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Case Study: Visualize Complex Microservice Data Using Python

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As a software engineer, your day-to-day duties can seem like an endless to-do list, so it’s often difficult to find the time to develop new skills to grow and advance your career. How do you make an impact with your organization while also completing your core work?

In this course, Kathryn Hodge takes you through the process of coming up with an idea for an initiative, planning it, and then implementing the solution with your team. Kathryn covers the basics of microservices and shows you how to identify and solve problems when building and using microservices. She introduces you to PlantUML, an open-source tool that helps you quickly create sequence diagrams, class diagrams, component diagrams, and more. She explains how to plan the development of a problem-solving initiative—and how to sell it to your team. Kathryn then shows you how to build a Python script to convert data into PlantUML code, how to review and refine your code, and how to demo your initiative for your team.


01 - Introduction
  • 01 - How to make an impact in your organization as an engineer
  • 02 - Why use Python to build automation simple tools
  • 03 - Using GitHub Codespaces

  • 02 - 1. Defining the Problem and Researching a Solution
  • 01 - What are microservices
  • 02 - Disadvantages of the microservice architecture
  • 03 - How to solve for the challenges introduced by microservices
  • 04 - How to research and find a technology that will help solve technical problems

  • 03 - 2. Learning PlantUML
  • 01 - What is PlantUML
  • 02 - Experiment with PlantUML
  • 03 - How can you work with PlantUML in a maintainable way
  • 04 - How to decide if PlantUML will work for a use case

  • 04 - 3. Planning for the Development
  • 01 - Create an implementation plan for the initiative
  • 02 - How to convince your team to pursue the initiative
  • 03 - Divide work into user stories

  • 05 - 4. Building a Python Script to Convert Data into PlantUML Code
  • 01 - Establish input of the script
  • 02 - Establish the output of the script
  • 03 - Design implementation for script code
  • 04 - Load JSON data from a file
  • 05 - Iterate through JSON data and store effectively
  • 06 - Write simple PlantUML code to a file
  • 07 - Export PlantUML code to a PNG diagram with Python
  • 08 - Add data to each node in the PlantUML graph
  • 09 - Add edges to the PlantUML graph

  • 06 - 5. Going Above and Beyond
  • 01 - Review your code for inefficiencies and unnecessary complication
  • 02 - Create a README
  • 03 - Add live call to generate live graph
  • 04 - Prepare a demo for greater organization

  • 07 - Conclusion
  • 01 - Contributing to your engineering organization
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