Monolithic Vs. Microservices Architecture: Modernizing Monolithic Apps and Databases for the Cloud

monolithic vs microservices architecture
Bob Quillin April 27, 2022

If your company has been in business for a decade or more with a custom application, there’s a high chance that the application’s architecture is obsolete. Ten years ago, monolithic vs. microservices architecture for business apps wasn’t much of a discussion: monolithic applications seemed to still be working well, and most IT professionals knew how to manage and maintain them, despite longer development and release cycles.

However, times have changed. These days, many existing business apps are built with code and frameworks that less experienced workers in IT don’t know how to use, and these monolithic applications have been patched numerous times. 

Additionally, keeping old equipment around the office is getting very expensive. Staff time is precious, and the time of staff who use the aging technology stack is even more valuable.

What’s the solution? For many companies, it’s refactoring the monolithic application to create microservices and migrating it to the cloud. In this article, we’ll discuss how refactoring and migrating work.

Monolithic vs. Microservices Architecture

Deciding how to modernize your legacy applications requires you to first understand the difference between monolithic and microservices architecture. Both the architectures operate differently and are designed to work in very different operating conditions.

Monolithic Architecture

Monolithic applications are the ones that are completely self-contained and don’t depend on anything else but hardware. Monoliths have everything inside of them: coding for each function, a database, user accounts, and more.

What’s the problem with monolithic architecture? Besides the fact that many are written using outdated language versions, frameworks, and best practices, they are less stable than the alternative. Because everything in a monolithic application is tightly-coupled and interdependent, if something goes wrong with one part of the application, the entire system can stop functioning.

Remember the old, “our systems are down, we can’t work right now?” Yes, that’s the monolith.

Microservices Architecture

Microservices are best described as a cluster of apps or services where each one operates independently and work together through an application programming interface (API). Each microservice is isolated and performs a specific action based on its own data sources. Microservices work together to perform a range of tasks.

Think of this as an application assembly line. In a factory for mechanical items, one person on the assembly line sits with a pile of the same parts. As they receive an unfinished product unit, this person adds their designated “contribution” to it. 

So for a car, one person puts the axles on the chassis, another fits the steering wheel, and so on. All workers on the line collaborate to get the car assembled, but they essentially work independently.

The best part? Microservices architecture is both efficient and stable. API communication between microservices is typically seamless. In addition, if one microservice goes down, it doesn’t impact other functionalities.

Related: 7 Approaches to Legacy Java Modernization for Architects

Microservices Are the Best Cloud-Native Architecture Option

Microservices are likely your best option when modernizing a monolithic application for the cloud. For one thing, they’re comparatively lightweight: each microservice uses fewer resources than a large monolith, and because they are loosely coupled and distributed, it’s possible to scale particular services up and out with less complexity. 

Another reason why microservices are the way to go: the overall architecture was designed for the cloud. When you consider monolithic vs. microservices architecture, you have to think in terms of monolithic programs being the default option from before the internet: while communicating within a computer program was always possible, old technology didn’t allow for programs to communicate with each other. 

Therefore, programs had to have access to all the data they needed without asking another program for help. In the internet age, IT departments moved to make the program run on servers, which are ”consulted” by individual workstations. The monolith, however, remains intact.

On the other hand, microservices are designed to talk to each other in a cloud computing environment. Each microservice performs its individual task, then passes it to the next one. 

Alternately, the one microservice gets specific information from another microservice that encapsulates the database. This way, the other microservices don’t get slowed down by a single point of contention at the data layer. In other words, microservices architecture works through communication between processes to produce the desired result.

Related: Monolithic Applications vs Microservices

How Can You Migrate Your Monolithic Applications to the Cloud Using Microservices?

In a nutshell, creating microservices from your legacy application and then having them run in the cloud provides the best results. There are several steps along the way: analyzing your monolith to determine what parts best go together, breaking down the database, writing the microservices along with testing, and migrating everything left to the cloud.


Before you begin, you’ll need to identify logical domains and individual services in your code base. A service in this case is a basic function. For instance, on an e-commerce website, you’ll find a shopping cart, inventory database, and payment service. 

Each of these functions work together in a monolithic app. With microservices, however, each of these processes would work separately, but consult each other when needed. So, the cart would talk to the payment service during checkout, and then tell inventory to deduct the items purchased.

Breaking Down the Database

Next, you’ll need to break down the database.  For instance, in the typical database, you can search for information based on the dataset. To break down, or refactor, your monolith into microservices, you’ll assign the data to whichever service uses it. 

This breaks up your monolithic database, makes the original data part of your refactored microservices, and lets the microservice use the data it needs without waiting for other services.

In practice, assigning data as part of your refactoring project means that the microservices, like the monolith, are largely autonomous. However, in monolithic vs. microservices architecture the size of your programs (or apps) are different. For the refactoring to be successful, you need to ensure that the right data is assigned to the right microservice. 

Performing careful analysis before breaking down the database allows for proper functioning. If you fail to refactor your tasks and database properly, then there will be errors and performance issues.

Writing and Testing Microservices

Once you know the best way to divide the monolith, it’s time to write the new microservices. Writing new programs is time-consuming and costly, so it’s important to do it right. Perhaps most importantly, you’ll need to select technologies that are both current and commonly known so that most IT staff will know how to fix them later. Google gives some programming tips, including ideal tools for refactoring.

As you write the new microservices, you’ll need to test each one. In this case, you’re looking for more than bugs. Rather, you’re making sure that the transition is successful to ensure overall functionality is preserved without sacrificing speed. 

At the same time, you will need to determine which functions should be transitioned first to ensure your business continues to operate smoothly.

Finally, Google recommends that you only transition a few functions at a time. This helps on several fronts. First, it helps you spread out the expense of the transition, both in terms of staff hours and other resources, such as cloud space. Second, spacing the factoring out over time allows you to make adjustments as you go while ensuring optimal business functioning.

What Should Be Migrated to the Cloud?

While most companies can refactor their monoliths into microservices, some companies may need to keep some or all of their data on an in-house server. 

Although the cloud is very secure (Google and AWS have some of the best security in the world), some industries such as Banking and Healthcare require restricted information access. This depends on the regulations of the countries where you have customers, your industry, and special considerations for certain customers.

Let’s look at an example. Most of us trust our banks–and for a good reason–they don’t get hacked very often. The same thing goes with doctors and other professionals that handle highly confidential information. In some cases, information is too sensitive to be stored in the cloud. For those datasets, you should keep a traditional server. Then, you can architect your microservices to consult that database as needed.

Alternatively, companies in these industries can choose a private cloud option or implement special access controls. However, if these other options are impractical for a particular company, the monolithic vs. microservices architecture debate can tip in favor of the monolith.

Choose Your Cloud Provider, Then Migrate

Once you’ve decided which datasets can be migrated, it’s time to start the process. Your first step is to determine which cloud service or services you can use, then decide how much infrastructure you need. 

When it comes time to perform the migration, use the tools provided or recommended by your provider. Experts recommend that you put safeguards in place to ensure that your business isn’t disrupted during the migration process. In addition, you should keep a copy of the original data in case something goes wrong.

vFunction: Break the Monolith More Easily

As you can see, the monolithic vs microservices architecture shift isn’t always easy. However, the hardest part may arguably be deciding which functions and data go where. Once these decisions have been made, you only need to write the new microservices. Luckily, with vFunction, analyzing your monolith and accompanying databases can be done easily. The program crawls your code, then gives you an automatic map you can turn into an actionable microservices plan. This takes a fraction of the time and money of manual analysis. What are you waiting for? Request a demonstration today.