Microservices architecture: keys to managing it

Microservices architecture has a determining role in data processing, allowing organizations to manage large volumes of information in an efficient and scalable manner. 

Unlike monolithic architectures, microservices divide the system into small, independent, specialized components. 

This facilitates parallel data processing, which is an essential factor when working with large flows of information in real time. 

To understand the growth that these environments are experiencing, a study conducted by Intel revealed that 83% of all new cloud-native applications and SaaS solutions are using microservices. 

For its part, a report by Mordor Intelligence estimates that the cloud microservices market will reach $1.63 billion in 2024, and predicts that could reach 4.57 billion in 2029.

In this article we discuss the impact that microservices have on the financial, retail and telecommunications sectors.

We also share best practices for managing them, explore the tests that can be used to evaluate this type of architecture, and identify the benefits of microservice independence.

In addition, we discuss methods for managing communication between microservices and how to address data consistency issues in such an architecture.

Impact of microservices in critical sectors

"The microservices architecture It is a software development approach that breaks down an application into a series of small, independent, loosely coupled services,” he explains. Martin Barrio, Software Delivery Manager IT Patagonia. 

“Each of these services or microservices is responsible for a specific business functionality and communicates with other services through lightweight APIs, such as HTTP/REST or messaging,” the expert adds.

As Martin points out, it is often used in combination with other architectural patterns and styles, such as event-driven architecture, CQRS, and service-oriented architecture.

In a microservices architecture, each microservice can be optimized and scaled individually. The goal is to improve overall performance and allow a Greater agility in the development and implementation of new functionalities.

This is why they are ideal when high performance and availability are required, and when different teams work in parallel on different services. 

This is especially useful in data processing systems that need to react quickly to market changes or new user demands. 

In order to analyze the value contribution of a microservices architecture, let's look at its impact on three sectors that must manage large flows of information in real time on a daily basis.

Financial sector

It allows services to be developed and deployed more quickly and efficiently. 

Each microservice focuses on a specific function, such as user authentication, account management, or payment processing, making it easy to upgrade or replace without affecting the rest of the system. 

So Development and implementation times for new functionalities are reducedThis strategy allows for rapid adaptation to various market demands, such as integration with digital wallets or support for cryptocurrencies. 

Furthermore, being highly scalable, microservices can manage demand peaks, which improves the user experience and ensures the continuous availability of financial services.

Retail

Microservices architecture transforms IT management by enabling greater flexibility and scalability in key operations such as inventory, payments, and personalizing the customer experience. 

By decoupling these functions into independent components, retail companies can synchronize their e-commerce platforms, mobile applications and physical points of sale in real time, allowing Eliminate inconsistencies in product availability. 

In addition, it facilitates integration with artificial intelligence tools for personalized recommendations and enables rapid scaling during spikes in demand, such as massive sales events. 

This not only improves operational efficiency, but also optimizes the shopping experience, generating greater customer loyalty.

Telecommunications

Functions such as billing or usage analysis are implemented as independent modules. In this way, Adaptability and the ability to offer dynamic solutions are increased.

Microservices architecture drives innovation and agility by allowing critical functions such as billing, usage analytics, and service provisioning to operate as independent modules. 

This facilitates the customization of services for clients, such as the creation of plans tailored to their needs or the implementation of real-time billing systems. 

In addition, microservices architecture enables easier integration with advanced technologies such as 5G networks and the Internet of Things (IoT), with the aim of improving the ability to offer dynamic and adaptable solutions.

This approach also increases system resilience, as failures in one microservice do not affect the rest, ensuring a high level of availability and quality in the services offered.

Benefits of microservices independence

Service independence is fundamental in microservices architecture and brings several key benefits:

• Development: Each team can work on a specific microservice without interfering with other teams. This allows for greater agility and speed in development.
• Deployment: Microservices can be deployed independently. This means that one service can be updated, scaled or repaired without affecting the others and minimizing downtime and the risk of errors.
• Scalability: Each microservice can be scaled independently based on its load needs. For example, if the payment service experiences a high transaction volume, it can be scaled without having to scale the entire application.
• Resilience: A microservice failure does not affect the entire application. If one service fails, the others can continue to function, which improves system resilience and availability.
• Technological flexibility: Teams can choose the most appropriate technologies for each microservice. This way, they can experiment with new technologies and adopt the best tools for each specific task.

To give an example, in the case of an e-commerce application, if the payment service needs an urgent security update, it can be deployed without affecting the product or user service. 

Additionally, if the ordering service experiences a surge in demand, it can be scaled independently to handle the additional load.

Recommended best practices

From BlockStellart suggest some practices for implementing microservices architectures:

1. Each service should have its own independent database.

2. All services must maintain a similar level of maturity and updating. 

3. Each microservice should be built and deployed independently. The development, testing, and deployment cycles for each microservice should be autonomous, to allow for updates and upgrades without affecting other services.

4. Each microservice has to be designed for a single specific responsibility, according to the single responsibility principle (SRP).

5. Each microservice and its dependencies should be packaged into a container to ensure that it runs consistently in any environment.

6. Treating servers as “stateless” means that microservices should not depend on information stored on the server to function.

7. Domain-driven design (DDD) helps structure services around coherent, well-defined business areas, known as “bounded contexts.”

8. Instead of building a single monolithic frontend application, the user interface is broken down into smaller, autonomous components that can be developed, deployed, and maintained independently.

9. Microservices Orchestration: refers to the process of managing, coordinating and automating the deployment, scaling and operation of microservices in a distributed infrastructure. 

Another issue to consider is data persistence, which is typically handled through external databases and caches, to ensure that the application state can be easily recovered in the event of failures. This allows microservices to be deployed and scaled seamlessly.

Additionally, and facing a migration from a monolithic architecture to a microservices architecture, one can also consider the Implementing CI/CD tools to automate infrastructure deployment and management.

Likewise, consider using monitoring tools to monitor the performance and health of microservices.

In addition, it is important to foster a culture of collaboration and provide ongoing training to teams to ensure they adapt appropriately to the new architecture. These are the keys to consider in order to: Migrating to a microservices architecture from a monolithic architecture.

What tests can be used to evaluate microservices environments?

Given the distributed and highly decoupled nature of an architecture, where microservices interact with each other to meet the functional requirements of the system, testing ensures that each of them works correctly, both independently and together.

Additionally, testing ensures that each service performs in accordance with business logic, integration between services, contract consistency, performance under load, and end-user experience. 

By identifying errors early and maintaining the quality of interactions between services, these tests allow changes to be implemented with greater security. 

This reduces the risk of interruptions and improves the reliability of the production system.

The most commonly used types of testing in microservices architectures are:

Unit Testing 

They are essential in microservices, because they evaluate individual functionalities of each isolated component, ensuring that they fulfill their intended purpose. 

They verify business logic at a granular level, using mock data to ensure that each microservice works correctly in its own execution. 

Due to the decoupled nature of microservices, unit testing helps maintain code quality and allows you to quickly detect bugs before they affect other services.

Integration Testing

They analyze how multiple microservices interact with each other or microservices with external systems, such as databases or APIs. 

They are essential to verify that communication between services works consistently and to ensure that data flows correctly between components. 

Since microservices rely on clear communication interfaces, these tests identify issues related to incompatibilities or errors in data transmission.

Performance Testing

They study how a microservice behaves under different workloads and high demand conditions. 

They evaluate response times, scalability, and service stability, ensuring that microservices can handle traffic spikes without performance degradation. 

They also help identify bottlenecks or limitations in the infrastructure, a key aspect for distributed systems with high concurrency.

Component testing

They focus on evaluating an individual microservice in its near-real-world environment, but without interacting with other services. They validate that the microservice works correctly with its simulated internal dependencies (such as databases or configurations). 

It is a useful approach to detect errors that might not show up in unit tests, but without the complexity of full integration tests.

Contract Tests

They are specific to microservices and verify that the contracts between them (definitions of the APIs or interfaces) remain consistent. 

They ensure that changes to a microservice do not break its integration with others, providing confidence in continued development. 

They are especially useful in teams that work independently on different services, as they reduce the risk of communication problems between them.

End-to-end testing

They evaluate how microservices work together to deliver complete functionality from the end-user perspective. 

They check complete flows, such as processing an order in an e-commerce system, ensuring that all parts of the system collaborate correctly. 

Although they are more expensive and complex, they are critical to ensuring that the final solution meets business requirements and offers a satisfactory user experience.

Methods for managing communication between microservices

Communication is a crucial aspect in microservices architecture. 

Microservices communicate with each other through APIs, via protocols such as HTTP/REST, gRPC, or asynchronous messaging (e.g. Kafka, RabbitMQ). 

These APIs allow data to be exchanged and requests to be made without the services being directly coupled to each other. This decoupling improves flexibility and makes maintenance easier, as changes to one microservice do not necessarily affect the others.

The most common methods for managing communication in microservices architectures are as follows:

1) Synchronous Communication

• RESTful APIs: Microservices communicate over HTTP using RESTful APIs. 
• gRPC: A high-performance communication framework that uses HTTP/2 and allows communication between microservices in different programming languages.

2) Asynchronous communication

• Messaging: Use messaging systems like RabbitMQ, Apache Kafka, or AWS SQS to send messages between microservices. This method is useful for decoupling services and improving resilience.
• EventsMicroservices can publish events to an event bus (such as Apache Kafka) and other services can subscribe to these events to react accordingly.

Asynchronous messaging is ideal for systems that require high availability and fast response.

Example of synchronous and asynchronous communication of microservices 

In order to exemplify communication in microservices architectures, we return to the example of an e-commerce application:

Synchronous communication with RESTful APIs

When a user places an order, the order service may call the product service to check the availability of the product and then the payment service to process the cancellation of the price of a product. 

These calls are made through RESTful APIs.

Asynchronous communication with messaging

After the order service creates a new order, a message can be sent to a message queue that the payment service “listens” to process the payment.

How to address data consistency issues in a microservices architecture?

Managing data consistency in a microservices architecture can be challenging, due to its distributed nature. 

Some common strategies and patterns for handling these problems may include:

Eventual consistency

Instead of ensuring immediate consistency, data is allowed to be synchronized over time. This is useful in systems where availability is more critical than immediate consistency.

Saga pattern

This pattern handles distributed transactions by breaking them into a series of local transactions coordinated through events or messages.

Each step in the saga performs an action and publishes an event to trigger the next step.

If a transaction fails, compensating steps are executed to undo changes made by previous transactions.

Conciliation

To find blocked transactions and resume the operation or apply a compensation, data from multiple services needs to be reconciled.

Data from multiple services can be reconciled through actions that can be triggered on a scheduled basis or through a monitoring system, when a failure is detected. 

The simplest approach is to run a record-by-record comparison and this process can be optimized by comparing added values. 

CQRS (Command Query Responsibility Segregation)

Separate read and write operations into different models. This allows each model to be optimized for its specific purpose and can help manage data consistency.

Event Sourcing

Instead of storing the current state, all the events that led to that state are stored and recorded. This allows the current state to be reconstructed from the various events that occur, facilitating consistency.

Databases by service

Each microservice has its own database, which reduces dependencies between services and improves autonomy.

However, this can complicate management and require additional strategies to maintain consistency between databases.

Conclusion

Migrating to a microservices architecture offers advantages such as scalability, resilience and flexibility, but in parallel presents significant challenges that require strategic planning and organizational adaptation. 

Breaking down monolithic applications involves identifying clear boundaries between services and avoiding critical dependencies, while data management raises issues of consistency and synchronization across distributed databases. 

Furthermore, ensuring efficient communication between microservices requires robust tools and strategies to mitigate latency and network overload. 

Beyond the technical aspects, the transition to microservices entails a cultural change within the organization. Teams accustomed to working with monolithic applications must adapt to more collaborative and autonomous approaches, restructuring roles and responsibilities. 

Added to this is the need to implement specific security strategies for each service, ensuring authentication and authorization without compromising the system as a whole. 

Overcoming these challenges requires not only the right technological solutions, but also a mindset geared toward innovation and continuous improvement across the company.

If your organization is considering modernizing its systems and migrating to a microservices platform, We invite you to discover our Software Studio.

Our multidisciplinary teams analyze projects with a 360-degree approach to identify opportunities for improvement and boost your digital transformation.