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prernaa96 edited this page Feb 10, 2022 · 35 revisions

Welcome to the DSDummies wiki!

For this weather application we are using the following technology stack:

  1. ReactJS (Frontend)
  2. NodeJS (Backend - AuthService)
  3. Java Springboot (Backend - CacheService)
  4. Python (Backend - Data Ingestor)
  5. MongoDB (Database)

Data Flow Diagram :

System Architecture

Napkin Diagram:

Napkin Diagram

User Napkin Diagram:

User-Napkin_Diagram

Steps to install :

Docker

We just need to run the following script to run the entire application :

  • Create a new directory in your local machine
  • Open a terminal in the folder created above and run "git clone https://github.com/airavata-courses/DSDummies.git"
  • Type cd DSDummies (only folder in the directory)
  • Run the individual commands as listed or run the script.

Directly execute script:

  • chmod 755 start.sh

  • ./start.sh

Alternatively, if not using script or it doesn't runs for you, the following commands would work for deploying the application on docker as well:

  • cd Client ( You need to go into the "Client" directory )

    • make build

  • cd ../Auth. ( You need to go into the "Auth" directory )

    • make build

  • cd ../cache. ( You need to go into the "cache" directory )

    • make build

  • cd ../Data\Ingestor/ ( You need to go into the "Data\Ingestor" directory )

    • make build

  • cd ..

  • make run-dev (From root directory)

  1. This shall spawn all the containers and then you would be able to open localhost://3000
  2. This shall open up a login page, if you're a first time user , then click on register.
  3. Once you register, go to login and put in your credentials.
  4. It shall open a US map with drop down boxes for data and time as well as specifying video option.
  5. Put in the radar station name, date and time, choose if you want to select a video or not, then click on getplot.
  6. This will fetch you the result from the aws and show a plotted graph of the received data.

Note : Step 6 doesn't works yet on Docker, but the complete functionality works end to end perfectly on local, we're in the process of fixing it, but until that time, for grading , please refer to the local setup.

UPDATE: Complete dockerization of the application works and the above mentioned steps should be able to deploy our code on the docker and run in it. This is fixed by Issue #50 commit

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