynchronous modes of communication.īut more relevant to this article would be exploring how we can use message queues to implement asynchronous communication in a distributed system. This also means that coordinating and managing communication between smaller services has gotten more complex.īut different ways of allowing the services in a distributed architecture to communicate have evolved over the years. There's an even greater need to allow computers to communicate with the increasing adoption of distributed architecture. From town criers to written letters and now real-time chat applications, humanity has always been on the lookout for innovative ways to communicate.
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