Monolithic architectures are regaining popularity as companies struggle with microservices
Microservices were very popular at first, offering scalability and independence at a glance. In theory, they were supposed to break down bloated systems into manageable, flexible components, helping companies to move faster and smarter. But in practice? It’s been a bumpy ride for most.
Implementing microservices is no small feat. Organizations face hurdles like unclear domain boundaries, tangled inter-service dependencies, and the logistical nightmare of migrating data from an existing system. Companies like Amazon Prime Video, Invision, and Segment didn’t revert to monolithic systems out of nostalgia; they did it because sticking with microservices became more trouble than it was worth.
Monoliths might seem old-school, but they’re simpler and more predictable. When you strip away the buzzwords, what many businesses need isn’t complexity; it’s stability. Monoliths are proving their worth again because they work. And when your system just works, you’re in a better position to deliver for customers, innovate, and stay competitive.
Defining domain boundaries in microservices is a persistent challenge
Every microservices evangelist will tell you that the architecture depends on clear domain boundaries. Each service should be a neatly wrapped package, handling a full business domain with zero need for outside help. Sounds great on paper.
In practice, defining domains isn’t easy, especially in legacy systems where data and responsibilities are scattered across layers of logic and infrastructure. Without careful planning, you end up with overlapping domains that introduce chaos instead of clarity. Circular dependencies and excessive inter-service calls become common, turning what was supposed to be an efficient system into a performance nightmare.
Then there’s the human factor. When multiple teams need to manage overlapping domains, you get a mess of inefficiencies and endless back-and-forth discussions. The lack of clear ownership slows everything down and makes it hard to fix issues or ship updates. If the architecture doesn’t make sense to the people maintaining it, what hope does it have of staying functional?
Deep coupling of data and functionality complicates microservices transition
Most monoliths aren’t built to transition gracefully into microservices. Over years of operation, they develop deep interdependencies, data, logic, and even client applications become tightly interwoven. Breaking this apart is painstaking work.
Monolithic clients often bypass clean interfaces to hook directly into databases and business logic. So when you try to migrate to microservices, you’re rewriting the way clients interact with your system. That’s no small task. It demands refactoring, and in many cases, organizations simply stop midway, leaving parts of the monolith still intact.
This leads to fragmentation. Data gets duplicated across services and the monolith, creating redundant models that are difficult to keep consistent. Instead of solving problems, you end up introducing new ones, data integrity issues, unnecessary inter-service calls, and systems that are harder to debug. It’s no wonder many migrations stall out at this stage.
Data migration is a major barrier to adopting microservices
Moving data to a new architecture is risky, complex, and one misstep can bring everything crashing down. This is one of the toughest hurdles in shifting from a monolith to microservices.
The challenges are numerous. Data needs to move accurately and consistently, any loss or corruption can have cascading effects on operations. And if you’re dealing with large datasets, the sheer volume can bog down the migration process, tying up resources and extending timelines.
Then there’s the business continuity question. Customers don’t care that you’re migrating data; they expect continuous service. Balancing the need for uptime with the technical demands of migration is a high-wire act. And even after the data’s been transferred, rigorous testing and validation are required to make sure the system performs as expected.
It’s no surprise that many companies hit pause at this stage. The risks are high, and if you can’t guarantee a smooth transition, sticking with the old system often feels like the safer bet.
Microservices’ real-world implementation challenges outweigh their promised benefits
Microservices have been billed as the answer to modern software challenges, promising abstraction and modularity. In the real world, the promises don’t always hold up. The theoretical advantages are often overshadowed by the complexity and headaches of implementation.
Take partial migrations. Many companies start the process, only to get stuck in a limbo where half the system runs on microservices and the other half clings to the monolith. This hybrid state doesn’t deliver the efficiency or scalability microservices were supposed to provide. Instead, it introduces data integrity problems and makes system maintenance a chore.
Then there’s the problem of overlapping domains and dependencies. Instead of clean, independent modules, you end up with a web of services that are just as tightly coupled as the monolith they replaced. Performance suffers, reliability drops, and teams struggle to collaborate effectively.
This is why companies like Amazon Prime Video and Segment are stepping back. The operational difficulties of maintaining a microservices architecture often outweigh the benefits. Monoliths might not be trendy, but they’re reliable, and when you’re trying to serve millions of customers, reliability wins every time.
