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Serverless Computing with AWS Lambda

Serverless Computing with AWS Lambda

Introducing Amazon Web Services Lambda

Primarily released in November 2014, AWS Lambda has been designed as a receptive cloud service that is used to inspect the action in an application and also respond to the user-generated codes called the functions. All the compute resources are managed automatically by Lambda on several zones with availability, to scale when new actions are triggered. Codes written in programming languages such as Python, Java, and Node.js are supported by AWS Lambda. Also, Lambda can launch processes in languages that are supported by Amazon Linux which includes Go, Bash and Ruby.

Working Frame of Amazon Web Services Lambda


  • Either write your code in the Lambda’s code editor or upload your written code to the Amazon Web Services Lambda.


  • From other Amazon Web Services or HTTP endpoints/ in-application activity condition your code to trigger.


  • Upon being triggered, Lambda runs your code by utilizing only the required compute resources.


  • Roll out cash only for the time spent in computing.

Configuration of Amazon Web Services Lambda

Step 1

  • Log in to your Amazon Web Services account

Step 2

  • Navigate to the AWS section
  • Select the option Lambda

Step 3

  • You can now select a blueprint
  • This is optional
  • Now, click on the Skip button

Step 4

  • Give all the essential details that are required to create your Lambda function
  • Paste your Node.js code
  • This will be automatically triggered every time a novel item is added in the DynamoDB
  • Provide access to all the required permissions

Step 5

  • Click on the Next button
  • Verify all the provided details

Step 6

  • Click on the Create Function button
  • While selecting the Lambda service and Event Sources tab, no records would be found
  • So, you need to add in any case one source to make your Lambda function work
  • For instance, you can start by adding the DynamoDB Table

Step 7

  • Associate the stream tab with Lambda function during its selection
  • This entry would be displayed in the Event Sources tab of the AWS Lambda Service page

Step 8

  • To the added table, make some entries
  • The Lambda service will trigger the function only when your entry is added and saved
  • The adding and saving status can be viewed on the Lambda logs

Step 9

  • In order to navigate to the Lambda logs, click on the tab that shows the Monitoring tab in the Lambda service tab
  • Click on the View Logs option in the CloudWatch

Key Features of Amazon Web Services Lambda

1. Extension of AWS Services Through Custom Logic

AWS resources like Amazon S3 buckets or DynamoDB tables can be added with custom logic on AWS Lambda. This makes it easy to compute the data as and when it enters or traverses through the cloud.

2. Building Custom Back-End Services

Through AWS Lambda, you can now create back-end services for all your applications which are triggered by Lambda API or those endpoints which are built via Amazon API Gateway. You can also inhibit variations in the client platform, decrease the drain of battery, and facilitate easier updates by processing custom events on Lambda rather than serving them on the clients.

3. Coding Simplified

On AWS Lambda, you don’t have to take the time to study new languages or frameworks or tools. You can make use of a third-party library or even the native ones. Any code can be packaged into a Lambda Layer to manage and share them effortlessly over multiple functions. Primarily Lambda supports Java, PowerShell, C#, Ruby Code, Go, Node.js, Python. It is also provisioned with a Runtime API to help you utilize any programming language to write your functions.

4. Tackle Multiple Functions

Multiple functions can be coordinated on AWS Lambda. Through the AWS Step Functions, tasks that take a long time for execution and are complex can be seamlessly subjected to workflow configuration. You can, therefore, define the workflows of these tasks to trigger the Lambda functions collection via parallel, sequential, branching and error tackling steps. Stateful and long-running processes can also be built with AWS Lambda for backends and applications.

5. Cohesive Security Model

Through the integration of AWS IAM and in-built AWS SDK, AWS Lambda allows your code to access other AWS services securely. It also allows you to run your code in a VPC by default. Should you wish, you can configure AWS Lambda to access the resources that are behind your own VOC. Thus, you can leverage the custom security groups.

Merits of Amazon Web Services Lambda

1. Non-Requirement of Servers

In order to run the written codes, with Amazon Web Services Lambda you do not need a server. So, all the hassle in managing servers is eliminated. You can simply write your codes on the languages supported by Lambda and upload it there to run the program.

2. Ceaseless Scaling

In reaction to the triggers, Amazon Web Services Lambda can scale your application by automatically running your codes. Therefore, while your code runs parallel, triggers are processed individually. In concordance with the workload size, scaling is performed precisely.

3. Time Efficient Metering

One of the key benefits of AWS Lambda is that you are charged for every hundred milliseconds during which your code is executed and the number of times that your code is triggered in the timeframe. Therefore, you need to pay only for the consumed computing time.

4. Constant Performance

You have a feature to optimize the execution time of your code by selecting the required memory size that’s needed by your function. To have your functions initialized you can enable the Provisioned Concurrency feature so that your functions would be constantly ready to react within binary digit milliseconds.

Conclusive Words

We have understood from this article that AWS Lambda is a special service that allows you to compile your codes where servers are not needed. Therefore, through any programming language that is supported on AWS Lambda, your codes can be executed and applications can be triggered without provisioning and managing servers. What’s more interesting is that you pay only for the time you take for computing.

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