{"id":5069,"date":"2022-09-19T10:53:39","date_gmt":"2022-09-19T10:53:39","guid":{"rendered":"https:\/\/www.cloudmetrik.com\/?p=5069"},"modified":"2022-09-19T12:04:20","modified_gmt":"2022-09-19T12:04:20","slug":"getting-started-with-aws-lambda","status":"publish","type":"post","link":"https:\/\/www.cloudmetrik.com\/tr\/getting-started-with-aws-lambda\/","title":{"rendered":"Getting Started with AWS Lambda"},"content":{"rendered":"<p><strong>AWS Lambda<\/strong> is a serverless processing service in AWS. When programming with Lambda, a logical layout of your application is literally all you need. You simply need to make sure each component in the layout maps directly to a function that can independently perform exactly one task. For each component, code is then developed and deployed as a separate Lambda function.<\/p>\n<p>AWS Lambda natively supports running any <strong>Java<\/strong>, <strong>Go<\/strong>, <strong>PowerShell<\/strong>, <strong>Node.js<\/strong>, <strong>C#<\/strong>, <strong>Python<\/strong>, or <strong>Ruby<\/strong> code package that can contain all kinds of extensions, prerequisites, and libraries\u2014even custom ones. On top of that, Lambda even supports running custom interpreters within a Lambda execution environment through the use of layers.<\/p>\n<p>The code is packaged into a standard ZIP or WAR format and added to the Lambda function definition, which in turn stores it in an AWS-managed <strong>S3 bucket<\/strong>. You can also provide an S3 key directly to Lambda, or you can author your functions in the browser in the Lambda section of the <strong>AWS Management Console<\/strong>. Each Lambda function is configured with a memory capacity. The scaling of capacity goes from 128 MB to 3,008 MB, in 64 MB increments.<\/p>\n<p>The Lambda section of the Management Console allows you to manage your functions in an easy-to-use interface with a simple and efficient editor for writing or pasting in code. The following example shows how to create a simple Node.js Lambda function that prints out a JSON-formatted response after you input names as key\/value pairs.<\/p>\n<p><strong>Building an Event Handler and Testing the Lambda Function<\/strong><\/p>\n<p>Start by opening the AWS Management Console, going to the AWS Lambda section, and clicking Function and then \u201cCreate function.\u201d Next, replace the default code with the code shown here. This code defines the variables for the key\/value pairs you will be entering in your test procedure and returns them as JSON-formatted values:<\/p>\n<p>&#8212;-<\/p>\n<p>When you are done creating the function, click the Save button at the top right.<\/p>\n<p>Next, you need to configure a test event for entering your key\/value pairs. You can use the following code to create your test data:<\/p>\n<p>&#8212;-<\/p>\n<p>Once you\u2019ve entered that, scroll down and click Save at the bottom of the Configure Test Event dialog box. Next, run the test, which invokes the function with your test data. The response should be a JSON-formatted column with the value Names, and then a list of the names that you entered as test data.<\/p>\n<p>In the execution result, you also have information about the number of resources the function consumed, the request ID, and the billed time. At the bottom, you can click the \u201cClick here\u201d link to go to the logs emitted by Lambda into <strong>Amazon CloudWatch<\/strong>.<\/p>\n<p>In CloudWatch, you can click the log stream and see the events. By expanding each event, you get more detail about the request and duration of the execution of the Lambda function. Lambda also outputs any logs created by your code into this stream because the execution environment is stateless by default.<\/p>\n<p>In this example, you\u2019ve seen how easy it is to create, deploy, and monitor an <strong>AWS Lambda function<\/strong>\u2014and that serverless truly is the future of cloud computing. Enjoy coding!<\/p>","protected":false},"excerpt":{"rendered":"<p>AWS Lambda is a serverless processing service in AWS. 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