Cloud Design Patterns
The Cloud Design Patterns project serves as an excellent resource for anyone looking to understand and implement effective architectural patterns in cloud-based applications. It's part of a larger series provided by the Azure Architecture Center, aiming to guide developers and architects in building robust and efficient cloud solutions.
Overview
This repository acts as a companion to the Cloud Design Patterns article series. It provides sample code that demonstrates best practices in design patterns commonly used in cloud applications. The main goal is to showcase solutions that address recurring design challenges and enable developers to adopt them in real-world scenarios.
Patterns Demonstrated
Here is a look at some of the key patterns included in the repository, each addressing specific challenges in cloud application design:
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Asynchronous Request-Reply: This pattern helps manage communication between services that require an acknowledgment of message receipt but where processing time might vary significantly.
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Choreography: Used in distributed systems, this pattern allows for decoupling services and letting them communicate without needing a central orchestrator.
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Claim Check: It helps manage data processing where messages can become too large by storing part of the data externally and passing a claim check to the consumer.
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Deployment Stamps: This pattern aids in designing cloud solutions that scale across multiple regions or tenants by replicating a set of services across numerous deployment locations.
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Geode: A structure where services are grouped based on geographic location to reduce latency and enhance performance in multi-region applications.
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Health Endpoint Monitoring: This pattern allows monitoring of application health by exposing endpoints that system operators can check to ensure services are working properly.
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Leader Election: In systems where a task needs to be performed by just one instance of a service, this pattern helps determine which instance should take the lead.
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Pipes & Filters: Useful for processing data streams, this pattern structures complex processing tasks into a series of reusable components, or filters, connected by pipes.
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Priority Queue: This pattern ensures important tasks are processed first by organizing tasks based on priority in the queue.
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Rate Limiting: It manages the number of requests a service can handle over time, thus ensuring stability and performance.
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Saga: Used for managing complex transactions across microservices, this pattern ensures that a sequence of transactions can be completed successfully or compensated for in case of failure.
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Sharding: This technique is used to divide databases into smaller, more manageable pieces called shards, significantly improving performance and scalability.
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Static Content Hosting: A way to deliver static files—like images and HTML—efficiently over the web.
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Valet Key: This pattern allows temporary, limited access to secure resources, ensuring client applications can access resources without compromising security.
Contributions
The project welcomes community contributions. Interested developers can refer to the Contributor Guide provided in the repository for guidance on how to contribute.
Code of Conduct
The project adheres to the Microsoft Open Source Code of Conduct, ensuring a professionally maintained and welcoming environment for all contributors.
The Cloud Design Patterns repository, backed by Azure patterns & practices and the Azure Architecture Center, provides an invaluable toolkit for anyone working within the cloud architecture space, helping them adopt the best practices proven in the industry.