The microservices trap

“Let’s build it with microservices!” These words, often spoken with enthusiasm in early project meetings, can set teams down a path of unnecessary complexity that haunts them for years to come. While microservices architecture has its place, starting with it is usually premature optimization at its finest.

The siren call of modern architecture

It’s easy to understand the appeal of microservices. Tech blogs showcase beautiful architecture diagrams from Netflix and Uber. Conference talks highlight successful migrations from monoliths to microservices. Job postings emphasize experience with distributed systems. The message seems clear: modern applications should be built with microservices.

But this reasoning contains a crucial flaw. The companies often cited as microservices success stories didn’t start that way. They evolved their architecture as they faced specific scaling challenges. Their journey to microservices was a response to concrete problems, not an upfront architectural decision.

Understanding the hidden complexity

Let’s examine what building a “simple” e-commerce application with microservices really entails. At first glance, breaking the system into services might seem straightforward - you create separate services for user management, product catalog, shopping cart, order processing, payment handling, inventory management, and notifications.

But each of these services exists in a complex ecosystem. They need their own deployment pipelines, monitoring systems, error tracking, scaling policies, and databases. What used to be a single application now requires managing multiple deployment environments, monitoring dashboards, and database backup strategies.

The complexity doesn’t stop there. In a monolithic application, method calls are reliable and transactional. If something fails, you can roll back the entire operation. With microservices, every interaction becomes a network call that can fail in numerous ways. You need to implement retry logic, circuit breakers, and fallback mechanisms. You need to handle partial failures and implement compensating transactions.

Consider a seemingly simple operation like checking out a shopping cart. In a monolith, this might be a single database transaction. In a microservices architecture, it becomes a complex choreography involving multiple services that all need to succeed or fail together. You need to handle scenarios like: What happens if the payment service succeeds but the inventory service fails? How do you ensure the system remains consistent if the notification service is temporarily down?

Distributed systems are hard

One of the most significant complexities of microservices is data management. In a monolithic application, your data lives in a single database. Joins are simple, transactions are ACID-compliant, and data consistency is straightforward to maintain.

In a microservices world, each service typically owns its data. This means that data that naturally belongs together is now split across multiple databases. Want to display a user’s order history with product details? Now you need to join data across three different services. Want to run analytics on user purchasing patterns? You’ll need to implement a data synchronization mechanism or build a separate data warehouse.

This data distribution leads to complex questions: How do you maintain data consistency across services? How do you handle distributed transactions? How do you deal with eventual consistency? These are challenging problems that even experienced teams struggle with.

An operational nightmare

The operational complexity of microservices cannot be overstated. Instead of monitoring one application, you’re now monitoring a distributed system. Problems that were once straightforward to debug now require correlating logs across multiple services. A single request might traverse several services, making it difficult to track down performance issues or errors.

You also need to handle service discovery, load balancing, and network partitioning. Each service needs its own scaling policies. You need to implement sophisticated monitoring to understand the health of your system. The operational overhead multiplies with each new service you add.

The development complexity tax

The day-to-day experience of developing a microservices-based application comes with its own set of challenges. What used to be a simple local development environment now requires running multiple services, each with its own dependencies. Developers need to understand and maintain multiple codebases, each potentially using different technologies and frameworks.

Testing becomes particularly challenging. Unit tests are still straightforward, but integration testing now requires spinning up multiple services and their dependencies. End-to-end testing becomes even more complex, requiring careful orchestration of test data across multiple services. A simple feature that touches multiple services requires coordinating changes across multiple repositories, potentially involving multiple teams.

Consider this common scenario: a developer needs to add a new field to display on the order history page. In a monolith, this might be a single database migration and a few lines of code. In a microservices architecture, they might need to:

• Add the field to the orders service database
• Update the orders service API
• Update the API client library used by other services
• Deploy the updated client library to all dependent services
• Coordinate the deployment order to maintain backward compatibility
• Update the front-end code to display the new field

What should be a simple task becomes a complex coordination effort.

When microservices actually make sense

Despite these challenges, there are legitimate reasons to adopt a microservices architecture. The key is recognizing when these reasons apply to your situation.

Microservices make sense when you have clear boundaries between different parts of your system that rarely change together. They work well when different components of your system have vastly different scaling needs - perhaps your authentication service needs to handle thousands of requests per second, while your reporting service only handles a few dozen.

They become valuable when your engineering organization has grown to the point where team coordination is a significant bottleneck. When you have multiple teams that need to work independently and deploy their code on different schedules, microservices can provide the necessary autonomy.

Large-scale systems that need to handle millions of users across multiple regions might benefit from the ability to deploy and scale services independently. Companies dealing with strict regulatory requirements might need to isolate certain components of their system for compliance reasons.

Start with a monolith

Instead of starting with microservices, consider beginning with a well-structured monolith. This doesn’t mean creating a big ball of mud - it means building a modular application with clear boundaries between different components. These boundaries might eventually become service boundaries, but they start as module boundaries within a single application.

The key is to focus on good design principles: proper separation of concerns, well-defined interfaces between modules, and careful management of dependencies. A well-structured monolith can give you many of the benefits of microservices (modularity, separate concerns, team ownership) without the distributed systems complexity.

As your application grows and you identify specific scaling or organizational challenges, you can begin extracting services. This extraction should be driven by concrete needs rather than abstract principles. Perhaps your image processing module is consuming too many resources and needs to scale independently - that’s a good candidate for extraction. Maybe your payment processing needs to be isolated for security reasons - another good candidate.

The art of timely architectural decisions

The path to a sustainable architecture starts with understanding your actual needs rather than anticipated ones. This aligns with the concept of the “Last Responsible Moment” - a principle from lean software development that suggests delaying important decisions until you have the most information possible, but not so long that you miss your window of opportunity. Begin by identifying the core domain problems you’re trying to solve. Focus on building a clean, modular codebase that reflects your domain boundaries. These boundaries will guide future architectural decisions.

Keep your architecture decision-making grounded in reality rather than theory. The Last Responsible Moment for adopting microservices isn’t when you think you might need them - it’s when you have concrete evidence that your current architecture is causing specific, measurable problems. When you feel the pain of a monolithic architecture through concrete problems like scaling bottlenecks or team coordination issues, that’s your signal that the responsible moment for change has arrived.

Remember that many of the problems microservices solve can be addressed through other means. Team autonomy can be achieved through well-defined module boundaries. Scaling challenges can often be solved through careful optimization or horizontal scaling of your monolith. Independent deployability can be achieved through feature toggles and careful interface design. By waiting for the Last Responsible Moment, you ensure these simpler solutions get fair consideration before jumping to more complex alternatives.

The goal isn’t to avoid microservices forever - it’s to make architectural decisions at the optimal time, with the maximum amount of information available. This approach helps you avoid premature complexity while preserving your ability to evolve your architecture as needed. Start simple, stay focused on your actual problems, and let your architecture grow with your needs, making each significant architectural decision only when you truly must.

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Is your team facing architectural decisions about microservices? We understand the challenges of balancing system complexity with future scalability needs. Our experience helping organizations navigate these transitions - both toward and away from microservices - has taught us that each situation is unique and deserves careful consideration. Whether you’re evaluating a potential microservices migration, struggling with a distributed system’s complexity, or looking to simplify your architecture, let’s discuss sustainable solutions that match your team’s current needs and capabilities. Reach out to us through our contact form or send us an email at contact [at] asyncsource.com. We’d love to help you build an architecture that grows with your business without unnecessary complexity.