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Processing Messages in AWS with Auto Scaling and SQS Message Queues

Hands-On Lab


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Training Architect





In this hands-on lab, we will cover how an Auto Scaling group of EC2 instances can be used to process messages in an SQS queue based on queue size. This design uses the AWS Job Observer Pattern. In this pattern, the queue is monitored for increases and an Auto Scaling group scales accordingly. Amazon CloudWatch is essentially the observer. By setting an alarm on a metric for messages available in the queue, the CloudWatch alarm can trigger an Auto Scaling group to scale out when the message queue size exceeds the alarm value. We will configure this architecture and be able to test it by sending messages to the SQS queue.

What are Hands-On Labs?

Hands-On Labs are scenario-based learning environments where learners can practice without consequences. Don't compromise a system or waste money on expensive downloads. Practice real-world skills without the real-world risk, no assembly required.