Introduction

AWS Lambda is a serverless computing service that allows developers to run code without provisioning or managing servers. It automatically scales applications by running code in response to events and only charges for the compute time used. This makes AWS Lambda an ideal choice for building scalable and cost-effective applications.

However, one challenge that developers might encounter is recursive loop invocations. This occurs when a Lambda function inadvertently triggers itself, leading to a potentially endless loop of invocations. This can result in high costs and system instability if not properly managed.

In this blog post, we will explore the concept of recursive loop invocations in AWS Lambda, why they can be problematic, and how to detect and mitigate them using AWS CloudWatch and AWS Billing.

What are Recursive Loop Invocations?

Recursive loop invocations happen when a Lambda function is configured to invoke itself directly or indirectly through a series of events. For instance, consider a Lambda function set up to process messages from an Amazon SQS queue. If the function inadvertently republishes a message back to the queue after processing, it will trigger itself again, creating a loop.

Real-World Example

Imagine a scenario where a Lambda function processes user uploads and stores metadata in a DynamoDB table. If the function also listens to DynamoDB stream events to trigger additional processing, any changes it makes to the table could potentially retrigger the function, leading to an unintended recursive loop. One example is the image below. Because of the recursive loop, the Lambda Function was invoked multiple times above 300. Not only that, as you can observe, the duration of each invocation also went up over 70 thousands of milliseconds.

Detecting Recursive Loop Invocations with AWS CloudWatch

AWS CloudWatch is a powerful monitoring service that helps you track metrics and set alarms for various AWS resources, including Lambda functions. To detect recursive loop invocations, you can monitor specific metrics and set up alarms to alert you of abnormal activity.

Key Metrics to Monitor

1. Invocations: The number of times your Lambda function is invoked.
2. Duration: The amount of time your function runs per invocation.
3. Error Count: The number of errors that occur during function execution.
4. Throttles: The number of invocation attempts that are throttled due to exceeding concurrency limits.

One requirement for us to set our AWS CloudWatch alarm for recursive loop is to determine how normally our Lambda Function behave. For example, we can check how many Invocations our Lamba Function behave every minute. In the image below, we can see that in average number of invocation of all the Lambda Functions is around 10, and the highest was 19. We can use this information to set the alarm, for example, to trigger if the number of Invocations is above 19 or, let’s say, 50 or 100, which is, we can say, an abnormal activity already.

Setting Up Alarms

1. Go to the AWS Management Console and navigate to the CloudWatch service.

2. In the CloudWatch dashboard, click on All alarms in the left-hand navigation pane.

3. Click on Create alarm.

4. Click Select Metric.

   • Look for Lambda and click on it.

   • Click on Across All Functions.
     

   • Look for Invocations/Duration/Error Count/Throttles, and choose the key metrics you want for your alarm. For this blog, we are going to choose:
   • Click on Select metric.
5. Change the period to 1 minute.
   
6. For the conditions, select Greater/Equal with the value of 100 or whichever you desire.
   
7. In the configurations action, you can set SNS to send you alert via email.
   

8. Click on Next.

9. Review the configuration and click on Create alarm.

Tracking Unexpected Cost Increases with AWS Billing

Recursive loop invocations can lead to unexpected increases in your AWS bill. By closely monitoring your billing and usage, you can quickly detect and address these issues. AWS Billing provides tools to help you track and manage your costs effectively:

• Enable Detailed Billing Reports: This helps you analyze your spending by delivering detailed reports to an S3 bucket.
• Set Up Cost Allocation Tags: Tagging your Lambda functions and other resources allows for more granular tracking of costs.
• Create Budgets and Alerts: In the AWS Billing console, set up budgets for your Lambda function costs and create alerts to notify you when spending approaches or exceeds your budget.

By leveraging these tools, you can gain better insights into your Lambda function costs and quickly identify any unusual spikes that might indicate recursive invocations.

Best Practices

• Implement Safeguards: Add safeguards in your code to prevent recursive invocations. For example, include logic to check if the current invocation is a result of a previous one and skip reprocessing if necessary.
• Use Dead-Letter Queues: Configure a dead-letter queue for your Lambda function to capture and analyze failed events.
• Regular Audits: Conduct regular audits of your Lambda function configurations and event sources to ensure no unintended loops exist.

• Set Reserved Concurrency: Set a reserved concurrency limit on your Lambda functions to control the maximum number of simultaneous executions. This can help mitigate the impact of recursive loops by capping the concurrency, thus preventing excessive invocations.

Conclusion

Monitoring for recursive loop invocations in AWS Lambda is crucial to maintaining system stability and controlling costs. By leveraging AWS CloudWatch and AWS Billing, you can detect and mitigate these issues effectively. Regular monitoring and implementing best practices can save you from unexpected charges and ensure your serverless applications run smoothly.

Remember, proactive monitoring and regular audits are key to preventing and addressing recursive loop invocations, helping you maintain a robust and cost-effective serverless environment.

References:

https://docs.aws.amazon.com/lambda/latest/dg/invocation-recursion.html

https://aws.amazon.com/blogs/compute/detecting-and-stopping-recursive-loops-in-aws-lambda-functions/