AWS Lambda in Action

Gaurav Rajapurkar - A Technology Enthusiast

Published in

AWS Tip

8 min readJan 5, 2023

Hi All ,

First of all, Let me wish you a Very Happy New year 2023 . May you reach all your personal and professional goals.

Today , We will see what is AWS Lambda Service of AWS and how it brings action in Application Development process.

AWS Lambda is a Serverless computing service provided by Amazon Web Services (AWS). It allows you to run code without the need to provision or manage servers. With AWS Lambda, you can run your code in response to events such as changes to data in an Amazon S3 bucket or an Amazon DynamoDB table, or in response to a custom event generated by an application or service.

Here are some key concepts to understand when working with AWS Lambda:

Functions: A function is the code that you write and run on AWS Lambda. You can write functions in a variety of languages, such as JavaScript, Python, and C#.
Events: An event is a trigger that causes your function to be executed. An event can be a change to data in an AWS resource, or it can be a custom event generated by your application or service.
Execution environment: The execution environment is the environment in which your function runs. It includes the operating system, the runtime, and the resources that are available to your function.
Triggers: A trigger is a configuration that specifies which events cause a function to be executed. You can specify triggers when you create or update a function.

To get started with AWS Lambda, you can use the AWS Management Console, the AWS Command Line Interface (CLI), or the AWS Lambda API. You can find more detailed documentation and tutorials in the AWS Lambda documentation.

AWS Lambda Documentation

Here are a few more things to consider when working with AWS Lambda:

Scaling: AWS Lambda automatically scales your functions in response to incoming events. You don’t have to worry about capacity planning or managing servers.

Pricing: With AWS Lambda, you pay only for the compute time that you consume. You are charged based on the number of requests for your functions and the duration of each execution.

Limits: There are limits to the resources that are available to your functions. For example, there is a maximum amount of memory that you can allocate to your function, and there is a maximum execution duration for each function.

Debugging: AWS Lambda provides a number of tools and features to help you debug your functions, including logging, error reporting, and debugging with AWS X-Ray.

API Gateway: You can use Amazon API Gateway to create RESTful APIs that trigger your functions. This can be useful if you want to expose your functions over HTTP, or if you want to build a microservices architecture.

AWS SAM: AWS Serverless Application Model (SAM) is an open-source framework for building serverless applications. It provides a declarative syntax for defining functions, APIs, and other resources in your serverless application. You can use AWS SAM to build, test, and deploy your serverless applications.

Here are a few more things to consider when working with AWS Lambda:

Lambda Layers: A Lambda layer is a package of code or data that you can manage and share across multiple functions. You can use Lambda layers to manage common code that is used across your functions, or to share code and data with other developers.
AWS CloudFormation: AWS CloudFormation is a service that enables you to define and deploy infrastructure as code. You can use CloudFormation to define your functions, triggers, and other resources in a template, and then use that template to deploy your resources. This can be useful if you want to automate the deployment and management of your serverless applications.
AWS CodePipeline and AWS CodeBuild: AWS CodePipeline is a continuous delivery service that enables you to automate the build, test, and deployment of your applications. You can use CodePipeline to build a pipeline that includes your functions and other resources, and then use CodeBuild to build and test your functions.
AWS X-Ray: AWS X-Ray is a distributed tracing system that enables you to trace requests as they travel through your applications. You can use X-Ray to visualize the performance of your functions, identify bottlenecks, and debug issues.
Security: AWS Lambda provides a number of security features to help you protect your functions and the data that they access. For example, you can use Amazon Virtual Private Cloud (VPC) to provide secure network access to your functions, and you can use AWS Identity and Access Management (IAM) to control access to your functions and other resources.
Serverless architectures: AWS Lambda is often used as part of a serverless architecture, which is a design pattern that allows you to build and run applications and services without having to worry about infrastructure. In a serverless architecture, you can build and deploy your functions independently, and the cloud provider handles the underlying infrastructure and scaling.
Third-party integrations: AWS Lambda integrates with many other AWS services and third-party tools and platforms. For example, you can use Lambda to process data streams from Amazon Kinesis, respond to changes in data stored in Amazon S3 or Amazon DynamoDB, or build custom integrations with other platforms using AWS Lambda@Edge.
Best practices: There are a number of best practices to consider when working with AWS Lambda. For example, it’s important to design your functions for scalability, test and debug your functions carefully, and use monitoring and logging to track the performance of your functions.
Community resources: There is a large and active community of developers who are working with AWS Lambda. You can find resources and support from this community by joining online forums and discussion groups, attending meetups and conferences, and accessing online tutorials and documentation.
Local development: You can use the AWS SAM CLI to develop and test your functions locally, before deploying them to the cloud. The SAM CLI provides a local development environment that simulates the AWS runtime, allowing you to test your functions without incurring any charges.
Continuous integration and delivery (CI/CD): You can use tools like AWS CodePipeline and AWS CodeBuild to automate the build, test, and deployment of your functions. This can help you to release updates to your functions quickly and reliably.
Asynchronous processing: You can use AWS Lambda to perform tasks asynchronously, by triggering your functions in response to events or by using a message queue. This can be useful if you have long-running tasks or tasks that don’t need to be completed in real-time.
Custom runtime: AWS Lambda provides a number of supported runtimes that you can use to run your functions. However, if you need to use a runtime that is not supported natively, you can use the custom runtime API to build your own runtime. This can be useful if you want to use a programming language or runtime version that is not supported by AWS Lambda.

AWS Lambda is a Serverless computing service provided by Amazon Web Services (AWS). It enables you to run code without the need to provision or manage servers. You can use AWS Lambda to build and run applications and services that automatically scale in response to changes in traffic and usage.

AWS Serverless is a broader term that refers to the overall serverless computing platform provided by AWS. In addition to AWS Lambda, the AWS Serverless platform includes a number of other services and features that you can use to build and run serverless applications, such as Amazon API Gateway, AWS SAM, and AWS CloudFormation.

Here are some of the key benefits and drawbacks of using AWS Lambda:

Pros:

Cost-effective: You only pay for the compute time that you consume, so you can save money compared to running your own servers.
Scalability: AWS Lambda automatically scales your functions in response to changes in traffic and usage, so you don’t have to worry about capacity planning.
Flexibility: You can use AWS Lambda with a variety of event sources, programming languages, and environments, so you can choose the best tools and technologies for your needs.
Integration: AWS Lambda integrates with many other AWS services and third-party tools and platforms, so you can build a wide range of applications and integrations.

Cons:

Cold starts: There may be a delay when a new instance of your function is started, known as a “cold start.” This can be an issue if you have latency-sensitive workloads.
Concurrency limits: There are limits to the number of concurrent executions of your function, so you may need to design your functions to handle high levels of traffic gracefully.
Debugging: Debugging serverless applications can be more challenging than debugging traditional applications, due to the distributed nature of serverless architectures.
Vendor lock-in: AWS Lambda is a proprietary service, so you may be concerned about vendor lock-in if you decide to use it.

In summary, AWS Lambda is a specific service that allows you to run code in response to events, while AWS Serverless refers to the larger platform that includes AWS Lambda and other services that you can use to build serverless applications.

This is a great opportunity if you are interested in learning how to build Serverless applications with AWS Lambda, API Gateway, and other services! 🙌☁️

In conclusion, AWS Lambda Serverless is a powerful and flexible platform that allows you to build and run a wide range of applications and services without having to worry about infrastructure.

With pay-per-use pricing, automatic scaling, and a range of tools and features to help you build, test, and deploy your applications, AWS Lambda Serverless makes it easy to focus on what you do best: writing code.

Whether you are building a simple web application or a complex data pipeline, AWS Lambda Serverless has the tools and resources you need to bring your ideas to life. So if you are ready to take your development skills to the next level, consider exploring the many possibilities of AWS Lambda Serverless.

Happy Learning … Happy Coding ….. And Happy New Year 2023..

AWS Lambda in Action

Written by Gaurav Rajapurkar - A Technology Enthusiast