gopher-holes-unlimited VS aws-cdk

When you define the backing resources and request schemas in your spec file, SAM will automatically create a huge amount of supporting resources:

If we take my reference application Gopher Holes Unlimited as an example, we see that I have a function that updates an existing gopher and another function that links gophers to gopher holes.

Gopher Holes Unlimited

Any operation that you need to be idempotent and require the full resource data to be provided should be backed by a PUT operation. For example, if we take the update gopher hole endpoint from my reference project Gopher Holes Unlimited, you can see that we overwrite the entire gopher hole resource.

The real key to the success I've had doing this is that I can quickly find my resources from a known entry point, like an API endpoint. I can look at my spec, see that it ties to a specific Lambda function, and go straight there.

With serverless microservices, structure your root-level folders by resource type. Take the Gopher Holes Unlimited reference architecture project as an example.

When talking about data flows, I mean the path through your system a business process follows. If we take an example from Gopher Holes Unlimited, we can see what happens when a new gopher is added to the system.

I'm not a fan of providing theory without practice. So I have revamped my Gopher Holes Unlimited application to show the specifics of how to setup and process jobs.

# My Example Microservice ## Description This is an example README for **Gopher Holes Unlimited** - a fake business but real API that tracks two things: 1. Gophers 2. Holes ## Infrastructure  *Resources currently deployed in Production. This diagram was automatically generated in the CI pipeline* ## Source If you want to check out the source, please visit our [GitHub page](https://github.com/allenheltondev/gopher-holes-unlimited)

We will take an example from my fake business but real API, Gopher Holes Unlimited, where we add a new gopher into the system to be tracked.

https://github.com/aws/aws-cdk#at-a-glance is the "generate cloudformation using code," and is the AWS version of troposphere as best I can tell

environment: Specifies the environment variable that will be available to our Lambda function. In this case I wrote an environment for RDS Database. Anyway, later I will write about AWS CDK using Python for creating database clusters, etc.

Today, I will show you how to build Amazon Location Service, which allows you to build location-based applications within your AWS environment using AWS Cloud Development Kit (AWS CDK) and AWS CloudFormation. I will also show examples of the recently popular CDK Migrate and AWS CloudFormation IaC generator.

AWS Cloud Development Kit (CDK): is an open-source software development framework to define your cloud application resources using familiar programming languages.

I am not one to build programming languages on a whim. In fact, I've spent the last five years building the AWS CDK, which is a multi-language library that addresses some of the challenges I am talking about by allowing developers to define cloud infrastructure using their favorite programming language.

I recently started exploring SST as an alternative to my favorite full-stack set consisting of Projen, AWS CDK, and React. I have been thoroughly impressed with the experience so far. In this article, I will demonstrate how to create a Next.js App Router S3 Picture Uploader using SST.

AWS CDK

For KMS 🔑, Each key is ~$1/mo, and with CDK, keys are generated on a massive scale, if not centralized.

Here is a github repository containing the code and instructions on how to automate this whole setup using AWS CDK.

Now that you have a working smart contract event listener, we'll deploy the resources to AWS using AWS CDK, which is an Infrastructure as Code (IaC) tool. AWS CDK allows you to configure, deploy, and manage AWS cloud resources using popular programming languages such as TypeScript.