What are microservices?

Microservices: What is it?

When building software, one of the most important decisions you'll face is how to structure your application. For years, the default approach was building everything as a single, unified system (a monolithic architecture). But as companies grew and applications became more and more complex, this approach started showing its limitations. That's where microservices architecture comes in.

TL;DR

• Microservices architecture breaks applications into small, independent services that each handle a specific business function
• Each service can use different technologies, scale independently, and be deployed without affecting other parts of the system
• Key benefits include team autonomy, fault isolation, easier maintenance, and the ability to scale specific components based on demand
• Challenges include increased operational complexity, distributed system management, and maintaining data consistency across services
• Best suited for large applications with multiple teams, varying scaling needs, and organizations ready to invest in the required infrastructure and expertise

The shift from monolithic thinking

Think about how a traditional monolithic web application works. Imagine an online store where everything lives in one place: user accounts, product listings, shopping carts, checkout, payments, and inventory management are all bundled together in a single codebase. In this monolithic setup, when you need to update the payment system, you have to redeploy the entire application. When the product search experiences high traffic, you have to scale everything, even the parts that don't need it.

With microservices, things are completely different. Instead of one large system, you build your application as a collection of small, focused services that work together. That same online store could be rebuilt, where each business function becomes its own independent service.

Breaking down what are the microservices

Each microservice in your architecture has a specific functionality. Your online store might be composed of separate services for user authentication, product catalogs, shopping carts, order processing, payments, and shipping logistics. Each one is a complete unit with its own codebase, its own database, and its own deployment schedule.

What makes a service truly a microservice? Several defining characteristics set this approach apart:

Each service deploys on its own schedule. For example, your payment team can ship updates every Tuesday without waiting for the product catalog team to finish their work. Or, when a bug appears in the search functionality, you can fix and redeploy just that service. The rest of your application keeps running on the previous version, unaffected by the new changes.

Teams choose their own technology stack. Each service can run on a different technology. The payment service might run on Java, while your analytics service uses Python. There's no need for company-wide standardization on a single language or database. You can pick what works best for each service’s unique requirements.

Services mirror how your business actually works. Instead of organizing code by technical function (all your database code here, all your API code there), you organize by business domain. Everything related to user profiles lives in one service; everything about order fulfillment lives in another.

Services communicate without tight dependencies. They communicate through well-defined interfaces, typically using REST APIs or message queues. The internal workings of each service remain hidden from the others. The payment service doesn't need to know how the inventory service stores its data. It just needs to know how to ask for inventory information when processing an order. This loose coupling between services gives developers a lot of flexibility, as they can completely rebuild how one part of the app works internally without affecting the others.

Real advantages in practice

The independence of microservices translates into real benefits for development teams. When one service faces a sudden spike in traffic (like a product catalog during a sale), you can scale just that specific service. You don’t have to pay to run extra instances of your entire application when only one part needs more resources.

Teams can work with true autonomy, meaning they can choose the technology, architecture, and deployment regardless of what other teams decide. Your payments team might choose to build its service in Java with a PostgreSQL database because it handles transactions reliably. Meanwhile, your recommendations team might use Python with MongoDB because it's better suited for the flexible data structures they need. Neither team is blocked by the other's choices.

With microservices, when something goes wrong, the impact stays contained. If your product review service experiences issues, customers can still browse products, add items to their carts, and complete purchases. You implement circuit breakers and fallback mechanisms to ensure that problems in one area don't cascade through your entire system.

Finally, for developers joining your team, there's a faster path to productivity. Instead of needing to understand a massive codebase before making changes, they can focus on one service that handles a specific business capability. The scope is manageable, the code is easier to test, and the feedback loop is shorter.

The challenges of Microservices

Adopting a microservices architecture doesn’t come without its own set of challenges. You're trading the complexity of a large monolithic application for the complexity of a distributed system. Network calls between services are slower than function calls within a single application, so they can fail in ways that local code doesn't. This is why you need strategies to handle timeouts, retries, and service outages gracefully.

Data management becomes more intricate. Each service typically has its own database, which means you can't rely on database transactions to keep everything consistent. You'll need to implement patterns like eventual consistency or distributed transactions, which will require careful thought and testing.

The operational burden also increases significantly. Instead of deploying one application, you're deploying dozens or potentially hundreds of services. While this is great for many reasons, it also demands investment in automation, containerization, orchestration platforms, comprehensive monitoring, centralized logging, and distributed tracing tools. Without these, managing a microservices system becomes overwhelming very quickly.

Testing grows more complex, too. You need strategies for testing individual services in isolation, testing how services interact with each other, and validating the behavior of your complete system. Mocking service dependencies, contract testing between services, and maintaining test environments all require additional effort.

Design patterns for microservices

Luckily, certain microservices design patterns, which are standardized and reusable solutions, have emerged to address these common challenges.

• The API Gateway pattern provides a single entry point for clients, handling request routing and aggregation.
• The Circuit Breaker pattern prevents cascading failures by stopping requests to services that are struggling.
• The Saga pattern manages distributed transactions across multiple services, ensuring data consistency even when operations span service boundaries.
• The Service Discovery pattern allows services to find each other dynamically as they scale up and down.
• The Event Sourcing pattern maintains a complete history of changes, making it easier to understand how your system reached its current state.

These design patterns in microservices aren't theoretical concepts but practical solutions that teams use every day to build reliable distributed systems, and understanding them can help you avoid common pitfalls.

Making the transition from monolith to microservices

Many organizations start with monolithic applications and later move to microservices as they grow. The transition from monolith to microservices is rarely a complete rewrite. Instead, teams typically extract services gradually, starting with boundaries that are clearly defined and loosely coupled.

You might begin by identifying a capability that changes frequently or has different scaling needs than the rest of your application. Extract that functionality into its own service while leaving the monolith intact. As you gain experience managing multiple services and build out your deployment infrastructure, you can extract additional services at a pace that makes sense for your team.

When microservices make sense

Microservices architecture is an excellent choice in certain situations. Large applications built by multiple teams benefit from the clear boundaries and autonomy that services provide. When different parts of your application have vastly different scaling requirements, the ability to scale those services independently becomes extremely valuable. Finally, organizations that prioritize fast iteration and want teams to move quickly without coordinating releases find microservices enabling.

However, microservices aren't always the right choice. Splitting into services for small applications built with a single team can feel unnecessarily complex. Similarly, startups trying to find product-market fit usually have a lot to gain from the speed and simplicity of a monolith. Likewise, teams without experience managing distributed systems will face a steep learning curve.

The decision about whether a microservices architecture is right for your organization depends on your specific context: team size, technical expertise, scaling needs, and organizational maturity. It's not about choosing the most modern or sophisticated architecture, but rather the one that best supports your goals while being realistic about the challenges you're ready to handle.

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