Achieving Optimal AWS Lambda Concurrency with Amazon SQS as an Event Source

In January 2023, AWS Lambda introduced a capability to manage the maximum level of concurrent functions triggered by Amazon SQS when utilized as an event source. This functionality empowers you to oversee the concurrency of Lambda functions engaged in processing messages within specific SQS queues. This exactly solves the "SQS overpull", the event source mapping used to read messages that it can not be able to send to Lambda function:

Lambda's concurrency and SQS integration operated independently in the past. When an SQS trigger was enabled, Lambda initiated "long polling" using five parallel connections. Each connection retrieved a batch of messages from the SQS queue and forwarded them to a Lambda function. As long as there were messages in the queue, Lambda escalated polling operations by adding up to 60 additional instances every minute, potentially reaching a maximum of 1,000 instances. However, a challenge arose as this scaling of polling instances was not inherently synchronized with your Lambda function's concurrency. Consequently, if your Lambda function reached its concurrency limit due to the escalating polling instances and became incapable of handling incoming requests, it imposed throttling on the messages. These throttled messages returned to the queue after the visibility timeout, and they could eventually end up in the dead-letter queue. This decoupled behavior between Lambda concurrency and SQS scaling led to operational complications in managing event-driven serverless architectures in the past.

Personally I had to design a complex system with FIFO queues and messageGroupIds just to overcome this problem.

AWS Lambda and SQS

When it comes to building serverless applications, AWS Lambda is a popular choice due to its ability to run code without the need for managing servers. Combining AWS Lambda with Amazon SQS as an event source provides an efficient way to process messages from a queue in a scalable and reliable manner. In this post, we'll delve into the concept of Maximum Concurrency in AWS Lambda and how it relates to using Amazon SQS as an event source.

AWS Lambda can process events from various sources, including API Gateway, S3, Kinesis, and more. One such event source is Amazon SQS, a managed message queue service. Using SQS, you can decouple the components of your serverless application, making it more resilient and scalable. To understand the concept of Maximum Concurrency in AWS Lambda, let's first define what it is and why it matters when using Amazon SQS.

What is Maximum Concurrency?

Maximum Concurrency refers to the maximum number of concurrent executions of a Lambda function. It essentially sets a limit on how many Lambda instances can run simultaneously in response to incoming events. AWS allows you to configure the Maximum Concurrency of your Lambda functions, and this is particularly important when using SQS as an event source.

AWS Lambda and Amazon SQS

When using Amazon SQS as an event source for AWS Lambda, you're essentially configuring Lambda to pull messages from an SQS queue and process them. SQS ensures that each message is delivered at least once. This means that if a Lambda function fails to process a message, SQS will retry it until the function successfully processes it. While this is great for reliability, it can lead to challenges related to concurrency.

Here's how Maximum Concurrency and Amazon SQS interact:

Configuring Maximum Concurrency

Configuring the Maximum Concurrency of a Lambda function when using Amazon SQS as an event source can be done via the AWS Management Console, AWS CLI, or SDKs. You set this value based on your application's needs, considering factors like message processing time, expected queue traffic, and the function's resource configuration.

Here's a basic example of how you can set Maximum Concurrency using the AWS CLI:

aws lambda put-function-concurrency --function-name MyLambdaFunction --reserved-concurrent-executions 100

In this example, the --reserved-concurrent-executions flag sets the Maximum Concurrency to 100 for the Lambda function named MyLambdaFunction.

Monitoring and Optimization

Monitoring the performance of your Lambda function is crucial to optimizing your application. AWS provides various monitoring tools, including Amazon CloudWatch, to help you track metrics like execution duration and error rates.

By adjusting your Maximum Concurrency setting based on performance metrics and your application's specific requirements, you can optimize the throughput of your Lambda function and SQS queue, ensuring efficient message processing.

Conclusion

AWS Lambda and Amazon SQS are a powerful combination for building scalable and reliable serverless applications. Understanding and configuring Maximum Concurrency is key to controlling the processing rate of your Lambda function when using SQS as an event source. By fine-tuning this setting and monitoring your function's performance, you can achieve optimal throughput, ensuring your application runs smoothly and efficiently.

For more details and in-depth information, you can refer to the official AWS blog post on Introducing Maximum Concurrency of AWS Lambda Functions when using Amazon SQS as an Event Source.

I hope this post helps you understand the concept of Maximum Concurrency in AWS Lambda and how it plays a vital role when using Amazon SQS as an event source. If you have any questions or would like to share your experiences, feel free to leave a comment below. Happy serverless coding!