In the world of software development, there are certain design principles and practices that have stood the test of time, while others have fallen out of favour. The rise of microservices architecture has brought about a renewed focus on design patterns and anti-patterns, as developers look for ways to build more scalable, flexible, and maintainable systems. But what exactly are design patterns and anti-patterns, and how do they apply to microservices? In this article, we will explore the concepts of design patterns and anti-patterns in the context of microservices architecture, and discuss how they can impact the quality of your system.
What is a Design Pattern?
Design pattern in microservices refers to a set of proven and reusable solutions to common architectural and design challenges faced during the development of microservices-based systems. They provide a blueprint for developers to follow when designing and implementing individual services or entire systems and can help to improve scalability, flexibility, maintainability, and other key characteristics of microservices architecture.
Uses of a Design pattern are: -
Design patterns, in particular, are used to find solutions to design issues.
To help you discover the less obvious, look for appropriate objects and the things that capture these abstractions.
Choose an appropriate granularity for your object — patterns can assist with the compositional process.
Define object interfaces — this will aid in the hardening of your interfaces and a list of what’s included and what isn’t
Help you comprehend by describing object implementations and the ramifications of various approaches.
Eliminating the need to consider what strategy is most successful by promoting reusability.
Provide support for extensibility, which is built-in modification and adaptability.
Problem with Design Pattern
While design patterns are a useful tool for developing microservices, some potential problems can arise when using them. Here are a few common problems that can occur:
Over-engineering: One potential problem with design patterns in microservices is that they can sometimes be overused, leading to unnecessary complexity and overhead. It is important to only use design patterns when they are actually needed and to avoid adding extra layers of abstraction that can make the system more difficult to understand and maintain.
Tight Coupling: Another potential problem with design patterns in microservices is that they can sometimes lead to tight coupling between different services or components. This can make it more difficult to modify or replace individual services without affecting the rest of the system.
Performance Overhead: Some design patterns can also lead to performance overhead, especially if they involve additional network calls or data transformation steps. It is important to carefully consider the performance implications of using each design pattern and to only use patterns that are appropriate for the specific performance requirements of the system.
Complexity and Learning Curve: Finally, another potential problem with design patterns in microservices is that they can increase the overall complexity of the system and require additional learning time for developers. It is important to balance the benefits of using a particular design pattern with the additional complexity and learning curve that it may introduce.
Different Design Patterns in Microservices
1. Aggregator Microservice Design Pattern: The first, and probably the most common, is the aggregator microservice design pattern. In its simplest form, Aggregator would be a simple web page that invokes multiple services to achieve the functionality required by the application.
2. Proxy Microservice Design Pattern: Proxy microservice design pattern is a variation of Aggregator. In this case, no aggregation needs to happen on the client but a different microservice may be invoked based on the business need. Just like Aggregator, the Proxy can scale independently on X-axis and Z-axis as well. You may like to do this where each service need not be exposed to the consumer and should instead go through an interface.
3. Chained Microservice Design Pattern: Chained microservice design patterns produce a single consolidated response to the request. In this case, the request from the client is received by Service A, which is then communicating with Service B, which in turn may be communicating with Service C. All the services are likely using a synchronous HTTP request/response messaging.
4. Branch Microservice Design Pattern: The branch microservice design pattern extends the Aggregator design pattern and allows simultaneous response processing from two, likely mutually exclusive, chains of microservices. This pattern can also be used to call different chains, or a single chain, based on the business needs.
5. Shared Data Microservice Design Pattern: One of the design principles of microservice is autonomy. That means the service is full-stack and has control of all the components – UI, middleware, persistence, and transaction. This allows the service to be polyglot, and use the right tool for the right job. For example, a NoSQL data store can be used if that is more appropriate instead of jamming that data in a SQL database.
6. Asynchronous Messaging Microservice Design Pattern: While the REST design pattern is quite prevalent and well understood, but it has the limitation of being synchronous, and thus blocking. Asynchrony can be achieved but that is done in an application-specific way. Some microservice architectures may elect to use message queues instead of REST request/response because of that."
What is Anti-Pattern?
Anti-patterns are commonly used solutions that may seem intuitive, but they lead to poor design or implementation practices that are detrimental to the overall quality of a system. They are often a result of developers taking shortcuts or making assumptions and can lead to problems such as decreased maintainability, reduced scalability, and increased technical debt. In a microservices architecture, anti-patterns can lead to tightly coupled, inflexible services that are difficult to modify or replace, or that may experience cascading failures. It is important to avoid anti-patterns and promote good design practices to build scalable, maintainable, and robust microservices systems.
Anti-patterns are generally considered to be undesirable practices in software development and are therefore not recommended for use in microservices or any other type of architecture. However, it is important to recognize and understand anti-patterns to avoid them and promote good design practices.
Here are a few examples of anti-patterns that should be avoided in microservices:
Monolithic Architecture: This anti-pattern involves building a single, large application instead of breaking it down into smaller, more manageable services. This can lead to reduced scalability, flexibility, and resilience, and can also make it more difficult to modify or replace individual components of the system.
Tight Coupling: Tight coupling between services or components can make it more difficult to modify or replace individual parts of the system, and can also increase the risk of cascading failures if one service goes down. To avoid this anti-pattern, it is important to use loose coupling and appropriate design patterns to ensure that services can be modified or replaced independently.
Over-Reliance on APIs: APIs are an important tool for integrating services in a microservices architecture, but over-reliance on APIs can lead to increased network overhead and reduced performance. It is important to use APIs judiciously and to balance their benefits with the potential performance costs.
Data Duplication: Duplicating data across multiple services can lead to inconsistencies and errors, and can also increase the overall complexity of the system. To avoid this anti-pattern, it is important to use appropriate data sharing and synchronization techniques, such as event-driven architecture or a shared data layer.
1. Ambiguous Service
An operation’s name can be too long, or a generic message’s name can be vague. It’s possible to limit element length and restrict phrases in certain instances.
2. API Versioning
It’s possible to change an external service request’s API version in the code. Delays in data processing can lead to resource problems later. Why do APIs need semantically consistent version descriptions? It’s difficult to discover bad API names. The solution is simple and can be improved in the future.
3. Hard code points
Some services may have hard-coded IP addresses and ports, causing similar concerns. Replace an IP address, for example, by manually inserting files one by one. The current method only recognizes hard-coded IP addresses without context.
4. Bottleneck services
A service with many users but only one flaw. Because so many other clients and services use this service, the coupling is strong. The increasing number of external clients also increases response time. Due to increased traffic, several services are in short supply.
5. Overinflated Service
Excellent interface and data type parameters. They all use cohesiveness differently. This service output is less reusable, testable, and maintainable. For each class and parameter, the suggested method will validate service standards.
6. Service Chain
Also called a messaging chain. A grouping of services that share a common role. This chain appears when a client requests many services in succession.
7. Stovepipe Maintenance
Some functions are repeated across services. Rather than focusing on the primary purpose, these antipatterns perform utility, infrastructure, and business operations.
This antipattern consists of a collection of disjointed services. Because these poor cohesive services are tightly connected, reusability is constrained. Anti-patterns with complicated infrastructure have low availability and high response time.
The Difference: Design Pattern vs Anti-Pattern
A proven and reusable solution to common architectural and design challenges.
A common but suboptimal solution to a problem that can lead to poor design or implementation practices.
Provides a blueprint for developers to follow when designing and implementing microservices.
Often a result of developers taking shortcuts or making assumptions.
Improves scalability, flexibility, maintainability, and other key characteristics of microservices architecture.
Leads to decreased maintainability, reduced scalability, and increased technical debt.
Helps to build scalable, maintainable, and robust microservices systems.
Results in tightly coupled, inflexible services that are difficult to modify or replace, or that may experience cascading failures.
Examples include the Factory Method, Observer, and Chain of Responsibility patterns.
Examples include Monolithic Architecture, Tight Coupling, Over-Reliance on APIs, and Data Duplication.