As in previous chapters, we will create a serverless microservice using Google Cloud Functions, so let's follow these to create a working example:

1. Go to Google Cloud Console and locate Cloud Functions, as follows:

2. Click on the Create Functions option and start the process of defining an HTTP trigger function, as follows:

3. Use the following code in the index.js section to handle the main business logic of our serverless microservice. Also, please note that just below the code in the console, the value of the Function to execute option should be set to weatherService:

function handlePUT(req, res) {
 // Return Forbidden message for POST Request
 res.status(403).send('Forbidden!');
 }

function handleGET(req, res) {
 // Retrieve URL query parameters
 var zip = req.query.zip;
 var countrycode = req.query.countrycode;
 var apikey = req.query.apikey;

// Create complete OpenWeatherMap URL using user-provided parameters
 var baseUrl = 'http://api.openweathermap.org/data/2.5/weather';
 var completeUrl = baseUrl + "?zip=" + zip + "," + countrycode + "&appid=" + apikey;
 console.log("Request URL--> " + completeUrl)

// Import the sync-request module to invoke HTTP request
 var weatherServiceRequest = require('sync-request');

// Invoke OpenWeatherMap API
 var weatherServiceResponse = weatherServiceRequest('GET', completeUrl);
 var statusCode = weatherServiceResponse.statusCode;
 console.log("RESPONSE STATUS -->" + statusCode);

// Check if response was error or success response
 if (statusCode < 300) {
 console.log("JSON BODY DATA --->>" + weatherServiceResponse.getBody());
 // For Success response, return back appropriate status code, content-type and body
 console.log("Setting response content type to json");
 res.setHeader('Content-Type', 'application/json');
 res.status(statusCode);
 res.send(weatherServiceResponse.getBody());
 } else {

 console.log("ERROR RESPONSE -->" + statusCode);
 //For Error response send back appropriate error details
 res.status(statusCode);
 res.send(statusCode);
 }
 }

/**
 * Responds to a GET request with Weather Information. Forbids a PUT request.
 *
 * @param {Object} req Cloud Function request context.
 * @param {Object} res Cloud Function response context.
 */
 exports.weatherService = (req, res) => {
 switch (req.method) {
 case 'GET':
 handleGET(req, res);
 break;
 case 'PUT':
 handlePUT(req, res);
 break;
 default:
 res.status(500).send({
 error: 'Something blew up!'
 });
 break;
 }
 };

4. Now, click on the package.json option and edit it to include our code-specific dependencies, as follows:

Here's the code snippet to put in the package.json window:

{
 "name": "sample-http",
 "version": "0.0.1",
 "dependencies": {
 "sync-request": "^2.0"
 }
}

5. Click the Create button once you have verified that all of the settings and code are in line with the previously mentioned steps. In a few minutes, the function will be created and active in the console.

6. Now, it's time to test the function and for the same, go to your function details page and under the Tigger option, you will find the HTTPS endpoint for your function which can be used to invoke and test the microservice. Copy this URL which will then be used in the next step:

7. Now, append the following parameters to the preceding URL: zip, countrycode, and apikey, as follows:

https://us-central1-abcdef-43256.cloudfunctions.net/weatherService/?zip=10011&countrycode=us&apikey=vjhvjvjhvjhv765675652hhjvjsdjysfydfjy

Now, use any internet browser of your choice and go to this URL and see the magic for yourself! If the function executes successfully, then you should be able to see a JSON response with weather information for the location you specified in the parameters.

8. You can also test the same using the command line by using the curl command as follows:

$ curl -X GET 'https://us-central1-idyllic-coder-198914.cloudfunctions.net/weatherService/?zip=10001&countrycode=us&apikey=098172635437y363535'
    {"coord":{"lon":-73.99,"lat":40.73},"weather":[{"id":500,"main":"Rain","description":"light rain","icon":"10d"}],"base":"stations","main":{"temp":285.07,"pressure":998,"humidity":87,"temp_min":284.15,"temp_max":286.15},"visibility":16093,"wind":{"speed":10.8,"deg":290,"gust":14.9},"clouds":{"all":90},"dt":1522869300,"sys":{"type":1,"id":1969,"message":0.0059,"country":"US","sunrise":1522837997,"sunset":1522884283},"id":420027013,"name":"New York","cod":200}

9. Once you have tested the function, you can also monitor it from the console, under the General tab of the function details. There are multiple different views available, like those based on invocations, memory usage, and execution time, as follows:

10. Another important aspect of managing your Google Function is the Stackdriver Logs option, which can provide you with details of backend debugging from the code and function execution, as follows:

So with this, we have completed an end-to-end demo of how to design a serverless microservice using Google functions.