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AWS CloudFormation is a service provided by Amazon Web Services (AWS) that enables users to model and manage infrastructure resources in an automated and secure manner. [1] Using CloudFormation, developers can define and provision AWS infrastructure resources using a JSON - or YAML -formatted infrastructure as code template.
Event-driven architectures have loose coupling within space, time and synchronization, providing a scalable infrastructure for information exchange and distributed workflows. However, event-architectures are tightly coupled, via event subscriptions and patterns, to the semantics of the underlying event schema and values.
Due to the fallacies of distributed computing, finding an adequate granularity is hard. [2] There is no single simple answer but a number of criteria exist (see below). A primary goal of service modeling and granularity design is to achieve loose coupling and modularity, which are two of the essential SOA principles, [3] and to address other architecturally significant requirements.
Service reference autonomy (an aspect of loose coupling) The relationship between services is minimized to the level that they are only aware of their existence. Service location transparency (an aspect of loose coupling) Services can be called from anywhere within the network that it is located no matter where it is present. Service longevity
Content coupling (high) Content coupling is said to occur when one module uses the code of another module, for instance a branch. This violates information hiding – a basic software design concept. Common coupling Common coupling is said to occur when several modules have access to the same global data.
Strong coupling does not allow this. This is a UML diagram illustrating an example of loose coupling between a dependent class and a set of concrete classes, which provide the required behavior: For comparison, this diagram illustrates the alternative design with strong coupling between the dependent class and a provider:
For example, due to the nature of Java, the IDL-Java mapping is rather straightforward and makes usage of CORBA very simple in a Java application. This is also true of the IDL to Python mapping. The C++ mapping requires the programmer to learn datatypes that predate the C++ Standard Template Library (STL).
The AWS CDK aims to improve the experience of working with Infrastructure as Code by providing higher-level, reusable constructs that enable developers to create and manage AWS resources more efficiently and with less boilerplate code compared to traditional configuration files like AWS CloudFormation templates.