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Implementing Cloud Design Patterns for AWS

You're reading from   Implementing Cloud Design Patterns for AWS Create highly efficient design patterns for scalability, redundancy, and high availability in the AWS Cloud

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Product type Paperback
Published in Apr 2015
Last Updated in Feb 2025
Publisher
ISBN-13 9781782177340
Length 228 pages
Edition 1st Edition
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Author (1):
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 Young Young
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Young
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Table of Contents (13) Chapters Close

Preface 1. Introduction FREE CHAPTER 2. Basic Patterns 3. Patterns for High Availability 4. Patterns for Processing Static Data 5. Patterns for Processing Dynamic Data 6. Patterns for Uploading Data 7. Patterns for Databases 8. Patterns for Data Processing 9. Patterns for Operation and Maintenance 10. Patterns for Networking 11. Throw-away Environments Index

Job observer pattern


The previous two patterns show a very basic understanding of passing messages around a complex system, so that components (machines) can work independently from each other. While they are a good starting place, the system as a whole could improve if it were more autonomous. Given the previous example, we could very easily duplicate the worker instance if either one of the SQS queues grew large, but using the Amazon-provided CloudWatch service we can automate this process. Using CloudWatch similar to the Scale out pattern from Chapter 2, Basic Patterns, we might end up with a system that resembles the following diagram:

For this pattern, we will not start from scratch but directly from the previous priority queuing pattern. The major difference between the previous diagram and the diagram displayed in the priority queuing pattern is the addition of a CloudWatch alarm on the myinstance-tosolve-priority queue, and the addition of an auto scaling group for the worker instances...

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