Common Mistakes When Building Microservices

Common Mistakes When Building Microservices

Microservices architecture is becoming increasingly popular, promising scalability, rapid development, and independent components. However, the transition to Microservices is not always smooth. If you are not careful, you can fall into anti-patterns that cause more problems than solutions.

1. Microservice as Monolith

Problem: Instead of splitting the application into small, independent services, you create a single service that takes on too many responsibilities, becoming a “monolith” application disguised as a Microservice. This service contains complex business logic, connects to multiple databases, and changing it becomes difficult and risky.

For example, a "UserService" not only performs authentication and authorization, but also stores personal information, manages activity history, integrates with email marketing systems, and more.

Solution:

• Clearly define scope of responsibility: Each service should have a single, clearly defined function.
• Apply the Single Responsibility Principle (SRP): Each module, class, or service should have only one reason to change.
• Refactor: If you already have a " Microservice as Monolith ", break it down into smaller, more specialized services.

2. Chatty Services

Problem: Services continuously exchange data with each other through many small requests, instead of a few large requests. This increases latency, reduces performance, and makes it difficult to monitor and debug.

For example, instead of an OrderService returning all product information (name, price, description, thumbnail), it calls the ProductService for each product in the shopping cart to get the details.

Solution:

• Using API Gateway: API Gateway can aggregate data from multiple services and return it to the client with just one request.
• Data Replication: Copy a portion of data from one service to another to reduce the number of requests. Consider data consistency.
• Batching: Combine multiple small requests into one larger request to reduce overhead.

3. Tight Coupling

Problem: Services depend too much on each other, making changes to one service can affect other services. This reduces the independence and scalability of the system.

For example, OrderService directly calls InventoryService database to check remaining product quantity.

Solution:

• Use APIs: Services should communicate with each other through clearly defined APIs, rather than directly accessing each other's databases.
• Using Message Queue (e.g. RabbitMQ, Kafka): Services can exchange information via message queue, reducing direct dependencies.
• Events: A service emits an event when there is a change, and other services can listen to this event to perform corresponding actions.

4. Nano Services

Problem: Splitting the application into too many small services leads to huge overhead in management, deployment, and monitoring. Orchestrating these services becomes complex and expensive.

For example, a service that performs only a simple mathematical operation (e.g. adding two numbers) is considered a standalone microservice.

Solution:

• Find a balance: Not everything needs to be a microservice. Focus on breaking it down into pieces that can be developed and deployed independently.
• Bounded Context: Use the Bounded Context concept in Domain-Driven Design (DDD) to define the scope of each microservice.
• Cost/benefit assessment: Carefully consider the costs and benefits of breaking up part of your application into a microservice.

5. Lack of Automation

Problem: Deploying, monitoring, and managing a microservices system requires a high level of automation. Without automation, you will waste a lot of time and effort on repetitive tasks.

For example, manually deploy a new version of a service by copying files, configuration, and restarting the service.

Solution:

• CI/CD (Continuous Integration/Continuous Deployment): Use CI/CD tools to automate the build, test, and deployment process.
• Orchestration (e.g. Kubernetes): Use orchestration tools to manage and coordinate containers.
• Monitoring and Logging: Set up monitoring and logging systems to track performance and detect errors.

6. Technology Heterogeneity Chaos

Problem: Using too many different programming languages, frameworks, and technologies across services. This makes maintenance, hiring, and knowledge sharing difficult.

For example, some services are written in Java, some in Python, some in Node.js, and each service uses a different framework.

Solution:

• Build standards: Establish standards for programming languages, frameworks, and technologies allowed to be used in the project.
• Share libraries: Create common libraries to share code between services.
• Training: Ensure that team members have sufficient knowledge and skills to work with the technologies used.

7. Security Neglect

Problem: Ignoring security issues when building microservices. This can lead to serious security vulnerabilities that can be costly to the business.

For example: No encryption of sensitive data, no user authentication, no access control.

Solution:

• Authentication and authorization: Ensure that only authorized users can access services.
• Data encryption: Encrypt sensitive data during storage and transmission.
• Access Control: Restrict services' access to other resources.
• Security Testing: Perform regular security testing to detect and fix vulnerabilities.

Conclusion: Building a Microservices architecture is a complex process that requires care and experience. By recognizing and avoiding these mistakes, you can increase your chances of success and get the most out of Microservices.