Autoscaling Simulation server

This is the API service for autoscaling simulation.

The service now supports 2 features.

Generate jobs time data from source data.

POST /api/1.0/getJobs 
jobamanger: xxx.txt
splunk: xxx.json

HTTP/1.1 200 OK
[
    {
        "renderingTime":29,
        "downloadTime":3,
        "scenebuilderTime":7,
        "zipTime":3,
        "type":"image",
        "startTime":86266
    }
    ....
]

Two input files are needed, one is txt record data from jobmanager, file name is like xxx.txt each line in this file have 4 columns, the are -- Jobid, create time, rendering type and job final status

8a4f8bce-4bea-4a18-a0eb-da5eb302d69a,	0:21:24	,image,2

Another is record data from splunk, the file has .json file append, but is not a real json file, in this file, each line is a json object,

{
    "preview":false,
    "result":{
        "event_type":"RenderProxyEnd",
        "jobid":"63604c0c-1c1d-4af9-8f68-350d71b99aa9",
        "timestamp":"2016-11-28T15:59:16.170Z"
    }   
}

Simulation

1. Simulation by jobs

    POST /api/1.0/simulationByJobs
    jobs: xxx.json
    options:
    {
        "maxMachine": 50,
        "groupCount": 2,
        "capacity": 3,
        "imageTime": 120,
        "panoramaTime": 500
    }
   
    HTTP/1.1 200 OK
    {
        "machine": [
            {
                "hour": 20,
                "living": 20,
                "working": 20,
                "id": "1",
                "actions": [
                    {
                        "open": "2:10:10",
                        .....
                    }
                ]
            }
            ....
        ],
        "useRate": 88,
        "jobs": [
            {
                "totalTime": 100,
                "type": "image",
                "startTime": 100,
                "endTime": 100,
                "waitingTime": 200,
                "raasTime": 200
            }
            ...
        ],
        "timerRecords": [
            {
                "runningMachine": 100,
                "runningJob": 4,
                "waitingJob": 10
            }
            ...
        ],
        "averageRendering": 100,
        "averageWaiting": 100
    }
   

   Input json file, data is a json array, the file can get by API /api/1.0/getJobs or create by user themself.

    [
        {
            "renderingTime":218,
            "downloadTime":3,
            "scenebuilderTime":3,
            "zipTime":1,
            "type":"image",
            "startTime":1284
        }
        ....
    ]
   

2. Simulation by source data

    POST /api/1.0/simulationByData
    jobmanager: xxx.txt
    splunk: xxx.json
    options:
    {
        "maxMachine": 50,
        "groupMachineCount": 2,
        "reservedCapacity": 3,
        "imageRenderingTime": 120,
        "panoramaRenderingTime": 500,
        "recordTime": 120,
        "autoscalingTimer": 120
    }
   
    HTTP/1.1 200 OK
    {
        "machine": [
            {
                "hour": 20,
                "living": 20,
                "working": 20,
                "id": "1",
                "actions": [
                    {
                        "open": "2:10:10",
                        .....
                    }
                ]
            }
            ....
        ],
        "useRate": 88,
        "jobs": [
            {
                "totalTime": 100,
                "type": "image",
                "startTime": 100,
                "endTime": 100,
                "waitingTime": 200,
                "raasTime": 200
            }
            ...
        ],
        "timerRecords": [
            {
                "runningMachine": 100,
                "runningJob": 4,
                "waitingJob": 10
            }
            ...
        ],
        "averageRendering": 100,
        "averageWaiting": 100
    }
   

   Two input files are needed, one is txt record data from jobmanager, file name is like xxx.txt each line in this file have 4 columns, the are -- Jobid, create time, rendering type and job final status

    8a4f8bce-4bea-4a18-a0eb-da5eb302d69a,	0:21:24	,image,2
   

   Another is record data from splunk, the file has .json file append, but is not a real json file, in this file, each line is a json object,

    {
        "preview":false,
        "result":{
            "event_type":"RenderProxyEnd",
            "jobid":"63604c0c-1c1d-4af9-8f68-350d71b99aa9",
            "timestamp":"2016-11-28T15:59:16.170Z"
        }   
    }