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Implementing Cloud Design Patterns for AWS

You're reading from   Implementing Cloud Design Patterns for AWS Solutions and design ideas for solving system design problems

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Product type Paperback
Published in Apr 2019
Publisher Packt
ISBN-13 9781789136203
Length 274 pages
Edition 2nd Edition
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Authors (4):
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Clive Harber Clive Harber
Author Profile Icon Clive Harber
Clive Harber
Sean Keery Sean Keery
Author Profile Icon Sean Keery
Sean Keery
Rick Farmer Rick Farmer
Author Profile Icon Rick Farmer
Rick Farmer
Marcus Young Marcus Young
Author Profile Icon Marcus Young
Marcus Young
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Toc

Table of Contents (18) Chapters Close

Preface 1. Section 1: The Basics
2. Introduction to Amazon Web Services FREE CHAPTER 3. Core Services - Building Blocks for Your Product 4. Availability Patterns - Understanding Your Needs 5. Security - Ensuring the Integrity of Your Systems 6. Section 2: DevOps Patterns
7. Continuous Deployment - Introducing New Features with Minimal Risk 8. Ephemeral Environments - Sandboxes for Experiments 9. Operation and Maintenance - Keeping Things Running at Peak Performance 10. Application Virtualization - Using Cloud Native Patterns for Your Workloads 11. Antipatterns - Avoiding Counterproductive Solutions 12. Section 3: Persistence Patterns
13. Databases - Identifying Which Type Fits Your Needs 14. Data Processing - Handling Your Data Transformation 15. Observability - Understanding How Your Products Are Behaving 16. Anti-Patterns - Bypassing Inferior Options 17. Other Books You May Enjoy

Anti-Patterns - Bypassing Inferior Options

Most data anti-patterns are schema design-and application-focused and so are out of the scope of this book. By identifying bottlenecks in data persistence, retrieval, and storage, we find anti-patterns that can be addressed programmatically. We encourage you to review processes within your organization to break out of consequences related to Conway's law (as a quick reminder: systems mirror the communication structures of the organization that designed them).

It is imperative that you try to remain flexible in your solutions—try to use the right tool for the job. In some cases, it's not all that clear cut which tool is the right one as there may be several options; this is where experimentation comes in.

The design of the system should maximize the portability of your data. One way is by adhering to established standards...

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