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A backend application which demonstrates the use of microservices, docker containers, azure and highly functional techniques such as scale-in and scale-out using Flask, RabbitMQ, Zookeeper, Docker and AWS

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RithvikChan/CC-FullStack

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CC-FullStack

Assignment 1:

  • upload files to instance
  • setup flask, nginx, guinicorn
  • run the app as : gunicorn app:app -w 4 -b localhost:5000

Assignment 2:

  • Upload the folders to instance
  • change ip in the app.py files to your respective instance ip address
  • go to each folder and run: sudo docker-compose up

Assignment 3:

  • Set up a load balancer with rules on AWS
  • Create 2 instances, upload rides to 1 and users to the other.
  • Change the ip's as required.
  • run sudo docker-compose up in each of the instance after cd'ing into the folder.
  • send requests over load balancer ip

Final Project:

  • Create 3 instances.
  • create load balancer.
  • Place each folder in a different instance.
  • Change the ip's as required.
  • cd into the folder in each instance and run the script "run-all.sh".
  • you might have to run sudo docker system prune --volumes -a incase instance runs out of memory.
  • send requests over load balancer.

Testing:

  • Test1.postman_collection.json is a postman collection we made on our own set of requests

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A backend application which demonstrates the use of microservices, docker containers, azure and highly functional techniques such as scale-in and scale-out using Flask, RabbitMQ, Zookeeper, Docker and AWS

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