Design Patterns Q&A - Q4 - Are there other patterns too?
Tags: beginners, codenewbie, designpatterns, architecture
Published: 2023-11-22 17:08:07

| 🔴 **Disclaimer**: This post is enhanced with AI assistance.|
|--------------|

And the dialogue continues.

## The Newbie Asked
> But are the design patterns limited to patterns documented by GoF? Are there other patterns too?

## The Master Replied

Welcome! Your question about design patterns is a great one, especially for someone new to the field.

While the Gang of Four (GoF) design patterns are considered classics, there are many more patterns out there that are worth exploring.

Imagine if you have a favorite genre of music that you always listen to, but then you suddenly realize that there are countless other genres and sub-genres that you've never even heard of. Similarly, the world of software design is incredibly vast and diverse, and it's thrilling to explore the different patterns and approaches that go beyond the traditional GoF classics. There are so many exciting possibilities to discover and embrace.

Software design offers a wide range of design patterns that go beyond the popular GoF patterns. These patterns are like books in a library, organized by category and offering various options to choose from. No matter if you're looking for a classic or an innovative pattern, software design has a vast selection to offer.

***

![Enterprise Integration Patterns](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/tfg1gka150gqxdsexgog.jpg)

### Enterprise Integration Patterns
Enterprise integration patterns are a set of design patterns that enable smooth and efficient communication between different systems, much like a well-conducted orchestra where every instrument plays a specific role in creating a harmonious melody. 

These patterns provide a standardized way of integrating various applications, systems, and technologies, resulting in improved data flow, reduced complexity, and increased agility in the overall IT infrastructure. By leveraging enterprise integration patterns, organizations can ensure seamless communication and data exchange between their internal and external systems, leading to enhanced business productivity and competitiveness.

Since 2002, a multitude of integration projects have been analyzed and 65 integration patterns have been carefully selected to comprise this pattern catalogue. These patterns offer technology-agnostic design recommendations to developers and architects, empowering them to create reliable and effective integration solutions.[^1]

Let's explore three examples of Enterprise Integration Patterns:

1. **Message Channel:**
   - **Description:** Think of a Message Channel [^2] as a virtual postbox. It's a communication pathway where different parts of a system can send and receive messages. This pattern facilitates the decoupling of components, allowing them to communicate without directly knowing each other. It's like sending letters – you don't need to know the exact route; you just drop your letter in the mailbox.

2. **Message Router:**
   - **Description:** A Message Router is the traffic cop of integration patterns. It examines incoming messages and directs them to the appropriate destination based on predefined criteria. This pattern ensures messages reach their intended endpoints efficiently.

3. **Publish-Subscribe Channel:**
   - **Description:** Imagine a radio station broadcasting to multiple listeners. The Publish-Subscribe Channel is like that radio broadcast. It allows multiple components to subscribe and receive messages simultaneously. When a message is broadcasted, all interested subscribers get a copy. It's a way for different parts of a system to stay updated without directly interacting with each other – a virtual town crier announcing news to everyone interested.

These Enterprise Integration Patterns form the backbone of systems that need to communicate seamlessly, whether it's different parts of a monolithic application or various services in a distributed architecture. Each pattern provides a solution to a specific communication challenge, enhancing the flexibility and scalability of integrated systems.

***

![Microservice Architecture ](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/sbooamvz7umu7eupxpg6.jpg)

### Microservice Architecture Pattern Language
As the demand for scalable, flexible and resilient applications continues to grow, the Microservice architecture pattern language has emerged as a powerful tool for software architects. This pattern language is a comprehensive collection of tried and tested patterns that guide you in designing and implementing microservices-based applications. [^3]

It helps you evaluate whether microservices are the right choice for your application and explains the differences between monolithic and microservices-based architectures, highlighting their respective benefits and drawbacks. If the microservice architecture is deemed a good fit for your application, the pattern language provides you with effective solutions to various architecture and design challenges, enabling you to build robust, scalable and maintainable microservices-based applications.

In software architecture, the pattern language comprises various groups of patterns that help in designing and developing applications. These patterns are categorized into different groups namely the application architecture patterns, the Monolithic architecture patterns, and the Microservice architecture patterns. These groups of patterns assist in creating a solid and scalable architecture that meets the needs of modern software development.

The patterns are categorized into three different layers, depending on the type of problem they are designed to solve. The first layer is the Infrastructure patterns, which address mainly infrastructure issues that are beyond the scope of development. The second layer comprises the Application Infrastructure patterns that deal with infrastructure issues that also impact the development process. Finally, the third layer, the Application patterns, focuses on solving the problems that developers encounter during the development process.

Let's delve into brief explanations of three key microservices patterns: Saga, CQRS, and Distributed Tracing.

1. **Saga Pattern:**
   - **Description:** The Saga Pattern [^4] is like a choose-your-own-adventure novel for microservices. It deals with managing distributed transactions in a way that ensures consistency across multiple services. Instead of one big transaction, it breaks it into smaller, manageable steps (sagas). Each step is a chapter in the adventure, and if something goes wrong, the saga provides a way to undo or compensate for previous steps, ensuring the system remains in a consistent state.

2. **CQRS (Command Query Responsibility Segregation):**
   - **Description:** CQRS [^5] is the maestro conducting the orchestra of microservices. It advocates separating the read and write operations in a system. Commands (changes to the system's state) and queries (requests for information) are handled by different components. This pattern allows for scalability as read and write operations often have different performance and scaling requirements. It's like having a dedicated team for composing music (commands) and another for playing it (queries).

3. **Distributed Tracing:**
   - **Description:** Picture Distributed Tracing [^6] as a detective's magnifying glass for microservices. In a complex system with many moving parts, tracing helps you follow the journey of a request as it travels through different services. It provides insights into the performance and interactions between services. It's like having a GPS tracker for your requests, helping you identify bottlenecks, delays, or issues in the intricate dance of microservices.

These microservices patterns, like chapters in a playbook, offer solutions to challenges specific to the distributed and decentralized nature of microservices architecture. Whether it's ensuring consistency in transactions, segregating responsibilities for optimal performance, or tracing the journey of requests through a network of services, these patterns contribute to building resilient and scalable microservices-based systems.

***

![Cloud Native Patterns](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/4ttd3cjm5rdgqo2uvrcq.jpg)

### Cloud Native Patterns

Cloud Native Patterns [^7] are a set of best practices and design principles that enable applications to be developed and deployed in the cloud, with a focus on scalability and resilience. These patterns help to ensure that applications can handle a large volume of traffic and remain available even in the face of failures or disruptions.

The key principles of cloud-native patterns include microservices, containers, orchestration, infrastructure as code and DevOps.

Let us see three examples of cloud-native patterns:

1. **Service Mesh:**
   - **Description:** A service mesh [^8] is a dedicated infrastructure layer that provides service-to-service communication within a microservices architecture. It includes features such as load balancing, service discovery, and traffic management.

1. **API Gateway:**
   - **Description:** An API gateway [^9] is a layer that sits between clients and microservices, providing a single point of entry for all external requests. It also includes features such as authentication, rate limiting, and caching.

1. **Sidecar Pattern:**
   - **Description:** The sidecar pattern [^10] involves adding a separate container to a pod that provides additional functionality to the main container. This can include features such as logging, monitoring, and security.

***

![Kubernetes Design Patterns](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/eh1da6tysqorpapnfrhe.jpg)

### Kubernetes Design Patterns

Kubernetes design patterns [^11] are essential for building scalable and fault-tolerant containerized applications. These patterns provide a set of tried and tested solutions to common problems encountered in container orchestration. By understanding these patterns, you can optimize your Kubernetes deployment and achieve better performance, resilience, and availability. Think of them as the dance moves of container orchestration that can help you choreograph a seamless and efficient deployment. So, never forget to explore the Kubernetes design patterns and leverage them to build robust and reliable applications.

Let us see three examples of these patterns:
1. **Health Probe Pattern**
   - **Description:** Health Probe [^12] dictates that every container should implement specific APIs to help the platform observe and manage the application in the healthiest way possible. 

1. **Init Container Pattern**
   - **Description:** Init Container [^13] introduces a separate life cycle for initialization-related tasks and the main application containers. Init Containers enable the separation of concerns by providing a separate life cycle for initialization-related tasks distinct from the main application containers.

1. **Service Discovery Pattern**
   - **Description:** Service Discovery [^14] explains how clients can access and discover the instances that are providing application services.

***

![Version Control Patterns](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/x8905j601lt1zbcixpg3.jpg)

### Version Control Patterns

It's not just about design and coding; version control patterns [^15] ensure a smooth flow in the development rhythm. Effective usage of branching in software development requires following certain patterns to ensure seamless integration of work from multiple developers and a streamlined path to production releases. The key principle is to frequently integrate branches and focus on maintaining a stable mainline that can be effortlessly deployed into production. This approach ensures that the team can work collaboratively while keeping the mainline stable and ready for deployment at all times.

Three examples of version control patterns:
1. **Mainline Pattern**
   - **Description:** Mainline [^16] is a single, shared, branch that acts as the current state of the product. The mainline is a crucial codeline that represents the current state of the team's code. When the team starts working on a new piece of work, they pull the code from the mainline into their local repository to begin the development process. After completing the work, the team updates the mainline with their changes using the Mainline Integration pattern, to share their work with the rest of the team. This approach helps in maintaining the integrity and consistency of the codebase and ensures that everyone on the team is working on the same code.

1. **Continuous Integration Pattern**
   - **Description:** As a software development practice, continuous integration [^17] allows developers to merge their code changes into the main codebase multiple times a day. This process ensures that each commit is thoroughly tested and integrated with the rest of the code, leading to faster identification and resolution of any issues that may arise.

1. **Feature Branching Pattern**
   - **Description:** With feature branching [^18], we can keep all the development related to a specific feature separate from the mainline. This enables us to work on the feature without interfering with the rest of the codebase. Once the feature is complete, we can easily integrate it into the mainline branch.

***

![software development processes and strategies](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/wg3v65cagt7toh62a8fc.jpg)

Patterns are not only limited to the software design. Those can be also used in software development processes and strategies.

### Cloud Native Transformation Patterns
These cloud-native transformation patterns [^19] include excellent architecture, design, and cultural patterns to assist you in transforming your organization into a cloud-native firm, whether you're transitioning from legacy architectures or building new systems from the ground up.

These patterns are grouped into four families:  Strategy & Risk Reduction, Organization & Culture, Development & Design, Infrastructure & Cloud.

Four examples of cloud native transformation patterns (one for each family):

1. **Big Bet Pattern**
   - **Description:** When enough information is available, commit to a significant solution [^20] for moving the cloud migration forward. Focus on execution rather than research.

1. **Communicate Through Tribes Pattern**
   - **Description:** Create groups of people who have similar skills but are on different teams [^21] to cross-pollinate ideas across the company and provide a valuable whole-organization perspective.

1. **A/B Testing Pattern**
   - **Description:** Comparing multiple versions [^22] of something (a feature, new functionality, UI, etc.) under real customer use conditions quickly gives useful data about which performs better.

1. **CI/CD as Platform Pattern**
   - **Description:** The CI/CD system is treated as a platform [^23] on top of the cloud platform.

***

So, dear newbie, note that each pattern is a piece of advice, a tried-and-true solution to a recurring problem. Think of them as tools in your coding toolbox, each serving a specific purpose.

So, while GoF's patterns are the classics, there's a rich tapestry of patterns waiting to be explored. It's an ever-growing collection, like adding new albums to your music playlist.

Ready to dive into this expansive world of patterns? The adventure continues!

| ✍ **Note**: |
| --------- |
| If you enjoyed this blog, please consider liking, subscribing, commenting, and praising it. Your support will help us to continue sharing stories of hope and inspiration with others.|

We look forward to sharing our next blog with you soon!

[^1]: Patterns and Best Practices for Asynchronous Messaging. [Learn more](https://en.wikipedia.org/wiki/Enterprise_Integration_Patterns)

[^2]: Message Channel Pattern. [Learn more] (https://www.enterpriseintegrationpatterns.com/patterns/messaging/MessageChannel.html)

[^3]: Microservices Patterns. [Learn more] (https://microservices.io/index.html)

[^4]: Saga implements a distributed command as a series of local transactions. [Learn more] (https://microservices.io/patterns/data/saga.html)

[^5]: CQRS implements a distributed query as a series of local queries. [Learn more (https://microservices.io/patterns/data/cqrs.html)

[^6]: Distributed Tracing. [Learn more] (https://microservices.io/patterns/observability/distributed-tracing.html)

[^7]: Cloud Native Patterns. [Learn more](https://www.manning.com/books/cloud-native-patterns)

[^8]: Service Mesh [Learn more](https://www.nginx.com/blog/what-is-a-service-mesh/)

[^9]: API Gateway [Learn more](https://www.nginx.com/learn/api-gateway/)

[^10]: Sidecar [Learn more](https://learn.microsoft.com/en-us/azure/architecture/patterns/sidecar)

[^11]: Kubernetes Design Patterns [Learn more](https://k8spatterns.io/)

[^12]: Health Probe Pattern [Learn more](https://kubernetes.io/docs/tasks/configure-pod-container/configure-liveness-readiness-startup-probes/)

[^13]: Init Container pattern [Learn more](https://kubernetes.io/docs/concepts/workloads/pods/init-containers/)

[^14]: Service Discovery pattern [Learn more](https://kubernetes.io/docs/concepts/services-networking/service/#cloud-native-service-discovery)

[^15]: Effective branching patterns for collaborative development and streamlined production releases. [Learn more](https://martinfowler.com/articles/branching-patterns.html)

[^16]: Mainline Pattern [Learn more](https://martinfowler.com/articles/branching-patterns.html#mainline)

[^17]: Continuous Integration Pattern [Learn more](https://martinfowler.com/articles/branching-patterns.html#continuous-integration)

[^18]: Feature Branching Pattern [Learn more](https://martinfowler.com/articles/branching-patterns.html#feature-branching)

[^19]: Cloud Native Transformation Patterns [Learn more](https://www.cnpatterns.org/)

[^20]: Big Bet Pattern [Learn more](https://www.cnpatterns.org/strategy-risk-reduction/big-bet)

[^21]: Communicate Through Tribes Pattern [Learn more](https://www.cnpatterns.org/organization-culture/communicate-through-tribes)

[^22]: A/B Testing Pattern [Learn more](https://www.cnpatterns.org/development-design/a-b-testing)

[^23]: CI/CD as Platform Pattern [Learn more](https://www.cnpatterns.org/operations/cicd-as-platform)