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  • Let's make Cloud #49: CI/CD Pipeline for Terraform Workflow Using Amazon CodeCatalyst, 12 Microservices Patterns for System Design Interview, Generating Mermaid Syntax Diagrams with AI 🧜🏼‍♀️

Let's make Cloud #49: CI/CD Pipeline for Terraform Workflow Using Amazon CodeCatalyst, 12 Microservices Patterns for System Design Interview, Generating Mermaid Syntax Diagrams with AI 🧜🏼‍♀️

CI/CD Pipeline for Terraform Workflow Using Amazon CodeCatalyst, 12 Microservices Patterns for System Design Interview, Generating Mermaid Syntax Diagrams with AI 🧜🏼‍♀️

Hello CloudMakers!

It's astonishing to think that there are only four days left until re:Invent officially kicks off! I know I've mentioned this in our last issue, but my excitement is truly sky-high and I can't seem to contain it. For us in the AWS community, the anticipation is palpable, and the countdown to the moment we all gather is thrilling. Please feel free to seek me out (also via the Peertalk app) in Las Vegas if you happen to be there. I'll be departing on Saturday, which means I'll be around from Sunday, and I'm simply buzzing with anticipation.

Today we shall see:

  • CI/CD Pipeline for Terraform Workflow Using Amazon CodeCatalyst

  • 12 Microservices Patterns for System Design Interview

  • Generating Mermaid Syntax Diagrams with AI 🧜🏼‍♀️

Enjoy!

CI/CD Pipeline for Terraform Workflow Using Amazon CodeCatalyst

This article focuses on the technicalities of integrating Terraform with Amazon CodeCatalyst in a CI/CD pipeline, emphasizing the practical application with extensive code examples. By leveraging CodeCatalyst, which is a new addition to the suite of AWS tools designed to streamline the development process, developers can manage infrastructure changes more efficiently.

The use of GitHub as the source code repository, connected to CodeCatalyst, allows for a seamless transition from code commit to deployment. The article's strength lies in its hands-on approach, providing readers with ample code snippets that they can directly implement or use as a reference to set up their Terraform workflows within a CI/CD pipeline. This guidance is particularly valuable for teams looking to automate and improve collaboration in their infrastructure management processes.

12 Microservices Patterns I Wish I Knew Before the System Design Interview

The article does a great job of breaking down microservices—a must-know for today's software developers, especially those aspiring to become Cloud Architects. If you've been considering stepping up to a Cloud Architect position but feel you might not be fully versed in certain technical concepts due to your past engineering focus, this piece could be a valuable starting point. It lays out the foundational patterns and practices of microservices that are crucial for any Cloud Architect, providing a clear overview to build upon as you deepen your expertise in the field.

Generating Mermaid Syntax Diagrams with AI-powered Amazon Bedrock 🧜🏼‍♀️

This article makes a strong case for the use of generative AI in software development, specifically through Amazon Bedrock. It presents several instances where AI tools can assist teams by visualizing complex information. With real code provided as examples, the article demonstrates how these visualizations help team members across different roles—like QA engineers or project leads—to quickly understand the work without needing deep coding knowledge. This use of AI to create state diagrams and Gantt charts from technical notes and code is shown to be an efficient way to keep everyone on the same page in a fast-paced development setting.

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