What Is AWS Lambda?
AWS Lambda is a serverless computing service provided by Amazon Web Services (AWS). It allows developers to run code in response to events and automatically takes care of the underlying compute resources required to run that code. With AWS Lambda, developers can write code in various programming languages, such as Python, Java, Node.js, C#, and Go, and then upload it to AWS Lambda. Then, when an event occurs, such as a change to an Amazon S3 bucket, an API Gateway request, or a message arriving in an Amazon Simple Notification Service (SNS) topic, AWS Lambda automatically executes the code in response to the event.
AWS Lambda eliminates the need to provision and manage servers, allowing developers to focus on writing code and delivering value to their customers without worrying about the underlying infrastructure. It can also create complex applications by combining multiple AWS services. Additionally, AWS Lambda can create custom back-end services, perform data processing tasks, and build serverless web applications.
Features of AWS Lambda
Multi-language support: AWS Lambda supports many programming languages, including Node.js, Python, Java, C#, Go, and Ruby. This means you can use the language you are most comfortable with to write your Lambda functions.
Pay-per-use pricing model: AWS Lambda is priced on a pay-per-use model, meaning that you only pay for the compute time your code uses. This makes it a cost-effective solution for running code with low to moderate usage patterns.
Seamless integration with other AWS services: AWS Lambda integrates with various AWS services, such as S3, DynamoDB, API Gateway, and more. This allows you to build complex, serverless architectures that take advantage of other AWS services.
Fine-grained access controls: AWS Lambda provides fine-grained access controls that allow you to control which AWS resources your Lambda function can access. This ensures that your application is secure and compliant with your organization's policies.
Setting Up AWS Lambda Functions
To set up your AWS Lambda function, the main thing you need is an account with AWS. If you do not have one, you can create one here. Likewise, you can sign in to your account here if you already have one.
You can search the AWS console for ‘Lambda,’ as seen in the image below. The AWS Lambda should be one of the first results to come up.
Go ahead to click on the ‘Create function’ button. Doing this takes you to the page below, where you get to select how you want to create the function. You can create your function from scratch, use a blueprint, or select a container image to deploy for your function. In this case, I will be creating a Lambda function from scratch.
At this point, there are some basic information you need to provide. This includes a name for your function, your preferred runtime environment, and the execution role for your function. The runtime environment you choose can be Node.js, C#, Python, or Java, while the execution role determines your function's permissions to AWS resources. You can create a role alongside your Lambda function if you do not already have a role. This role will have basic Lamda permissions.
Once this is created successfully, you should have a page similar to the one below. You can then write your function code or add a trigger.
AWS provides a code editor right on the page. This enables you to write and edit the code for your Lambda function. You also have the choice to upload rite the code: In the "Function code" section, write the code for your Lambda function. You can use the code editor provided by AWS or upload a zip file containing your code.
You can test your newly created function using the "Test" button, as seen above. In addition, you can create or use pre-configured test events to invoke your function.
If you want to configure the trigger, there are tons of options for you to choose from. Some of these options are shown in the image below, and some that are not visible include S3, DynamoDB, MQ, and more. For example, if you want your Lambda function triggered by a file upload to an S3 bucket, you can configure the S3 trigger.
Once you have tested your function and verified that it works correctly, save your function and deploy it. After you have configured the trigger, deploy your function. Then, you can go ahead to deploy your function.
When your function is deployed, it will automatically execute in response to the events that trigger it. You can use the Lambda dashboard to monitor your functions and their performances.
Benefits of using AWS Lambda
Scalability - AWS Lambda automatically scales to meet the demands of your application. It can handle thousands of concurrent requests, ensuring that your application remains responsive and available to your users. AWS Lambda executes code in response to each trigger, allowing the user's application to scale automatically. Since the code also executes in parallel processes and is triggered separately, scaling is done per the workload size.
Affordability - AWS Lambda has a pay-per-use pricing model, meaning you only pay for the computing time your function consumes. This can be more cost-effective than running and maintaining your servers. There is no cost to using AWS Lambda when the code isn't executing. Only 100 milliseconds of code execution and the number of times the code is activated need to be charged to the user.
Quick deployment - With AWS Lambda, you can quickly deploy your code and start running your application in minutes. This makes it easier to iterate and develop your application faster.
Security - AWS Lambda integrates with AWS IAM, thereby ensuring secure code access to AWS services.
Common Use Cases for AWS Lambda
Event-driven computing
Data processing
Backend for mobile and web applications
Integration with other AWS services
Conclusion
AWS Lambda is a powerful serverless compute service that allows you to run your code without provisioning or managing servers. Lambda enables you to easily build and deploy applications that can scale to meet the demands of your users. It has many useful features, including support for multiple programming languages, automatic scaling, and integration with other AWS services. Whether you are building a simple application or a complex system, AWS Lambda can help you get the job done quickly and efficiently.