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ACC: Airfoil Project G14

This project was developed as final project for the course Applied Cloud Computing.

File structure:

  • celeryconfig.py: Celery configuration file
  • tasks.py: Celery tasks definition file
  • app.py: Flask application file exposing the airfoil calculations to the end-user
  • cpu_monitor: File to run application demand evaluation

bin:

This folder contains CloudNaca and Airfoil binary files.

orchestration:

This folder contains the following YAML scripts for the application deployment using Heat orchestrator and Cloud-init contextualizer:

  • airfoil_asg_g14.yaml: Airfoil stack with auto-scaling group
  • airfoil_rg_g14.yaml: Airfoil stack with resource group
  • client_g14.txt: Celery client contextualization file
  • worker_rg_g14.yaml: Celery worker resource group
  • worker_g14.txt: Celery worker contextualization file
  • environment.yaml: Celery worker resource registration

Deployment Instructions

  • Using resource group: openstack stack create -t airfoil_rg_g14.yaml airfoil_stack_g14
  • Using auto-scaling group: openstack stack create -t airfoil_asg_g14.yaml -e environment.yaml airfoil_asg_g14

You could also change the default values for any of the following parameters including --parameter "ParamName=ParamValue"

  • image: Image to be used for compute instance
  • flavor: Type of instance (flavor) to be used
  • key: Name of key-pair to be used for compute instance
  • public_network: Public network with floating IP addresses
  • internal_network: Private network with local IP addresses
  • workers: Number of celery worker nodes to be deployed
  • sec_group_name: Assigned name for the security group

Task Monitoring

To monitor task execution using celery flower visit: <floatingip_client_node>:5555

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