Microservices Architecture vs Monolithic

Microservices is a tool that does work at a high scale, but there are also projects that don’t benefit from them at all. So whether to use them over monolith has to be made on a case-by-case basis. I’ve distilled years of expertise of our team in this post to help you understand what your project truly requires.

When Businesses Choose Microservices Architecture

Enterprise Platforms

Imagine you're building a complex e-commerce platform or an ERP with many different parts. Instead of sticking to one tech stack for everything, you'd want to pick and choose based on what works best for each part.

Take the e-commerce platform, for instance. You might go with React because it's slick and responsive. Then, when you're setting up the Product Catalog, a relational database like PostgreSQL makes sense because it's great with structured data. And for Reviews and Ratings, you choose a NoSQL database, like Cassandra, to handle all user comments coming in.

So, with microservices architecture, you're not just locked into one tech. You can mix and match, making sure each piece of the platform gets the best tech for its needs. It's all about flexibility and optimizing performance.

Projects requiring rapid deployment of updates and new features

One of the best things about microservices architecture is how it speeds up delivery. Because everything's modular, teams can work on different bits at the same time without stepping on each other's toes. If you need an update, just roll it out without a system-wide overhaul. And with tools like CI/CD and Kubernetes, it's always ready to evolve.

Plus, the setup gives us, the developers, room to try new things without the whole setup coming crashing down.

Services requiring 100% availability

Think about e-commerce sites or banks where uptime is pretty much everything. If they're down even for a bit, it's not just money they lose but also trust.

In such sectors, opting for a microservices setup really makes sense. The trick is that each service runs on its own, doing its own tasks. So if one faces an issue, the others don't get dragged down with it. This approach not only keeps systems more available but also builds in a good layer of fault tolerance.

SaaS apps and cloud-based systems with fluctuating workloads

Microservices really shine in cloud environments. You can tap into cloud scalability and serverless computing. Instead of paying for a chunk of computing capacity, you're only billed for what your code actually uses.

To name a few examples, startups and SaaS platforms are saving a lot by only shelling out for real resource usage. E-commerce sites are using microservices architecture to gracefully handle traffic spikes during sales. And IoT apps can easily scale with all that data pouring in.

Highly scalable applications

If you're developing an app with varying traffic expectations across its components, I'd recommend the microservices architecture. You can scale each service separately based on its load, which is pretty efficient resource-wise. It could save some costs and boost performance.

And with the tools we have now, scaling's a breeze. Really helps for apps that need to adapt on the fly.

Apps offering personalized UX and customization

If a business wants to really tailor its services for users, microservices are the way to go. They let you dial in the exact experience you want for different user groups.

E-commerce platforms, like Amazon, use microservices for tailored shopping experiences based on user behavior. Fintech firms, such as Stripe, offer custom financial solutions leveraging microservices' flexibility. Learning platforms like Coursera provide personalized course recommendations, while healthcare apps deliver patient-centric services.

Real-Life Business Case: When Scalability and Modularity of Microservices Shine

It seems like microservices are the secret sauce for businesses wanting to be agile and scale with ease, especially when we talk cloud-native and serverless setups.

The healthcare startup from the US wanted to tackle some pretty complex industry demands: staying always up, keeping patient data safe, and juggling tons of data efficiently. So Belitsoft stepped in to help.

• Microservices & AWS Pairing. Belitsoft combined these two powerful technologies, particularly AWS Lambda's serverless SaaS structure, making the most out of AWS's rock-solid security and microservices' modularity. The result is perfect auto-scaling.
• Data Privacy Boost. A central feature of the solution was the SaaS multi-tenant architecture, rooted in microservices. This design guaranteed that data for each tenant remained fully secure and isolated, enhancing data privacy.
• Ace User Management & Security. Microservices also played a crucial role in user management and access control. Integration with AWS Cognito and the Amazon API Gateway streamlined user identity verification and request routing, fortifying the application's security.
• Efficient Data Handling. We set up a dynamic ETL pipeline using AWS Glue, AWS SQS, and Apache Spark. After processing all that data, AWS QuickSight turned this data, utilizing pre-established dashboard frameworks, into visuals that anyone could get.

By using the full potential of both microservices and AWS, Belitsoft gave this startup just what they needed: agility, security, and the ability to scale. It's a great example of how microservices can really make a difference, especially in sectors like healthcare.

Challenges of Using Microservices Architecture [with Solutions]

• Data Consistency. When each service has its own database, things can get complex. It's not just about the decentralized setup. You've got to deal with challenges like syncing up distributed transactions, getting used to the idea that consistency might take a moment ("eventual consistency"), and then there's the potential for sync conflicts.
• Network Latency. With microservices being spread out, there's naturally some lag when services chat with each other. It's even more noticeable when we're changing data formats or chaining calls together. And let's not forget, things like finding the right service or balancing the load add a bit more to that delay.
• Service Orchestration.We've got to make sure they're all in sync, manage how data moves between them, keep an eye on their mutual ties, and ensure they all perform well together, especially when multiple operations are happening at once.
• Increased Operational Overhead. Each distinct service may have unique resource needs. So setting up and managing them can be a handful. We have to deal with scaling challenges, making sure one service doesn't trip over another, and ensuring they don't hog resources.
• Security Concerns. Multiple distinct services communicate over a network. With more services connected, there's a higher chance someone unwanted could sneak in. If we're passing data between services, we've got to make sure it's secure, so encryption is key. Diverse technology stacks used for different services and reliance on third-party services or APIs can further expose the system to risks.
• Vendor Lock-in and Integration Challenges. When we talk about vendor lock-in for microservices, It's like we get too comfy with one tool or platform, and suddenly it's super hard to switch or adapt. This can mean more costs, less room to try new stuff, a real headache if we want to migrate, and a challenge to plug in new tech or change between techs.
• Overhead Costs. Breaking up apps into separate services is great for flexibility and scaling up, but it comes with some cost challenges. Think about the specific infrastructure we need, plus all the monitoring and deployment tools. And with all services communicating to each other, especially in the cloud, the network traffic and making sure everything's always available can add up. Not to mention, with all that complexity, we often have to shell out for pricier management tools. And, of course, keeping all those services secure.

When Businesses Choose Monolithic Architecture

Businesses with a tight initial budget

If you're watching your budget closely, looking for a straightforward development and deployment process, I think going monolithic could be a smart move. With a monolithic setup, we're looking at one unified codebase, which honestly, can make our dev life a lot simpler. We can use specific IDEs meant for monoliths, and they'll gel nicely. Testing is also way smoother. With everything in one place, we don't have to deal with those pesky inter-service hiccups.

Now, deployment-wise, it's a dream for anyone counting costs. Just one server to worry about, which means less networking mess and more efficient use of memory and CPU. Plus, tools like Docker can help us containerize the whole thing with ease. So, from a cost perspective, it seems like a pretty solid route.

Startups launching a quick MVP

Monolithic architectures are like an all-in-one package, a one-stop-shop. We're talking about one unified space for development, thanks to its single codebase. This alone can save a ton of time because there's no headache of managing communication between different services. So, if you're a startup aiming for a speedy MVP release, this is golden.

Now, when it comes to testing and deployment, everything's in one place, meaning we don't have to fumble around simulating various external APIs. It's just simpler and faster. And if there's a surge in user traffic initially, monoliths can directly scale up to handle that.

Software handling critical data

When you're dealing with critical data, say financial transactions in a bank or patient health records in healthcare, consistency is paramount. With monolith where everything is in one place, data's consistent and there aren't too many entry and exit points for security threats. Consider also audits and compliance; it's way simpler with this setup. I get the whole advantage that flexibility and scalability of microservices bring, but when it's about keeping data tight and right, I'd lean towards a monolithic system. Makes sense for those ultra-sensitive data scenarios.

Real-Life Business Case: Reducing Costs by 90% with Monolithic Architecture

Using the monolithic architecture, Prime Video's Audio-Video Monitoring Service showcased the strength of a unified codebase of the monolithic architecture, complemented by specific tools and practices. Here's how:

• Simplicity in Deployment & Scaling. They used Docker for smooth containerization, making sure the app's environment was the same from start to finish. Add Jenkins to the mix for faster integration and deployment. Regular code check-ins and a modular approach made the entire codebase neat and easy to handle.
• Consistent & Unified Data Management. They hinged on PostgreSQL for rock-solid data storage. And for quick data access, Memcached was their go-to. With routine database tune-ups, they ensured the data was always spot on.
• Cost Efficiency. AWS EC2 was their cloud of choice, dynamically allocating resources and cutting costs by a whopping 90%! Monitoring how much they used and smart logging made sure no resources went to waste.
• Enhanced Reliability. Tools like Nagios and Grafana kept a watchful eye on app performance, spotting any hiccups ASAP. Throw in solid backup plans and rigorous tests, and you've got a system you can count on.
• Streamlined Development & Maintenance. They took advantage of IntelliJ IDEA and Git to make development smooth. SonarQube came into play for quality checks.

So, it's clear that Prime Video's service wasn't just about choosing monolithic; it was all about the right tools and best practices backing it up.

Why Not to Choose Monolithic Architecture

Restricted Scalability

In monolithic architecture, having everything in one big box can be a bit of a pain when we want to scale. Let's say one part of our app gets a ton of traffic - in a monolith, this means we'd have to scale up the whole thing, which isn't really efficient and can get pretty pricey. Plus, even small updates require us to touch the entire system, risking more downtime. And as we keep adding new features to it, the entire structure just gets more and more complicated to handle. Sure, we can try to scale it vertically, but there's only so much you can do before hitting hardware limits.

Limited Flexibility

Sticking to one tech stack can make it tough to keep up with the latest and greatest in the tech world. Plus, imagine if our stack becomes outdated or goes niche, finding people who know it inside out can become a real challenge. One more challenge is optimizing individual parts of the app. Another pain point is getting too attached to one vendor. It can back us into a corner with costs and limitations, and if we ever think of switching things up, it's going to be a major headache, both in effort and cost.

Large Codebase

With monolithic architecture, as they grow, things can get a bit tangled up in the codebase. Quick fixes pile up over time as technical debt. Then, making any change as well as testing becomes a minefield because of all the interdependencies. Plus, every time we push an update, we're often looking at redeploying the whole thing, which means possible downtimes. All this just puts a drag on being innovative and quick on our feet.

Single Point of Failure

In monolithic architecture, everything's interconnected. So, if an issue arises in one part, it can potentially disrupt the entire system. Unlike models where components are isolated, in a monolith, a problem isn't contained. So, a minor glitch can escalate, causing widespread disruptions. This interconnectedness poses risks to system stability and can have business implications.

Obsolescence

Monoliths are great for starting out simple, but over time, they might get left behind. We could face issues like less support and fewer updates. It's something to think about if we want to stay competitive.

Resource-intensive

Unlike microservices where you can just scale the bit that's busy, with a monolithic architecture, we have to scale the whole thing. That can be a bit wasteful, using more resources and probably costing more, especially when only a part of the app is under heavy load. It's like upgrading an entire train instead of just adding an extra carriage.

In addition, having all bundled up together in monolithic systems can make it a real headache for any newbies joining the team. Technically, they've got to wrap their heads around this intertwined codebase and all the tools we've tailored for our monolith. But from the business side of things, it's also tricky. Longer onboarding means more training costs. Plus, if they make a mistake, given how everything's connected, it could mess up a chunk of the system, delaying our releases. That's not great for staying ahead of the competition.

Can You Mix Both Or Migrate Between Microservices and Monolith?

I was mulling over Amazon's strategy (switching from microservices to monolith) and noticed an interesting trend. They're blending the classic monolithic architecture with contemporary tech tools, a blend of tradition with modernity.

Historically, monolithic architecture presented certain challenges - mainly scalability and maintainability. But with tools like Docker, CI/CD pipelines, Prometheus, and Grafana, monoliths are getting a substantial makeover, effectively addressing many of the old concerns tied to monoliths.

Can you migrate between them?

Yes. However, migrating from monolith to microservices may be complex. And this is why.

Conceptually, picture a monolithic architecture as a tightly-knit fabric. Every thread is interconnected, meaning a tug on one could affect the whole cloth. On the flip side, microservices are more like individual patches. Each has its unique role but remains independent. Transitioning from monolithic to microservices is akin to segmenting this fabric into distinct patches - offering flexibility and scalability.

Yet, shifting in the opposite direction, consolidating microservices into a monolith, is much more straightforward and can help streamline overlapping functionalities.

And what about using them both?

The middle ground is the hybrid model, a fusion of monolith and microservices. It harnesses the strength of a unified structure while reaping the benefits of modular adaptability.

To wrap up, it's entirely possible and, in many cases, advantageous to blend, transition, or even merge both architectural styles, depending on the project's needs and long-term vision.

Still on the fence about monolith vs. microservices? Reach out to our team! We'll help you navigate the best path tailored to your project.