Why Monolith Apps are Evil?

The title of this article is a bit of an exaggeration. Monoliths are evil and not so evil at the same time. How is that possible? Let's find out.

Every application starts simple, so monolith architecture is the right choice. When the project starts there is often very little information available, so the project should always start with the most straightforward approach. However, one thing to keep in mind is that the project is bound to grow with the introduction of more features. Therefore, the projects need to be architected with the ultimate goal of Microservices in mind.

Modular architecture design following the Single Responsibility Principle can help us achieve this goal. Boundaries between different classes and services need to be along functional aspects. Upon neglection of these principles, the once simple monolithic application eventually becomes a tangled spaghetti.

Organizations often focus on adopting the best agile processes and practices. However, after a while, they realize that engineers are still struggling with meeting deadlines. The rate of feature development and release is prolonged, what they fail to realize is that the application is suffering from monolith fever, therefore no matter what they do to improve the process they are only putting band-aids rather than fixing the core problem.

Monolithic applications have some advantages and disadvantages. However, its disadvantages are far more than the advantages when it comes to large and complex projects.

Monolithic applications are tightly coupled with the technology stack. Therefore as the time passes and the technology becomes obsolete, it is challenging to upgrade it to use the latest technology frameworks or even upgrade the version of an existing framework if the new version is not backward compatible. This necessitates a rewrite of the complete application from scratch using the latest tech stack.

Because of the obsolete technology, it is difficult to find talent and resources who are interested in working on the old tech stack. Often to work on those applications engineers have to learn old technologies which does not help them much in their career advancements. It is far easier to recruit engineers who want to learn and apply the most cutting edge technologies.

Monolithic applications are tough to scale; they often have one centralized database which is a single point of failure. If that database is down or struggling due to heavy load the only way to scale it without additional development work is to use more powerful hardware, i.e. vertical scaling. The nonresponsive database becomes a bottleneck and in turn, decommissions the whole application. To handle increased load more application instances can be launched and added to the Load Balancer.

Another major problem with monolith applications is that there is no way to use optimized hardware based on feature requirements. If one feature is memory intensive whereas another feature is computationally intensive, then the monolithic application is out of luck as it can only utilize general purpose hardware.

As monolithic applications tend to be large and complex their testing become very error-prone and challenging. Engineers are scared to make any significant refactorings because it becomes very time consuming and tedious to figure out all paths that are affected by the refactored code. This causes a ripple effect, creating more code debt.

Deployment cycle is yet another victim of Monolithic architecture. Since the application is hard to test, even a minor change in the application requires a complete retest. Testing takes longer, causing the deployment cycle to prolong.

As the code base of the monolith is quite extensive, the learning curve is pretty steep, which in turn affects the productivity of the whole team. No single engineer can become SME of the application.

Larger applications take a long time to build and start, thus development time and feedback cycle prolongs. Continuous integrations take a long time as well, and if the build fails, it becomes very time consuming to figure out the cause.

To avoid breaking the build, developers use the branching strategy to work on the features; this becomes very problematic when they merge their branches to the master branch. Merges are error-prone, so instead of helping, it hurts them instead.

If a nasty bug creeps in such as memory leak, it affects the whole application thus causing production outages and affecting customers.

So in short monolithic architecture violates all the requirements of the modern software application. i.e.

Maintainability

Extensibility

Testability

Scalability

Reliability

Releasability

Monolithic architecture is an excellent choice for small applications because they offer several advantages.

Monolithic applications can catch most of the bugs at compile time since they only have binary dependencies and no dependency on external services.

Monolithic applications are inherently more secure as the surface area for the attack is minimal and is centralized. So enforcing security is more natural.

The deployment procedure is very straight forward and only requires the deployment of one artifact across all instances.

For monolithic applications, setting up the development environment is very straight forward. Usually, only one code repository needs to be checked out, and IDE has access to all the code base of the application.

Debugging is easier in general, as the engineer can step through the code quickly without having to worry about external calls.

Transaction Management is very easy to implement in a monolithic architecture, since it is only dealing with a single database.

Testing monolithic application is simple, as there are no external dependencies to mock. Setting up the data required to run the test is straight forward as there is only one database involved.

To perform a similar task, monolithic architecture can be more performant as they only deal with local API calls, rather than making an over the network call to fetch the equivalent data. However, this advantage is at the cost of scalability.

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