In cloud architecture, cloud technology components interact and connect to create a cloud computing environment. There are different cloud architectures, like hybrid, public, private, and multi-cloud architectures. Today, we will talk about cloud architecture design patterns. What are they? These patterns have a set of approaches to solving one or more problems in cloud applications.
Table of Contents
An Overview of Cloud Architecture Design Patterns
You can use design patterns frequently to solve common issues in software design. Plus, these patterns can solve complex challenges that may arise while developing cloud-based applications. Let’s look at some of these popular patterns in detail.
Queue-centric Workflow Pattern
The queue-centric workflow technique of loose coupling mainly focuses on the asynchronous delivery of commands sent via an interface to the backend service.
The best part is that it lets the updates continue with the web tier without slowing down the process. Plus, you can use this pattern for requests or updates by users.
It is ideal for read-only requests, not routine ones. Here, communication is from one web direction to the service tier, often handled by messages in the queue.
It can be more reliable by decoupling the web and providing an enhanced user experience. Ideally, the pattern deals with applications distributed across tiers.
The pattern has a single horizontal focus through sharding. For sharding, you need to start with a single database and then scale up the data across two or more databases.
Each shard may have a database like the original one. Moreover, the data gets directed so that each row appears in a single shard. The combined shard data and original data are similar.
However, the data model you choose must be able to support sharding, which could be a possible barrier for apps not designed to fit the purpose. Also, cross-shard functions can be more complex than other patterns. You can use the pattern when database storage requirements exceed the capacity of a single node.
Horizontally Scaling Compute Pattern
You can horizontally scale compute nodes with the pattern. It primarily focuses on cloud resources and operational efficiency. Plus, it utilizes different resources in stateless autonomous compute nodes.
There are many advantages to apps, including a good user experience, availability, and high scalability. Horizontally scaling compute patterns can help when application capacity requirements exceed the capacity of the large compute node.
Also, it helps in the cost-effective scaling of the compute nodes. However, user state management should be handled without any sticky sessions. The pattern is ideal when the application capacity requirements are subject to unpredictable spikes.
In Bulkhead architecture, elements of the applications are isolated into different pools, so if one fails, the other will continue to function. It prevents a single failure within an app, saving it from total failure.
The Bulkhead pattern is named after the sectioned partitions of a ship hull. If the ship is compromised, only the damaged section is filled with water, saving the ship from sinking.
An application that uses the pattern must be built with resiliency. It allows you to preserve some functionality in the event of total failure. However, other functions of the app continue to work. With the pattern, you can deploy different services for different features when consuming apps.
With the help of the Ambassador pattern, you can create network requests on behalf of applications or users. You can use it when you need to access services in legacy applications, but without the client codes in such apps.
Ideally, it helps you build a proxy service that you can use for multiple Serverless frameworks or languages. Also, the pattern is effective when you need to offload cross-cutting connectivity stuff like security, monitoring, and logging.
Moreover, you can use the pattern with legacy apps or other applications you can’t modify easily. It also enables a specialized team to help with features.
External Configuration Store Pattern
With the pattern, you can move the configuration information of the app deployment package to a centralized location. It helps in the control of configuration data across different apps.
The pattern is ideal for a standard configuration system that does not support configuration settings like complex data types and storing images.
Moreover, it acts as a complementary store for app settings, allowing apps to override some centrally located settings. You can use the pattern to administer multiple applications and monitor configuration settings. However, the backup you choose for config information should have an interface with simple access.
A retry pattern enables an app to handle failures while connecting to a service or a network resource by retrying a failed function. Ideally, it helps improve app stability.
The pattern deals with third-party interactions and encourages the apps to accept failure. The processes help create a unique fault-tolerant system that requires minimum long-term maintenance.
You can use the pattern for handling failures, not internal exceptions caused by logical app errors. Additionally, you can use it as an alternative to address scalability challenges. If the app experiences issues, it’s a sign that access needs to be scaled up.
Busy Signal Pattern
The pattern mainly focuses on how an app should react when cloud services respond to programmatic requests with busy signals. For building reliable cloud-native applications, handling transient failures is significant.
Using this pattern, the app can detect these failures quickly. Moreover, you can tune your approach for different interactive user scenarios.
Ideally, the pattern reflects the client’s perspective and not the service. Oftentimes, it becomes difficult to test the app’s response to failure conditions or if it’s running on non-cloud hardware. Also, if the signal continues during a retry, the client may treat it as an unavailable service.
Circuit breaker patterns can handle faults that may take a long time to recover when connecting to a network or remote service. Scalability can be an issue in cloud-based apps, especially with unpredictable performance.
The pattern prevents the processes from running away before they consume added resources unnecessarily. However, it can improve the scalability and stability of an app.
You can use the pattern to prevent the app from invoking shared resources or remote services. But don’t use it as a substitute for handling business logic exceptions.
Anti-corruption Layer Pattern
With the pattern, you can use a layer between two subsystems that don’t share the same semantics. It translates the request made from one subsystem to another subsystem. Plus, you can use the pattern to ensure the design is not limited to one system.
By using this, you can avoid building point-to-point spiral architectures in the long run. Services are easy to explore, and you can focus on error handling with the layer.
Through a standard interface, you can expose functionalities to the external world. With the pattern, you do not have to customize the system when talking to other systems.
The pattern focuses on reducing the network latency for commonly accessed files through the globally distributed edge caching feature. The best part is that it helps to speed the app delivery of content to users.
By enabling a CDN, you can reduce the load on web servers and distribute the load across different services at once. With that, you can improve the overall user experience and scalability.
What are cloud architecture patterns?
Cloud architecture patterns are design solutions that address common challenges in cloud-based applications. These patterns include the Horizontally Scaling Compute Pattern, Queue-Centric Workflow Pattern, Auto-Scaling Pattern, and Eventual Consistency among others. They provide strategies for designing applications in a way that maximizes the benefits of cloud environments.
What are the patterns in cloud computing?
Patterns in cloud computing, like the Circuit Breaker and Retry pattern, are proven development paradigms that expedite the development process. They are repeatable solutions addressing common problems in software design, providing a conceptual framework for building applications for the cloud.
What are the 4 layers of cloud architecture in cloud computing?
The 4 layers of cloud architecture in cloud computing are the User/Client Layer, Network Layer, Cloud Management Layer, and Hardware Resource Layer.
What are the key design concepts of cloud architecture?
The key design concepts of cloud architecture include design principles, evaluation of cloud service providers, capacity planning, cloud-native architecture principles, and cloud architecture components such as frontend and backend platforms, cloud-based delivery models, and networks.
Cloud architecture makes it possible to develop functional and scalable applications. Multi-Cloud Architecture design can help you with complex challenges throughout the system so that you can focus on the scalability part.
Additionally, design patterns offer possible solutions to the most common problems when designing cloud-based apps. Knowledge of cloud design patterns can help you design cloud-based apps more seamlessly.