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Web Development Patterns – Microservices or Monoliths

by Craig Fraser
Published on: 2/28/2024

Microservices have become a popular architectural pattern in web development, with many developers and organizations adopting this approach to build and deploy applications. In this blog post, we will explore microservices in-depth, discussing their benefits, drawbacks, and best practices. We will also compare microservices to monolithic architectures and provide real-world examples and expert opinions to help you make informed decisions about which approach to use for your next project.

While microservices have garnered much of the spotlight in recent years, it’s crucial not to overlook the merits of the monolithic approach.

Understanding Microservices

At a high level, microservices are independently maintainable, scalable units of logic that orchestrate together to provide some functionality. Each microservice can be deployed and managed independently, allowing for greater flexibility and scalability compared to monolithic architectures.

In a microservices architecture, an application is broken down into smaller, loosely coupled components that communicate with each other using APIs or events. Each microservice can be written in a different programming language, use a different data store, and be deployed and scaled independently, however the complexity of achieving this shouldn’t be taken lightly.

The Good and the Bad

Like any architectural pattern, microservices have their benefits and drawbacks. Here are some of the main advantages and disadvantages of using microservices:


  • Greater scalability and flexibility: Since each microservice can be deployed and managed independently, it’s easier to scale individual components based on demand.
  • Improved fault tolerance: If one microservice fails, it doesn’t necessarily mean that the entire application will go down.
  • Easier to maintain and update: Since each microservice is smaller and more focused, it’s easier to maintain and update individual components without affecting the entire application.
  • Better team collaboration: Since each microservice can be owned by a single team, it’s easier for teams to collaborate and work independently.


  • Increased complexity: Microservices introduce additional complexity, such as managing inter-service communication, data consistency, and service discovery.
  • Higher operational overhead: Since each microservice is deployed and managed independently, there’s a higher operational overhead compared to monolithic architectures.
  • Increased network latency: Since microservices communicate over a network, there’s a higher risk of network latency and communication failures.
  • More difficult to debug and troubleshoot: Since microservices are distributed and loosely coupled, it can be more difficult to debug and troubleshoot issues.

Addressing the Cons:

Increased Complexity:

  • Service Mesh: Implementing a service mesh, such as Istio or Linkerd, can help manage inter-service communication, enforce policies, and provide features like load balancing, service discovery, and encryption. Service meshes abstract away much of the complexity involved in communication between microservices.
  • Event-Driven Architecture: Adopting an event-driven architecture can decouple microservices further and reduce complexity by allowing services to communicate asynchronously through events. This approach can streamline inter-service communication and minimize dependencies between services.
  • API Contracts: Establish clear API contracts between microservices to define communication protocols, data formats, and expected behaviors. This helps maintain consistency and reduces the risk of communication errors.

Higher Operational Overhead:

  • Container Orchestration: Utilize container orchestration platforms like Kubernetes or Docker Swarm to automate deployment, scaling, and management of microservices. These platforms provide tools for automating tasks like rolling updates, health checks, and load balancing, reducing manual operational overhead.
  • Infrastructure as Code (IaC): Embrace Infrastructure as Code principles to automate the provisioning and configuration of infrastructure components needed to support microservices. Tools like Terraform or AWS CloudFormation enable declarative definitions of infrastructure, promoting consistency and reproducibility while reducing manual intervention.

Increased Network Latency:

  • Edge Caching: Implement edge caching mechanisms using Content Delivery Networks (CDNs) or reverse proxies to cache frequently accessed data closer to users, reducing the need for round trips to microservices and mitigating network latency.
  • Asynchronous Communication: Opt for asynchronous communication patterns where possible, utilizing message queues or event-driven approaches to decouple services and minimize synchronous network calls that contribute to latency.

More Difficult to Debug and Troubleshoot:

  • Centralized Logging and Monitoring: Implement centralized logging and monitoring solutions to aggregate logs and metrics from all microservices. Tools like ELK Stack (Elasticsearch, Logstash, Kibana) or Prometheus can provide insights into system behavior, facilitating troubleshooting and performance analysis across distributed environments.
  • Distributed Tracing: Use distributed tracing tools like Jaeger or Zipkin to trace requests as they traverse through microservices. Distributed tracing enables visualization of request flows across services, aiding in pinpointing performance bottlenecks and debugging distributed systems.

Best Practices for Microservices

If you decide to use microservices for your next project, here are some best practices to keep in mind:

  • Start small: Don’t try to break down your entire monolithic application into microservices all at once. Instead, start small and gradually break down your application into smaller components.
  • Use a service registry: Use a service registry to manage service discovery and communication between microservices.
  • Implement API gateways: Use API gateways to provide a single entry point for clients and to handle authentication, rate limiting, and caching.
  • Use a consistent data model: Use a consistent data model across all microservices to ensure data consistency and integrity.
  • Implement monitoring and logging: Implement monitoring and logging to track performance, errors, and other metrics across all microservices.

Real-World Examples and Expert Opinions

Many organizations have successfully adopted microservices, including Netflix, Amazon, and Uber. Here are some real-world examples and expert opinions to help you make informed decisions about microservices:

  • Netflix: Netflix has been a pioneer in microservices, breaking down their monolithic application into smaller components to improve scalability and fault tolerance.
  • Amazon: Amazon has also adopted microservices, using this approach to build and deploy their e-commerce platform.
  • Uber: Uber has also adopted microservices, using this approach to build and deploy their ride-hailing platform.
  • Martin Fowler: “Microservices are a variant of the service-oriented architecture (SOA) style, with a smaller granule size and without the emphasis on ESBs and orchestration.”
  • Sam Newman: “Microservices are an architectural style that structures an application as a collection of small autonomous services, modeled around a business domain.”

Understanding Monolithic Architectures

At its core, a monolithic architecture entails building an application as a single, cohesive unit, with all components tightly integrated and deployed together. Unlike microservices, where functionality is distributed across independently deployable units, monoliths present a unified structure where all logic resides within the same codebase.

The Good and the Bad

While microservices boast scalability and flexibility, monolithic architectures offer their own set of advantages:


  • Simplicity and Coherence: Monoliths are inherently simpler to comprehend and manage, as all components reside within a single codebase. This cohesion can streamline development workflows and facilitate faster time-to-market.
  • Efficient Performance: With reduced overhead from inter-service communication and network latency, monolithic architectures often exhibit superior performance compared to their microservices counterparts.
  • Simplified Debugging and Troubleshooting: In a monolithic setup, pinpointing and resolving issues is often more straightforward, as all components operate within the same environment.


  • Limited Scalability: While monoliths excel in simplicity, they may encounter challenges when scaling, particularly as application complexity grows. Vertical scaling—upgrading hardware resources—might be necessary, which can incur higher costs.
  • Dependency Risks: Changes to one part of the monolith may inadvertently affect other components, leading to potential cascading failures. This tight coupling can introduce risks during maintenance and updates.
  • Monolithic Monoliths: In today’s fast-paced development landscape, some argue that monolithic architectures are outdated and unsuitable for modern applications. However, this assertion overlooks several key advantages that monoliths offer.

Addressing the Cons:

Limited Scalability:

  • Modularization: Introduce modular design principles within the monolith to break down the application into manageable modules or layers. This allows for more granular scaling of specific components as demand increases, reducing the need for vertical scaling.
  • Horizontal Scaling: While monoliths may face challenges with vertical scaling, horizontal scaling can be achieved by running multiple instances of the monolith behind a load balancer. This distributes incoming traffic across instances, increasing capacity and improving scalability.
  • Microservices Transition: Consider transitioning from a monolithic architecture to a microservices architecture if scalability requirements cannot be adequately addressed within the monolith. This approach allows for more fine-grained scaling of individual services, accommodating dynamic workload demands more effectively.

Dependency Risks:

  • Decoupling Components: Identify and decouple tightly coupled components within the monolith to reduce dependency risks. By modularizing the codebase and defining clear interfaces between components, changes in one part of the monolith are less likely to impact other areas, minimizing the risk of cascading failures.
  • Automated Testing: Implement comprehensive automated testing practices, including unit tests, integration tests, and end-to-end tests, to detect and prevent regression issues caused by changes. Automated tests provide confidence when making modifications to the monolith and help ensure the stability of the overall system.

Monolithic Monoliths:

  • Evolutionary Architecture: Embrace the concept of evolutionary architecture, which emphasizes incremental changes and iterative improvements over time. Rather than viewing monolithic architectures as static and outdated, approach them as adaptable systems that can evolve alongside changing requirements and technologies.
  • Continuous Refactoring: Regularly refactor the monolith to improve its design, maintainability, and adaptability. Refactoring involves restructuring code without changing its external behavior, making it easier to understand, modify, and extend the monolith as needed.

Best Practices for Monolithic Architectures

For developers opting for a monolithic approach, adhering to best practices can maximize the benefits and mitigate potential drawbacks:

  • Modular Design: While monolithic architectures are characterized by their unified structure, adopting a modular design within the monolith can enhance maintainability and scalability.
  • Robust Testing: Comprehensive testing strategies, including unit tests and integration tests, are essential for identifying and addressing potential issues within the monolithic application.
  • Continuous Refactoring: Regular refactoring sessions can help keep the monolith’s codebase clean and maintainable, reducing technical debt and enhancing long-term sustainability.

Real-World Examples and Expert Opinions

Numerous successful companies have embraced monolithic architectures to power their applications:

  • Facebook: Despite its colossal scale, Facebook initially built its platform as a monolithic application, leveraging its simplicity and efficiency.
  • GitHub: GitHub, the world’s largest code repository, also started as a monolith, enabling rapid development and iteration.
  • Linus Torvalds: “I think modern ‘microservices’ are mostly just plain awful. It sounds like it’s making things easier, but it’s making things worse.”
  • Donald Knuth: “Premature optimization is the root of all evil in programming. Monolithic architectures often embody simplicity, which can lead to more efficient optimization strategies.”

Comparing Microservices to Monolithic Architectures

While microservices have become a popular architectural pattern, monolithic architectures still have their place in web development. Here are some factors to consider when deciding between microservices and monolithic architectures:

  • Complexity: Monolithic architectures are simpler and easier to understand compared to microservices.
  • Scalability: Microservices are more scalable and flexible compared to monolithic architectures.
  • Maintenance: Microservices are easier to maintain and update compared to monolithic architectures.
  • Performance: Monolithic architectures can be faster and more performant compared to microservices due to reduced network latency.
  • Operational overhead: Microservices have a higher operational overhead compared to monolithic architectures.


While microservices continue to dominate discussions around web development architectures, it’s important not to overlook the compelling benefits of monolithic architectures. With their simplicity, efficiency, and proven track record, monoliths offer a viable alternative that developers should seriously consider. By embracing best practices and leveraging the inherent strengths of monolithic architectures, developers can build robust, scalable, and maintainable applications that stand the test of time.

It’s worth noting that starting with a structured monolith can provide a solid foundation, allowing developers to iterate quickly and deliver value to users. If the application grows in complexity or scalability requirements evolve, developers can then consider breaking down the monolith into microservices. This approach allows for flexibility and adaptability, ensuring that the architecture aligns with the evolving needs of the project.

While microservices may provide greater scalability and flexibility, they also introduce additional complexity and operational overhead. When deciding between microservices and monolithic architectures, it’s crucial to carefully weigh the pros and cons of each approach. By understanding the benefits and drawbacks of microservices, developers can make informed decisions about which architectural pattern best suits their project needs. Regardless of the chosen approach, whether it be microservices or monoliths, starting with a solid foundation and adhering to best practices will lead to successful application development and deployment.


Craig Fraser

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