radon-decomposition-tool

Items	Contents
Short Description	The decomposition tool is present to help RADON users in finding the optimal decomposition solution for an application based on the microservices architectural style and the serverless FaaS paradigm. It supports three typical usage scenarios: (1) architecture decomposition, (2) deployment optimization, (3) accuracy enhancement, (4) assignment/consolidation.
Documentation	D3.2 – Decomposition Tool I D3.3 – Decomposition Tool II
Stand-Alone Tutorial	https://decomposition-tool.readthedocs.io/
Video	https://youtu.be/ZHD0t8HK7K0
Repository	https://github.com/radon-h2020/radon-decomposition-tool https://github.com/radon-h2020/radon-decomposition-plugin https://github.com/radon-h2020/radon-decomposition-enhancement https://github.com/radon-h2020/radon-decomposition-interference
License	Imperial College's Intellectual Property
Contact	Lulai Zhu (@zhululai) Giuliano Casale (@gcasale)

Public Access Server

The decomposition tool has been made available on an Amazon EC2 instance with a RESTful API, which can be accessed through the URL: http://ec2-108-128-104-167.eu-west-1.compute.amazonaws.com:9000. The next table summarizes RESTful endpoints exposed by this public access server.

Path	Method	Parameters	Body	Response	Description
/file/{filename}	POST		file: octet-stream		Upload a file to the server
/file/{filename}	GET				Download a file from the server
/file/{filename}	DELETE				Delete a file in the server
/dec-tool/decompose	PATCH	model_filename: string			Decompose the architecture of a RADON model
/dec-tool/optimize	PATCH	model_filename: string		total_cost: number, measures: object array	Optimize the deployment of a RADON model
/dec-tool/enhance	PATCH	model_filename: string, data_filename: string			Enhance the accuracy of a RADON model
/dec-tool/consolidate	PATCH	model_filename: string, data_filename: string			Consolidate the assignment of a RADON model

Demo Application Example

A demo application example (thumbnail generation) based on the definitions of TOSCA types specific to the decomposition tool is provided here. Two RADON models are included in this example, one with an open workload and the other with a closed workload. To try the decomposition tool on the former, please perform the following steps:

1. Clone the repository and enter the model directory

    git clone https://github.com/radon-h2020/radon-decomposition-tool.git && cd radon-decomposition-tool/demo-app
   

2. Upload the original model to the server:

    curl -X POST http://ec2-108-128-104-167.eu-west-1.compute.amazonaws.com:9000/files/model.tosca -F 'file=@open_model.tosca'
   

3. Optimize the deployment of the model:

    curl -X PATCH http://ec2-108-128-104-167.eu-west-1.compute.amazonaws.com:9000/dec-tool/optimize?filename=model.tosca
   

4. Back up the original model in place:

    cp open_model.tosca open_model.tosca.bkp
   

5. Download the resultant model from the server:

    curl -X GET http://ec2-108-128-104-167.eu-west-1.compute.amazonaws.com:9000/files/model.tosca -o open_model.tosca
   

Additional information about the resultant model will be reported upon completion of deployment optimization (step 3), including predictions of the total operating cost and performance measures under consideration. In this example, the decomposition tool will return the mean as well as the 90th, 95th and 99th percentiles of the predicted response time distribution for the AwsLambdaFunction_0 node since a MeanReponseTime policy is attached to the execute entry of that node.

It is HIGHLY RECOMMENDED to use a different filename for each uploaded model, e.g. putting a UUID into the filename (model_5da82fdc-ae4c-48c4-ab5f-369a9a4fdee3.tosca), so as to minimize the possibility of collisions between concurrent requests. Last but MOST IMPORTANTLY, do not upload a model with any sensitive information, e.g. a pair of AWS access key ID and secrete access key. We currently cannot prevent other users from accessing your models in the server.