Microservices advantages and disadvantages

Microservices architecture has transformed how organizations build and deploy software applications. Instead of creating one large application where all components are tightly connected, microservices break down applications into smaller, independent services. Each service handles a specific business function and can be developed, deployed and scaled independently.

Companies like Netflix, Uber, Amazon, Spotify and Airbnb all use microservices to handle millions of users and transactions every day.

Microservices architecture has become increasingly important as it solves challenges that organizations face with traditional application design. Companies can build flexible overall systems, recover from failures easily and bring new features to market faster.

Microservices have moved from an emerging trend to a critical component of enterprise IT strategy. According to Gartner, 74% of surveyed organizations currently use microservices architecture, with another 23% planning to do so.¹

While microservices bring increased complexity, their benefits are driving widespread adoption across industries. Understanding the pros and cons of microservices is essential for making informed adoption decisions.

Microservices architecture represents a fundamental shift in how applications are designed and built, moving away from tightly coupled systems toward distributed architectures. Rather than building everything as one interconnected system, developers break functionality into separate, loosely coupled services. Each independently deployable module focuses on a specific business capability and operates with its own data storage, business logic and communication interfaces.

The concept of microservices can be traced to the 2010s and a shift away from service-oriented architecture (SOA), an approach where business applications are built from reusable software components called services.

Microservices build on the principles of SOA. Services are smaller and teams have more autonomy, while centralized control is minimized. This architecture gained traction alongside the rise of cloud computing and cloud-native development. Large technology companies like Amazon and Netflix pioneered this approach because they needed more flexibility and the ability to scale different parts of their applications independently.

Today, microservices have gone mainstream, with a robust ecosystem of tools and platforms that make them accessible to organizations of all sizes. The global microservices architecture market was valued at USD 376.08 billion in 2023. It is projected to reach USD 523.20 billion by 2030, growing at a CAGR of 4.9% from 2024 to 2030.²

Understanding the difference between microservices and monolithic applications shows why so many organizations are making the transition. In a monolithic application, everything is built as one unit with a single codebase. For instance, an enterprise web application handling customer orders, inventory management and billing would have all these functions tightly integrated. Changing one part requires understanding how it affects all the others.

While this simplicity makes initial software development simpler, it creates problems as applications grow. Any change requires rebuilding and redeploying the entire application. If more capacity is needed in a monolithic architecture, the entire application must be scaled, even the parts that don’t require increased performance capacity.

Microservices solve these problems by splitting the application into separate services that talk to each other through application programming interfaces (APIs). Each service has its own codebase and database and can be deployed independently.

Take the music platform Spotify, which has hundreds of millions of users globally. When music streaming demand spikes during a major album release, Spotify scales up its audio delivery and playlist services without affecting user authentication or payment processing. This approach allows different teams to work on individual services at the same time without conflicts.

Microservices architecture does introduce increased complexity in managing distributed systems. Many organizations take a hybrid approach, combining microservices with monolithic systems, serverless functions and other architectural patterns, based on what works best for specific use cases.

Microservices work through a combination of architectural patterns, communication methods and supporting technologies. Each microservice runs as its own process and presents its features through REST APIs, message queues or event streams. Services communicate over the network to share data and trigger actions.

For example, when a customer orders food through Uber Eats, multiple services work together in sequence. The system checks restaurant availability, processes payment, assigns a delivery driver and sends updates to the customer. An API gateway typically manages this communication, acting as a single entry point that routes requests to the right microservices.

Containerization technology, such as Docker, has become essential for microservices. Containers package each microservice with everything it needs to run, creating a standardized unit that works the same way across different environments.

Kubernetes and similar cloud platforms take this advancement further by automating the deployment, scaling and management of these containers. They handle service discovery, load balancing, health monitoring and automatic recovery when things fail.

Major cloud providers like Microsoft Azure, IBM Cloud® and Google Cloud Platform all offer comprehensive tools and managed services for deploying and orchestrating microservices.

Beyond containers, microservices rely on other technologies like service meshes for managing communication between services, distributed tracing for monitoring requests and API management tools for controlling access. Configuration management systems allow services retrieve settings dynamically and distributed logging platforms pull logs from all services into one place.

The benefits of microservices architecture integration are far-reaching. Key advantages include the most notable ones:

• Enhanced scalability

• Increased agility and faster time to market

• Fault isolation and system resilience

• Cost effectiveness

• DevOps integration and continuous delivery

• Technology flexibility and innovation 

Organizations scale exactly what they need with microservices. For example, during peak seasons, the travel accommodation platform company Airbnb scales up search and booking services while keeping other services like host messaging and review systems at normal capacity.

Different services use distinct scaling strategies based on their requirements. This modular approach reduces infrastructure costs and improves resource efficiency compared to scaling entire monolithic applications.

Small, autonomous teams own specific services end-to-end. Each team chooses the best technologies for their service and moves at their own pace without waiting for organization-wide coordination or redeployment cycles.

Companies can test ideas quickly, iterate rapidly and respond to market changes faster by building features such as new services that plug into existing ones.

If a recommendation engine crashes, users can still browse products, add items to their cart and check out. Circuit breakers and similar patterns allow services to handle failures smoothly when dependencies are unresponsive.

This resilience is crucial for enterprises where downtime costs reach thousands of dollars per minute. The entire application rarely goes down, even when individual components fail, because faults stay isolated.

Organizations save money through efficient resource management, scaling only the services that require greater capacity rather than entire applications. Development teams can optimize costs by selecting the most appropriate technology stack for each service’s specific requirements, avoiding the expense of overengineering or applying enterprise-grade solutions uniformly. The pay-as-you-go model of cloud-based microservices aligns costs directly with actual usage.

An IBM survey, Microservices in the Enterprise, 2021, found that 87% of over 1,200 IT executives, developer executives and developers agreed that microservices adoption is worth the expense and effort.

DevOps teams can seamlessly introduce new components without causing downtime, due to the independent operation of each service.

Automated testing, deployment pipelines and infrastructure as code (IaC) work well with microservices, creating a culture of rapid, reliable releases.

Each microservice can use different technologies, including programming languages (for example, Java™, Python), frameworks and databases best suited for its specific function. Teams aren’t locked into a single technology stack for the entire application.

Organizations can adopt new technologies incrementally, experiment with emerging tools and harness specialized solutions where they provide the most value.  

While offering substantial benefits, there are some drawbacks of microservices that organizations should address:

• Testing complexity

• Security considerations

• Communication coordination

• Data management

Testing a microservices-based application requires a different approach compared to monolithic applications. All dependencies, caching and data access need verification for proper performance. Test environments involve multiple services running simultaneously with proper configuration and data.

As services grow, test scenarios expand. Maintaining test data consistency and data integrity across services requires strategic planning.

Network communication between microservices creates enhanced security requirements. API gateways need proper authentication and encryption.

Managing credentials and access tokens across multiple microservices requires thoughtful coordination and security teams need robust visibility tools to monitor activity across the distributed architecture.

Design considerations become essential when coordinating communication between services. Calls between services add network latency compared to in-process function calls and these delays accumulate as requests flow through multiple services.

Network resilience features like retry logic, timeouts and failure handling become standard practice. Managing API versions also requires careful planning as services evolve independently.

Each microservice managing its own database creates data management challenges. Maintaining consistency when transactions span multiple databases requires specific patterns and reporting needs different approaches when data is distributed rather than centralized.

Microservices architecture requires deliberate planning and careful execution. Best practices include these key strategies:

• Define clear service boundaries

• Implement comprehensive observability

• Plan for resilience

• Automate infrastructure management