Avoid these 7 mistakes while designing microservices
Learn how to avoid and resolve them
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Microservices are a hot topic while designing software applications on the Cloud.
Designing microservices is challenging, and making mistakes while designing them can tremendously outweigh their benefits.
From the granularity trap, where services become too fine-grained and unmanageable, to the overlooked complexities of ensuring data consistency and robust security measures, these challenges can significantly hinder the performance and scalability of your system.
However, recognizing these pitfalls is the first step toward building a more resilient, efficient, and secure microservices architecture.
In today’s newsletter, I discuss 7 common mistakes while designing microservices and implementing strategic measures to avoid them.
Let’s dive in!
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7 Mistakes To Avoid While Designing Microservices
Here are 7 common mistakes that software engineers make while designing microservices.
I have broken down each mistake as
what the mistake is
how to avoid it
reason for the approach taken
example
Over-Segmenting Services
Mistake: Creating too fine-grained microservices leads to a tangled web of interdependencies and increased communication overhead.
How to Avoid: Conduct domain-driven design to identify service boundaries correctly. Aim for services that are self-contained but not overly granular. Start with a larger scope for each service and split only when necessary. Balance the need for separation with the overhead it introduces.
Reason: To achieve maximum modularity, services are often made too small, which can reduce the system's maintainability and performance.
Example: Instead of separate microservices for each user attribute (like one for email and another for username), have a single user profile service that handles multiple related attributes.
Ignoring Data Consistency
Mistake: Designing microservices without a coherent strategy for managing data consistency across services.
How to Avoid: Use patterns like CQRS (Command Query Responsibility Segregation) and Event Sourcing to maintain data consistency without tight coupling. Implement strategies like eventual consistency, distributed transactions, or using a Saga pattern.
Reason: Each microservice has its database, and maintaining consistency across these databases is challenging.
Example: In an e-commerce application, use Event Sourcing to keep the order and inventory service data consistent. Use a Saga pattern to manage a multi-step transaction that spans several services, ensuring consistency without locking resources.
Inadequate Monitoring and Logging
Mistake: Underestimating the importance of centralized monitoring and logging in a distributed system.
How to Avoid: Establish a robust logging format across all services. Utilize centralized monitoring tools to aggregate and analyze logs.
Reason: Distributed systems generate logs in multiple places, making it hard to track issues without centralized logging.
Example: Implement a tool like Grafana for visualizing logs and metrics from all services in one place.
Inconsistent Communication Protocols
Mistake: Using a mix of incompatible or inefficient communication protocols between services.
How to Avoid: Evaluate the needs of each service interaction (like latency requirements) and standardize on a small set of protocols. Standardize on a few well-suited protocols. Consider factors like latency, payload size, and synchronous vs. asynchronous communication.
Reason: Different teams may choose different protocols based on local needs, leading to a lack of standardization.
Example: For real-time communication, use WebSockets; for regular API calls, use HTTP/REST, and AMQP or Kafka for asynchronous event-driven communication.
Neglecting API Gateway
Mistake: Exposing microservices directly to clients without an intermediary, leading to potential security risks and management difficulties.
How to Avoid: Use an API Gateway to handle cross-cutting concerns like authentication, authorization, rate limiting, and logging.
Reason: Direct service exposure can lead to security breaches and complicate managing services.
Example: Use Amazon API Gateway to manage user authentication, rate limiting, and route requests to appropriate services.
Poor Error Handling
Mistake: Lack of proper mechanisms to handle failures in inter-service communication, leading to cascading failures.
How to Avoid: Use resilience patterns like timeouts, retries, and circuit breakers to handle failures gracefully.
Reason: Network issues are common in distributed systems, and not handling them properly can lead to more significant outages.
Example: Use the Hystrix library to implement Circuit Breaker patterns to prevent a failing service from causing system-wide issues.
Ignoring Security Best Practices
Mistake: Overlooking the implementation of security measures in internal service communications.
How to Avoid: Enforce strict authentication and authorization and encrypt communication channels. Regularly update security protocols.
Reason: Microservices often communicate over networks, exposing them to potential security threats.
Example: Use mutual TLS for secure service-to-service communication and integrate Identity Access Management (IAM) for managing permissions.
Key takeaways
Avoiding these mistakes requires a balance between focusing on the core functionality and paying attention to system-wide concerns such as data consistency, communication, security, and monitoring.
A well-thought-out approach, considering these factors, leads to a more robust, maintainable, and scalable microservices architecture.
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