{"id":17904,"date":"2015-03-12T15:34:42","date_gmt":"2015-03-12T10:04:42","guid":{"rendered":"http:\/\/www.tothenew.com\/blog\/?p=17904"},"modified":"2015-11-13T16:53:52","modified_gmt":"2015-11-13T11:23:52","slug":"introduction-to-aws-lambda","status":"publish","type":"post","link":"https:\/\/www.tothenew.com\/blog\/introduction-to-aws-lambda\/","title":{"rendered":"Introduction To AWS LAMBDA"},"content":{"rendered":"

The next buzz in cloud computing is the event-driven computing service. The service in preview mode \u201cAWS Lambda\u201d<\/strong> brings the same to existence. Lambda makes the best of the concept of “pay-per-use”<\/strong> and \u201cas a service\u201d<\/strong> much further than it did in the case of EC2. It offers pay-per-millisecond computing<\/strong>, a service always available<\/em> without delays, scalable<\/em> power, no systems maintenance<\/em> costs,\u00a0response to events <\/strong>both from the rest of AWS services<\/a> (such as a Kinesis stream or changes in DynamoDB) and events generated by your applications i.e. custom events (through API, the different SDK for programming languages or SDK for mobiles) .<\/p>\n

If we talk specifically, we can use AWS Lambda (currently) to respond to table updates in Amazon DynamoDB<\/em>, modifications to objects in Amazon S3 buckets<\/em>, messages arriving in an Amazon Kinesis stream<\/em>, AWS API call logs created by AWS CloudTrail<\/em>, and custom events<\/strong> from mobile applications, web applications, or other web services<\/em>.<\/p>\n

Examples of using AWS Lambda<\/strong><\/p>\n

\u00a0<\/strong>1) Suppose, if we upload a photo (from a mobile device) to S3 bucket, it will trigger a Lambda-function that we have written. The function will extract meta-data from that photo and put it on DynamoDB\u00a0and then it will trigger a function over all the streams of DynamoDB\u00a0to figure out which of the meta-data function, for example place, location or user are trending. This can be further enhanced, by adding a function that notifies the customer if his\/her photo is one of the trending-photos<\/em>.<\/p>\n

\"s3\"<\/a><\/p>\n

All of this can be done, without running any infrastructure or starting instances. So, it becomes really easy to build highly-reliable<\/strong> and concurrent application<\/strong> using Lambda.<\/p>\n

2) Suppose, we have an use case where we have to create a function to automate the creation of thumbnails<\/strong>. When a user uploads a photo to a bucket, a thumbnail of the same photo is automatically created and stored in the same bucket. Now, when the user opens his account, only the thumbnails are loaded to show a preview rather than the actual photo (using a Lambda function on a web-app<\/em>).<\/p>\n

\"Thumbnail\"<\/a><\/p>\n

To describe Lambda in more generic terms, the beauty of it is that you get to focus on your business logic instead of passing around data. You define a directed acyclic graph of small, composable functions and the rest happens on its own. This is the promise of Event-Driven Computing<\/strong> and Lambda.<\/i><\/p>\n

“Focus on business logic not infrastructure”<\/strong><\/p>\n

\u00a0<\/strong>Upload your code, Amazon Lambda handles:<\/i><\/p>\n

\u2022 Capacity<\/p>\n

\u2022 Scaling<\/p>\n

\u2022 Fault tolerance<\/p>\n

\u2022 Monitoring<\/p>\n

\u2022 Logging<\/p>\n

\u00a0Advantages of using AWS Lambda:<\/strong><\/span><\/p>\n

\u00a0\u2022 AUTOMATIC SCALING<\/i><\/p>\n