Node.js + ALM + REST API = Awesome

almNodeAuthentication.js

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Copyright (c) <2015> <junglee Force([email protected])>
  
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/**
    check out the post here https://jungleeforce.wordpress.com/2015/01/21/node-js-alm-rest-api-awesome/
**/

var https = require('https'),
    fs = require('fs'),
    config = JSON.parse(fs.readFileSync('config.json'));//this refers to a file where I have all my config like host, userName, password Etc
 
//this is added to avoid the TLS error. Uncomment if you get a TLS error while authenticating.
//process.env['NODE_TLS_REJECT_UNAUTHORIZED'] = '0';
 
//set the correct options for the call.
var options = {
    host : config.host, 
    path : "/qcbin/authentication-point/authenticate",
    method: "GET",
    headers : {'Authorization': 'Basic '+new Buffer(config.alm_userName + ':' + config.alm_password).toString('base64')}
    };
    //authenticating the user into ALM
    ALMConnect(options, 'header','', function(status, data){
        if(status){
            //get the LWSSO_Cookie from the header. This is the session cookie which will be used in all callouts to ALM.
            if(data.headers["set-cookie"] != undefined ) {
                extractDefects(data.headers["set-cookie"]);
            }else{
                console.log('Dagnabbit!! ERROR:  Unable to login, check your username/password/serverURL.');
            }
        }else{
            console.log('Dagnabbit!! ERROR:  ' + JSON.stringify(data));
        }
    });
 
//Function to extract the defects for analysis.
function extractDefects(LWSSO_Cookie){
    var queryParam = "{";
    //add Release
    queryParam += "detected-in-rel["+config.release+"];";
    //add all your request parameters here. Its a little complicated initially, but you will get a hang of it. 
    // Make sure to use encodeURIComponents() for all the values in the query parameters.
    queryParam+="}";
    //get all the fields that you want to query. Lesser the fields smaller the XML returned, faster is the call.
    var fields = config.defectFieldMapping.fieldArray.join(',');
    var opt = {
        host: config.host,
        path: "/qcbin/rest/domains/"+config.domain+"/projects/"+config.project+"/defects?query="+queryParam+"&fields="+fields+"&page-size=max",
        method:"GET",
        headers: {"Cookie":LWSSO_Cookie}
    };
 
    ALMConnect(opt, 'data','',function(status,data){
        if(status){
                        //write the defects to an XML file in local drive.
            fs.writeFileSync('newDefect.xml',data);
            //once you get the defectXML you can parse it into JSON and push it other databases like SFDC etc..     
        }else{
            console.log('Dagnabbit!! ERROR:  ' + JSON.stringify(data));
        }
    });
}
 
function ALMConnect(opt, responseType,requestBody, callback){
 
    var request = https.request(opt, function(res){
        res.setEncoding('utf8');
        var XMLoutput='';
        res.on('data',function(chunk){
            XMLoutput+=chunk;
        });
        res.on('end',function(){
            if(responseType=='data'){
                callback(true,XMLoutput);
            }else {
                callback(true, res);
            }
        });
    });
    request.on('error',function(e){
        callback(false,e);
    });
    if(opt.method=='POST' || opt.method == 'PUT'){
        request.write(requestBody);
    }
    request.end();
}

@sayantan2007
Hi bro,
Cross-origin resource sharing (CORS) means - the server(in our case ALM) expects your requests to come from another server/host and not from browser JavaScript like using FetchAPI or XMLHttpRequest. I tried something similar using Fetch in JavaScript and encountered similar error.
So i would suggest you to write your ALM rest calls in NodeJS, python, or any other server side programming languages or runtimes.
Hope it helps!!