The Real Talk on Microservices vs. Monoliths

Mohammad Abu Mattar
DevOps , Microservices , Monoliths
Published: 03 May, 2025
12 Mins read

The Tricky Side of Tiny Boxes: When Smaller Isn’t Always Better

So, microservices, right? They’re all the rage in the software world these days. Everyone’s buzzing about how they make things super flexible and let different parts of your app grow as much as they need to. And yeah, that sounds awesome when you hear it at a conference. But honestly, sometimes I think we get so caught up in the excitement that we forget to ask ourselves a pretty important question: “Hey, is this actually going to make our lives easier, or just… you know, more complicated?”

Think about it. You start with one big application – a monolith, as the fancy folks call it – that basically does everything in one place. Then, you chop it up into a bunch of little pieces, these microservices, that all have to talk to each other over the network. Suddenly, what used to be a simple chat inside one program turns into a bunch of phone calls between different programs. And you know how phone calls can go – dropped connections, misunderstandings, the whole shebang.

More Pieces, More Problems? Does Splitting Up Always Simplify?

One of the biggest things I’ve seen is that going from one big thing to a bunch of small things can actually make your life way more complicated. Instead of dealing with one application, you’ve got a whole bunch of them. That means you’ve got to worry about growing each one separately, making sure all their little doorways (they call ‘em APIs) are secure, keeping track of different versions of everything, and deploying all these little bits and pieces. It can feel like trying to herd cats, right?

And let’s not even get started on getting these little guys to talk to each other nicely. You make a change in one, and suddenly another one starts acting weird. It’s like trying to coordinate a bunch of musicians who are all playing their own songs at the same time. You need a really good conductor – or, you know, some serious coordination – to make sure it sounds like music and not just noise.

Testing becomes a whole new ballgame, too. Instead of just testing one big thing, you’ve got to test each little piece and how they all work together. That can mean setting up all sorts of special testing areas and spending a ton of time just making sure everything plays nice. And when something goes wrong? Forget about it. Trying to fix a problem that jumps across five different little services can feel like trying to find a single bad wire in a giant, tangled mess. You’re digging through logs from all over the place, trying to piece together what went wrong where.

Then there’s just the sheer number of moving parts. More services mean more servers, more network connections, more things that can potentially break. And managing all of that? It takes a lot more effort and can really add to your team’s workload. Plus, you’ve got to figure out how these services are going to talk to each other – are they using fancy REST calls? Maybe some other kind of messaging? Each way has its own quirks and can add its own layer of complexity.

And don’t even get me started on the people side of things. You might have different teams owning different microservices, which sounds great for independence, but it also means you need really clear rules about how these services interact. If teams aren’t on the same page, you can end up with a real mess of different technologies and ways of doing things, which just makes everything harder down the line.

Finally, let’s talk about the data. When you split up a monolith, you often end up splitting up your data too. Suddenly, information that used to be in one place is spread across multiple databases. Keeping everything consistent and making sure transactions work correctly across all these different places? That’s a serious headache and requires some pretty clever solutions.

Wait, Monoliths Aren’t All Bad? Why the “Old Way” Still Has Its Perks

You know, with all this talk about how great microservices are, it’s easy to forget that the “old way” – building monoliths – still has a lot going for it. For smaller projects, especially when you’re just starting out and have a small team, a monolith can be way simpler and faster to build. You’ve got one codebase, one place to deploy, and things are generally easier to understand. It’s like having all your tools in one toolbox instead of scattered across a whole workshop.

Getting a monolith up and running is usually pretty straightforward. You just deploy the whole thing to one place, and bam, you’re good to go. And when something goes wrong, you’re usually looking in one set of logs, in one environment. Makes fixing things a whole lot easier, especially when you’re not dealing with a bunch of network calls and different services.

Plus, sometimes a monolith can actually be faster. When different parts of your application need to talk to each other a lot, doing it within the same application is way quicker than sending requests over a network between different microservices. It’s like having a conversation with someone sitting next to you versus having to call them on the phone every time you need to say something.

And let’s be real, for applications that aren’t changing all the time or don’t need to handle massive amounts of traffic, a monolith can be perfectly fine. Why introduce all that extra complexity if you don’t really need it? It’s like buying a huge truck when all you need is a bicycle.

Amazon Prime Video’s Big U-Turn: Even the Big Guys Face Microservice Mayhem

The story of Amazon Prime Video is actually a really interesting one when it comes to microservices. You’d think a tech giant like that would have it all figured out, right? They started going big on microservices to handle their massive scale and make sure different parts of their video streaming service could grow independently.

But as they got bigger and bigger, they started running into some serious issues. All that back-and-forth communication between hundreds of tiny services started causing noticeable delays, even if it was just milliseconds. When you’ve got millions of people watching videos at the same time, even tiny delays can make a big difference in how smooth things feel. Managing all those services – keeping an eye on them, deploying updates, and figuring out what went wrong when something broke – became a huge headache.

And here’s the kicker: for one of their key services that analyzed video quality, they actually went back to a monolithic design! It turned out that the microservices approach they had used was costing them a fortune in cloud bills because of all the little interactions and data transfers. By putting it all back into one place, they managed to slash their AWS bill for that service by a whopping 90%!

Even though they were using fancy “serverless” microservices that were supposed to scale automatically, they still hit roadblocks in managing all the coordination. And for some of the really core parts of their system, like playing videos and recommending what to watch, they found that they needed things to be really tightly integrated, which was actually easier to achieve with a more together approach.

So, even Amazon Prime Video, with all their smart engineers and resources, realized that microservices aren’t always the golden ticket. They ended up going with a mix – using a monolith for some of the really critical, performance-sensitive stuff and keeping microservices for other things like billing and managing their content library. It just goes to show you that there’s no one-size-fits-all answer in tech.

The Sneaky Trap of Tech Debt: How Tiny Services Can Lead to Big Problems Later

You’d think breaking things down into smaller pieces would help you manage tech debt, right? In some ways, it can. But microservices can also create their own special brand of technical mess if you’re not careful. Because everyone’s doing their own thing in their little service, you can end up with different teams using totally different technologies, frameworks, and ways of coding. Over time, that can make it really hard for different parts of your system to work together smoothly and can lead to a lot of extra work when you need to make changes across multiple services.

If the communication between your microservices isn’t designed well, you can end up with services that are really tightly connected, even though they’re supposed to be independent. That means if you change one, you might break a bunch of others, which kind of defeats the whole purpose of having separate services in the first place. And if you don’t draw the lines between your services correctly, you can end up with either a million tiny services that are constantly chattering back and forth, or services that are still too big and clunky, just now they’re distributed.

Then there’s all the extra infrastructure and tooling you need for deploying, keeping an eye on, and scaling all these individual services. If you don’t invest in good tools and practices, that can become a huge source of tech debt down the road.

One of the worst things that can happen is what people call a “distributed monolith.” That’s when you have a bunch of microservices that are so tightly linked that they basically act like one big, clunky application, but with all the added headaches of network communication. You get all the downsides of a monolith and all the downsides of microservices – a real recipe for disaster! And because everything’s spread out, it can be harder to even realize you’ve got this problem and to clean it up. So, while microservices can help you manage tech debt in some ways, you’ve got to be really careful not to create a whole new set of problems.

The Give and Take: Weighing the Pros and Cons of Tiny Services

Choosing between microservices and monoliths really comes down to understanding the trade-offs. There’s no right or wrong answer that fits every situation. Each approach has its pluses and minuses, and you’ve got to figure out what’s most important for your specific project.

Feature	Monoliths	Microservices
Getting Started	Usually simpler and faster	Can be more complex to set up initially
Putting it Out There	Easier to deploy at first	Requires more coordination for multiple services
Dealing with Growth	Can be harder to scale specific parts	Easier to scale individual services as needed
Keeping Things Running	One failure can bring down everything	Problems in one service are less likely to affect others
Mixing Technologies	Usually stuck with one main tech stack	More freedom to use different tech for different services
Working Together	Easier for small, close-knit teams	Can enable more independent teams
Keeping Things Tidy	Can become harder to maintain as it grows	Easier to maintain smaller, focused services
Overall Complexity	Centralized, but can get messy over time	Distributed, requires careful planning and management
Initial Cost	Often lower to start	Can be higher due to infrastructure and tooling needs
Cost Over Time	Can become expensive to scale the whole thing	Costs can be more aligned with actual usage
Getting Features Out	Can be faster for simple apps	Can be faster for individual features once the system is set up

Basically, monoliths are often easier to get started with and deploy initially, especially for smaller teams and simpler applications. But as things grow and you need to handle more traffic or want to update different parts of your app independently, they can become a bottleneck. Microservices, on the other hand, can be great for scaling and letting different teams work independently, but they come with a lot more initial complexity in setting them up and managing all the different pieces. You get more flexibility in choosing technologies, but you also have to deal with the headaches of distributed systems. The cost can also be a factor – while a monolith might be cheaper to start, scaling it can become expensive, whereas microservices might have a higher initial cost but scale more efficiently in the long run. It’s all about finding the right balance for your specific situation.

So, When Should You Just Say “No Thanks” to Microservices?

A lot of folks jump on the microservices bandwagon without really thinking about whether it’s the right move for them. But there are definitely times when it’s better to just steer clear.

Honestly, dealing with all the extra overhead of microservices can really slow you down. You might spend more time managing the infrastructure and communication between services than actually building features. A monolithic approach is often much more manageable when you have fewer people.

You probably don’t need the extreme scalability that microservices offer. If you’re not expecting massive growth, the added complexity might not be worth it. A simpler setup can often handle moderate loads just fine.

Diving headfirst into microservices can be a recipe for disaster. There’s a lot to learn about how to design, build, deploy, and operate distributed applications, and making mistakes can be costly. It’s often better to start with something simpler and gradually evolve if needed.

For example, if you have a lot of tightly connected parts that always need to be deployed together, splitting them into separate services might just add unnecessary complexity without much benefit. And for quick little proof-of-concept projects, the overhead of setting up a microservices architecture is usually overkill.

It’s when you’re spending more time and effort managing the distributed system than you’re getting back in terms of scalability, flexibility, or resilience. If the complexity is slowing down your development, making your system less stable, or costing you a fortune without providing real advantages for your specific needs, then it’s probably time to reconsider.

Making the Smart Choice: How to Pick the Right Architecture for You

Choosing the right architecture is a big deal. It can set you up for success or lead to a world of pain down the road. Here are a few things to keep in mind when you’re making this decision:

For a lot of projects, especially when you’re just starting out, it makes sense to begin with a monolithic architecture. It’s simpler to understand and develop, and you can always break things down later if you really need to. Think of it as starting with a solid foundation.

A “modular monolith” can also be a really good middle ground. It’s still one application, but you design it in a way that different parts are really separate and don’t depend on each other too much. This can give you some of the flexibility of microservices without all the distributed complexity, and it can make it easier to split things out into separate services later if you need to.

It’s super important to pick an architecture that your team actually knows how to work with. If your team doesn’t have a lot of experience with distributed systems and cloud technologies, starting with a complex microservices setup is probably not a good idea.

Really think hard about how much your application needs to scale. If you’re not expecting massive growth, don’t over-engineer things from the start. You can always optimize for scale later if it becomes necessary.

Consider how complicated it will be to deploy and manage your application. Microservices require a lot more infrastructure and tooling, so make sure your team is ready for that.

If you do decide to go with microservices, make sure you clearly define the boundaries of each service based on what they do in the business. This helps avoid creating services that are too tightly connected or too small. And from day one, make sure you have good systems in place for monitoring and tracking what’s going on in all your services.

The bottom line is, don’t just jump on the microservices bandwagon because it’s the cool thing to do. Really think about your specific needs, your team’s skills, and the long-term goals for your application. Sometimes, the simpler path is the better path.

Wrapping Up: Choosing Your Tech Path Wisely

So, while microservices can be a powerful tool for building scalable and flexible applications, they’re definitely not a magic bullet. They come with a significant increase in complexity and can lead to a whole new set of challenges if you’re not careful. The experience of Amazon Prime Video shows us that even the biggest players can run into trouble and sometimes need to rethink their architecture.

It’s crucial to take a hard look at the potential downsides and really understand the trade-offs involved. For many applications, especially smaller ones or those with less demanding scaling needs, sticking with a monolithic approach or exploring a modular monolith might be the smarter and more efficient choice.

Ultimately, the best architectural decision is the one that aligns with your specific requirements, your team’s expertise, and your long-term goals. Don’t just follow the hype; choose wisely and build something that works for you.