AWS Lambda Features, Use Cases and Best Practices

AWS Lambda is a service that allows us to implement and create applications without the need to manage servers. This service is also widely used in the process of migrating container applications using an application modernization process, modifying them into an architecture where applications are divided into small independent functions.

Major companies around the world are already using this service. To put it simply, AWS Lambda is a serverless computing service that executes code in response to events and automatically manages the necessary computing resources for you, being used in modern architectures due to its simplicity and usage-based cost model.

In this article, we will explore some of its functionalities, use cases, and best practices.

To begin delving into these subjects and learn more about this service, let’s understand some concepts.

What is Serverless

Serverless is simply an architectural concept where we don’t need to manage infrastructure, such as servers, operating systems, etc. In this model, the infrastructure is completely managed by the service provider (in AWS Lambda’s case, AWS), allowing us to focus more on creating and implementing solutions rather than infrastructure.

AWS Lambda

Now that we understand the Serverless concept and had a brief introduction to AWS Lambda, let’s understand the benefits, usage models, and precautions we should take when using this architectural model.

Benefits of Lambda Functions

• Automatic Scalability: Scaling is done automatically, making it possible to handle thousands of requests simultaneously.
• Cost/Efficiency: We only pay for the function’s execution time and number of requests, with no fixed costs.
• Easy Maintenance: Eliminates the need to manage servers, focusing directly on innovation and business rules.
• Developer Support: AWS Lambda offers developer support through https://aws.amazon.com/serverless/serverlessrepo/ which helps accelerate integration development and building new applications.

Triggers and Integrations

AWS Lambda can be triggered in various ways through a variety of AWS events and services. Below we’ll cover some of the most commonly used services.

These triggers allow you to create highly integrated and reactive applications, leveraging AWS’s vast range of services.

• S3 Events: When an object is created, modified, or deleted in an Amazon S3 bucket, an event can trigger a Lambda function. This is useful for tasks such as image processing, file indexing, or thumbnail generation.
• DynamoDB Streams: DynamoDB Streams allows capturing changes in DynamoDB tables. When an item is added, updated, or deleted, an event is recorded in the stream and can trigger a Lambda function. This is ideal for creating applications that react to real-time data changes.
• API Gateway: Amazon API Gateway can be used to create RESTful APIs that trigger Lambda functions in response to HTTP requests. This allows building scalable and serverless backends for your web and mobile applications.

Other Common Triggers:

• Amazon SNS: Send notifications that trigger Lambda functions.
• Amazon SQS: Process messages from SQS queues.
• CloudWatch Events: Execute Lambda functions in response to CloudWatch events, such as schedules or state changes.
• AWS IoT: Trigger Lambda functions in response to IoT device events.

Supported Languages

• NodeJs
• Typescript
• Python
• Ruby
• Java
• GoLang
• C#
• PowerShell
• Rust

Challenges and Limitations

• Time and Memory Restrictions: Each Lambda function has a 15-minute execution limit and up to 10GB of memory
• Debugging Complexity: Function debugging can be challenging due to the distributed nature and managed environment (However, there are ways to perform troubleshooting)
• Cold Starts and Performance Impact: When functions aren’t frequently used, they may experience cold starts (slightly slower initialization process)
• Concurrency: By default, accounts have a limit of 1,000 concurrent executions, though this can be increased through quota increase requests.

Use Cases

Real-time Data Processing

With AWS Lambda, we can process real-time events, such as transforming files uploaded to S3, or processing Kinesis data streams.

Implementation Example: https://github.com/aws-samples/lambda-refarch-streamprocessing

RESTful API Execution

One of the most common uses of Lambda is creating backends using RESTful APIs in conjunction with Amazon API Gateway to handle HTTP requests.

Implementation Example: https://github.com/aws-samples/lambda-refarch-webapp

Other Cases

I could describe various Lambda usage models here, but I’ll provide the link to reference architectures and other use case models.

Reference Architecture: https://aws.amazon.com/lambda/resources/reference-architectures/

Best Practices

• Runtime and Cost Optimization: Use Provisioned Concurrency to reduce cold starts and include only necessary dependencies to reduce package size
• Log Management and Monitoring with CloudWatch
• Environment Variable Management: Use integrations with AWS Secrets Manager for variable management
• Use a keep-alive directive to maintain persistent connections: Lambda cleans up idle connections over time. Trying to reuse an idle connection when invoking a function will result in a connection error. To keep your connection persistent, use the keep-alive directive associated with your runtime.
• Write Idempotent Code: Writing idempotent code for your functions ensures that duplicate events are handled the same way. Your code should properly validate events and handle duplicate events gracefully.

Conclusion

AWS Lambda is an incredible tool that simplifies application creation by eliminating the need to manage servers. With benefits such as automatic scaling, cost savings, and ease of maintenance, it excels in many scenarios, from real-time data processing to RESTful API execution. However, it’s essential to understand the entire scenario and specific needs before implementing this solution. Carefully evaluating requirements and challenges can ensure that AWS Lambda is the right choice to maximize benefits and meet project expectations.

Reference Links

AWS Lambda — Resources

Getting started with serverless for developers: Part 2 — The business logic

Security Overview of AWS Lambda

AWS Lambda — Documentation

AWS Samples — Github