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@@ -102,19 +102,19 @@ To illustrate the challenge, let's consider an example. Suppose we have a bill g
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A Stack is the unit of deployment, meaning that everything within it is deployed together.
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**Example: Machine Learning Model**
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A machine learning model can also be modeled as a Construct and deployed as a Stack. The Constructs that make up this model include an Amazon S3 bucket for storing training data, an Amazon SageMaker notebook instance for model development, and an Amazon SageMaker endpoint for model deployment. These Constructs can be composed into a single high-level Construct, such as MachineLearningModel. This Construct can then be instantiated in one or more tacks for deployment, depending on the environment (e.g., dev, prod, staging).
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A machine learning model can also be modeled as a Construct and deployed as a Stack. The Constructs that make up this model include an Amazon S3 bucket for storing training data, an Amazon SageMaker notebook instance for model development, and an Amazon SageMaker endpoint for model deployment. These Constructs can be composed into a single high-level Construct, such as MachineLearningModel. This Construct can then be instantiated in one or more stacks for deployment, depending on the environment (e.g., dev, prod, staging).
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### Avoid Changing the Logical ID
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The logical ID is a unique identifier generated by AWS CDK for each resource in our Stack. Changing the logical ID of a stateful resource can lead to unintended consequences, such as
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The Logical ID is a unique identifier generated by AWS CDK for each resource in our Stack. Changing the logical ID of a stateful resource can lead to unintended consequences, such as
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***Resource recreation**: If the logical ID changes, AWS CDK may recreate the resource, resulting in data loss or inconsistencies.
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***Resource recreation**: If the Logical ID changes, AWS CDK may recreate the resource, resulting in data loss or inconsistencies.
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***Resource conflicts**: Changing the logical ID can cause conflicts with existing resources, leading to errors or unexpected behavior.
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### Use Generated Resource Names
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It's recommended to use generated resource names instead of physical names defined while resource creation which can lead to several issues, including: Resource recreation, Resource conflicts, Tight coupling
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It's recommended to use generated resource names instead of physical names defined while resource creation which, can lead to several issues, including: Resource recreation, Resource conflicts, tight coupling
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## Conclusion
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Our experience with AWS CDK, we were able to achieve true "infrastructure as code." Our CDK codebase became the single source of truth for our infrastructure, allowing us to manage and version-control our environments with ease. This approach also enabled us to automate our deployments, reduce manual errors, and improve our overall efficiency.
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Our experience With AWS CDK, we were able to achieve true "infrastructure as code." Our CDK codebase became the single source of truth for our infrastructure, allowing us to manage and version-control our environments with ease. This approach also enabled us to automate our deployments, reduce manual errors, and improve our overall efficiency.
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