3.1 Introduction to Microservices Architecture

Learning Goal:
• Understand why and how microservices architectures differ from monolithic designs.

Detailed Content:
• Monolithic vs microservices: pros and cons
• Key features of microservices: independent deployment, scalability
• Domain Driven Design (DDD) basics for service separation
• Common pitfalls in real companies
• Light case study: migration path from monolith to microservices

3.1.1 Monolithic vs Microservices: Pros and Cons

When teams first build an application, they often start with a monolithic architecture. In a monolithic design, all the system’s features—user interfaces, business logic, and data access—are packaged into a single deployable unit. This approach is simple to get started with: it’s easy to develop, test, and deploy as one piece. For small teams or early-stage products, monoliths can be the fastest way to launch and iterate.

However, as the system grows, monoliths often become harder to maintain. A single change in one module can affect many unrelated parts. Deployment becomes risky because a tiny bug in one corner can crash the whole application. Scaling is also all-or-nothing: you can’t just scale the part that’s under heavy load—like payment processing—without scaling the entire system.

This is where microservices architecture comes in. Instead of building one big application, you split the system into many small, independent services. Each service runs in its own process, owns its own data, and handles a specific business capability—like user management, order processing, or email notifications.

This design solves many headaches of monoliths. Microservices can be deployed independently. Teams can choose the best tech stack for each service. Services scale individually: if the product search service is getting hammered, you can scale just that one up without touching the rest. This architecture brings flexibility, resilience, and the freedom to evolve parts of the system without breaking everything else.

Of course, microservices are not free. They add operational complexity. You now have to manage networking, service discovery, distributed logging, and data consistency across boundaries. For a small team or a simple product, jumping into microservices too early can slow you down rather than help.

3.1.2 Key Features of Microservices: Independent Deployment and Scalability

Two characteristics define microservices above all else: independent deployment and independent scalability.

Independent deployment means each microservice can be updated, redeployed, and rolled back without affecting other services. If the payment team fixes a bug, they don’t have to coordinate a full-system redeploy with the user profile team. This independence allows teams to move faster and reduces the blast radius of changes.

Independent scalability means each service can scale horizontally or vertically based on its own load. For example, a video streaming service might need dozens of instances to handle massive traffic, while a billing service may only need two replicas. This fine-grained scaling can lead to significant infrastructure cost savings.

These benefits make microservices well-suited for large applications with diverse workloads and fast-changing business requirements. But achieving true independence requires strict boundaries—services should not share databases directly or rely on hidden couplings, or else the whole system reverts to a “distributed monolith,” which is the worst of both worlds.

3.1.3 Domain-Driven Design (DDD) Basics for Service Separation

A big question when adopting microservices is: How do you decide what goes where? This is where Domain-Driven Design (DDD) comes in. DDD helps teams break down complex business domains into smaller, more manageable bounded contexts.

Each bounded context represents a clear area of the business with its own models, rules, and language. For example, in an e-commerce company, “Customer Account” might be one bounded context, “Inventory” another, and “Payment Processing” yet another. Each of these can naturally map to a separate microservice.

DDD encourages teams to speak the same language as the business—avoiding generic, bloated modules. This leads to cleaner ownership, fewer interdependencies, and more natural service boundaries. Many real-world microservices failures stem from ignoring domain boundaries and splitting services arbitrarily, which only shifts complexity from code to inter-service communication.

3.1.4 Common Pitfalls in Real Companies

While microservices promise flexibility, they bring new challenges that catch many companies by surprise. One common pitfall is underestimating the cost of distributed systems: once you have dozens of services, you must manage inter-service communication, handle partial failures, ensure secure data exchange, and maintain observability across the entire network.

Another classic trap is poor service boundaries. If services are too small and chatty, network overhead kills performance. If they are too large and tightly coupled, you end up with a distributed monolith, losing the benefits of microservices while gaining the operational headaches.

Organizations also struggle when team responsibilities don’t align with service ownership. Conway’s Law tells us that systems mirror the communication structures of the teams that build them. If you split services without matching your team structure, you get constant coordination pain, unclear ownership, and duplicate logic scattered everywhere.

3.1.5 Light Case Study: Migration Path from Monolith to Microservices

Many companies don’t start with microservices—they migrate to them when the monolith’s limits become painful. A typical migration begins by identifying natural seams in the monolith. For example, an e-commerce company might start by carving out its payment processing as a separate service, since payments can naturally operate on clear API contracts.

The team would extract the payment logic into its own repository, create REST or gRPC APIs for communication, and deploy it independently. The monolith continues to handle the rest of the system but calls the new payment service when needed.

Gradually, more modules—such as order management or notifications—can be peeled off, tested in isolation, and deployed as their own services. This incremental approach reduces risk and allows the organization to learn new DevOps, CI/CD, and monitoring practices step by step, rather than in a big-bang rewrite.

Teams that succeed with microservices respect domain boundaries, automate deployments, monitor deeply, and keep services as decoupled as possible. Done well, microservices turn scaling headaches into a powerful advantage—letting teams evolve fast, release often, and build systems that keep up with complex, changing markets.