Handling Long-Running Tasks in AWS Lambda
If you’ve worked with AWS Lambda, you’re probably familiar with the 15-minute execution limit. It can be quite a constraint when dealing with longer tasks, right? Let me share a reliable pattern I’ve been using that elegantly handles this limitation by combining Lambdas with EventBridge and SQS.
The Building Blocks
- AWS Lambda: Our serverless compute engine
- Amazon EventBridge: For reliable scheduled triggering
- Amazon SQS: Our message queue service
- SQS FIFO queues: For sequential processing (when needed)
The Architecture Breakdown
Initial Trigger
EventBridge serves as our scheduler, triggering the Lambda function at configured intervals. When Lambda receives this trigger, it knows it’s time to plan out the work ahead.
Planning Phase
The Lambda function then:
- Analyses the total workload
- Divides it into manageable chunks (under 15 minutes each)
- Creates task messages
- Pushes them to SQS
Processing Phase
The same Lambda function (via a different SQS trigger):
- Receives messages from SQS
- Processes each chunk
- Automatically advances to the next task
Maintaining Order
When sequential processing is crucial:
- Utilize SQS FIFO queues
- Maintain consistent MessageGroupId for job-related messages
- Ensure strict processing order
Key Benefits
- Scalability: Handles varying workloads efficiently
- Cost-Effective: Pay only for actual processing time
- Reliable: Built-in retry mechanisms
- Manageable: Complex tasks become digestible chunks
- Flexible: Supports both parallel and sequential processing
This pattern provides a robust solution for handling long-running tasks within AWS Lambda’s constraints. Whether you’re processing large datasets or handling complex workflows, this architecture can help you build more efficient and maintainable systems. Give it a try on your next project!