This is a continuation of an article that describes operational considerations for hosting solutions on Azure public cloud.

These are some of the cloud design patterns that are useful for building reliable, scalable, secure applications in the cloud. Some of the challenges encountered for which these design patterns hold include:

Data Management: This is a key element of the cloud application. Data is hosted in different locations and across multiple servers for reasons such as performance, scalability or availability, and this can present a range of challenges. For example, data consistency must be maintained and data will typically need to be synchronized or replicated across different locations.

Design and Implementation: Good design comes with consistency and coherence in component design and deployment. It simplifies administration and deployment. Components and subsystems get reused from scenario to scenario.

Messaging: A messaging infrastructure connects services so that they have flexibility and scalability. It is widely used and provides benefits such as retries, dead letter queue and ordered delivery but it also brings challenges such as services not reacting to changes in message schema, idempotency of operations and the periods of inactivity when the messages are not delivered.

The patterns used to resolve these kinds of problems include the following:

1.       Ambassador patterns that create helper services and send network requests on behalf of a consumer service or application.

2.       Anti-corruption layer that implements a façade between a modern application and a legacy system.

3.       Asynchronous request-reply where the backend processing is decoupled from a frontend host, or it needs to time but the front end still needs a clear response

4.       Backends for Frontends: where microservices provide the core functionalities that the frontend requires

5.       Bulkhead: where elements of an application are isolated into pools so that if one fails, the others will continue

6.       Cache-Aside: this loads data on demand into a cache from a data store.

7.       Choreography: where each service decides when and how a business operation is processed and eliminates the need for an orchestrator

8.       Circuit breaker: which handles fault that takes variable amount of time to fix when connecting to remote resources.

9.       Claim Check: which splits a large message into claim checks and payload to avoid overwhelming a message bus

10.   Compensating Transaction: which undoes the work performed by a series of steps that together define an eventually consistent operation.