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This project is a Distributed Systems based Platform-as-a-Service(PaaS) implementation for enabling user-defined pipelined execution. Micro-services are deployed at run time using docker containers based on user requests.

Python 83.45% Dockerfile 5.47% Shell 8.04% PowerShell 2.96% Roff 0.09%
distributed-systems distributed-computing platform-as-a-service cloud-computing python flask-application docker containerization microservices microservice

distributed-systems-platform-as-a-service-implementation's Introduction

Steps to run 
Run the following commands in sequence

Following steps To be done at master physical node 
1. Create the Docker Images for each Microservice 

$ sh images.sh

2. Start the pricing scheduler and resource monitor server 

$ cd resource_monitoring_server
$ python3 pricing_schedular.py
$ python3 monitor_server.py

Note: Server running at http://<IP of Master Node>:9999/retrieve/<user_id>

3. Start the API Gateway Server

$ cd api_gateway_server
$ python3 api_gateway.py

Note: Server running at http://<IP of Master Node>:5000/


Following steps To be done at Slave Physical Node

1. Start resource monitor client

$ cd resource_monitoring_client
$ python3 monitor_client.py


Following steps To be done at Client Machine

$ cd client1

Note: Setup Configurations in the config.ini file and run the following commands.Tokenwill be updated on its own when we run config_setup.py.

$ python3 config_setup.py
$ python3 streaming.py



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