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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

Chapter 5. Patterns for Processing Dynamic Data

In the previous chapter, we covered a few patterns that allow servers to offload static data, or data that does not require request-time parsing, to AWS-backed storage. This allowed us to take advantage of storage that required very little maintenance operationally and, instead, focus on optimization of delivery through cache, content delivery networks, and so on.

These previous patterns are very rarely encountered in real-world exercises, as static data is generally rare itself. Real-world web applications are, by design, dynamic for the data is not set in stone, but changes over time through usage. From here, many issues arise from having multiple servers attempting to share data that cannot be cached easily, or at all.

One of the worst things that could happen from an end user's perspective would be to visit a web application and get conflicting data each time they change pages, or even refresh. If the underlying systems cannot...

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