I have a Python-based Lambda function that seems to have entered an infinite loop due to an unexpected edge case in the data. I’ve noticed my billing metrics spiking, and I need to stop the current execution immediately. Since Lambda is serverless, there isn't a "kill" button in the console like there is for an EC2 instance. How can I stop the active execution and prevent the function from re-triggering itself while I fix the underlying code?
3 answers
Because AWS Lambda is event-driven and abstract, you cannot "kill" an individual running process manually once it has started. However, the industry-standard workaround to stop a runaway function is to set the "Reserved Concurrency" to zero. By navigating to the Configuration tab and setting the concurrency to 0, you effectively throttle the function, preventing any new instances from starting and eventually causing current executions to time out based on your configured timeout settings. This is the fastest way to "kill" the activity without deleting the function entirely. Once the billing spike stops, you can deploy your fix and restore the concurrency to its original value.
Sarah's advice on setting concurrency to zero is the best immediate fix, but have you checked if the function is being triggered by an SQS queue or an S3 event, which might just keep retrying the failed execution once you turn the concurrency back on?
You can also delete the specific version of the function that is running. If you are using aliases, re-routing the traffic to a previous "known good" version will stop the bad code from executing further.
I agree with Emily. Using aliases like 'Prod' or 'Dev' makes this much easier. Rolling back to a previous version is often safer than just stopping everything, as it keeps the rest of your system operational while you debug.
Steven, that's a crucial point for anyone using event-source mappings. If the trigger remains active, the "poison pill" message will stay in the queue and trigger the function again as soon as you lift the throttling. You should also disable the event source or move the message to a Dead Letter Queue (DLQ). This ensures that when you bring the Lambda back online, it doesn't immediately fall back into the same infinite loop. It’s always better to isolate the problematic data before resuming the service.