Case Study: Visualize Complex Microservice Data Using Python

Source: My personal notes from Case Study: Visualize Complex Microservice Data Using Python Online Class | LinkedIn Learning, formerly Lynda.com

Use Case

• Create a solution from an idea at work, document it, develop it, and present and improve with others
• Why use Python? ease of use and other engineers are likely to be familiar with it; it is good for automation

Using Microservices

• Use case for microservices: Apps than are complex and need to scale, large applications with many functions

• Microservices vs Monolithic applications

  • Advantages of microservices: major functions separated to manage complexity, easier to scale and provide availability for different components
  • Disadvantages of microservices
    • Increased network communication between services and security - performance overhead
    • Due to distributed nature of microservice, requires management like through people management, automation, monitoring, and service integration
      • Data is distributed
      • Multiple platforms might be used
    • Can be more difficult to understand product and its lifecycles

Use case: How to Visualize Distributed Data?

Use case: Banned user from a social media platform with 250,000 followers wants to view their activity and manually review their activity. The ban can be done from various places like reports, algorithm detection, or user actions.

Solution: Build a diagnostic tool to visualize data from across different platforms. Needs to be:

• Maintainable: consider language, libraries, can be used in 1+ years
  • Consider existing team’s skills

Using PlantUML

• PlantUML is an open source tool to help create different types of diagrams like sequence, class, components and others
• Sequence diagram: show interactions in different services

@startuml

Client -> Server: request data
Server -> Client: response with data

@enduml

See more and a web based editor at PlantUML