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  • Book Overview & Buying Implementing Cloud Design Patterns for AWS
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Implementing Cloud Design Patterns for AWS

Implementing Cloud Design Patterns for AWS

By : Marcus Young
2.8 (5)
Buy this Book
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Implementing Cloud Design Patterns for AWS

Implementing Cloud Design Patterns for AWS

2.8 (5)
By: Marcus Young
Buy this Book

Overview of this book

This book is aimed at architects, solution providers, and those of the DevOps community who are looking to implement repeatable patterns for deploying and maintaining services in the Amazon cloud infrastructure. Prior experience using AWS is required as the book focuses more on the patterns and not on the basics of using AWS.
Table of Contents (13 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
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1
1. Introduction
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1. Introduction
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Introduction to AWS
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Cloud computing service models
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Benefits of moving to the Cloud
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Common problems encountered at AWS
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Summary
2
2. Basic Patterns
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2. Basic Patterns
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Introducing Vagrant
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Snapshot pattern
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Stamp pattern
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Scale up pattern
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Scale out pattern
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On-demand disk pattern
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Summary
3
3. Patterns for High Availability
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3. Patterns for High Availability
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Multi-server pattern
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Multi-data center pattern
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Floating IP pattern
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Deep health check pattern
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Summary
4
4. Patterns for Processing Static Data
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4. Patterns for Processing Static Data
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High availability storage
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Direct storage hosting
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Private data delivery
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Content delivery networks
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Rename distribution pattern
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Summary
5
5. Patterns for Processing Dynamic Data
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5. Patterns for Processing Dynamic Data
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Clone server pattern
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NFS sharing pattern
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State sharing pattern
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URL rewriting pattern
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Cache proxy pattern
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Summary
6
6. Patterns for Uploading Data
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6. Patterns for Uploading Data
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Write proxy pattern
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Storage index pattern
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Direct object upload pattern
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Summary
7
7. Patterns for Databases
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7. Patterns for Databases
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Database replication pattern
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Read replica pattern
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In-memory cache pattern
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Sharding write pattern
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Summary
8
8. Patterns for Data Processing
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8. Patterns for Data Processing
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Queuing chain pattern
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Priority queue pattern
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Job observer pattern
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Summary
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9. Patterns for Operation and Maintenance
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9. Patterns for Operation and Maintenance
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Bootstrap pattern
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Cloud dependency injection pattern
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Stack deployment pattern
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Monitoring integration pattern
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Web storage archive pattern
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Weighted transition pattern
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Hybrid backup pattern
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Summary
10
10. Patterns for Networking
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10. Patterns for Networking
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OnDemand NAT pattern
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Management network pattern
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Functional firewall pattern
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Operational firewall pattern
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Web application firewall pattern
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Multiple load balancer pattern
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Summary
11
11. Throw-away Environments
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11. Throw-away Environments
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Infrastructure as code
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Temporary development environments
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Continuous integration
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Summary
12
Index
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Index

Multi-server pattern

Consider a two-tier architecture in which there is a User Interface (UI) instance that connects to a database instance. Now suppose that the system gets a large burst of traffic. Using the scale out pattern discussed in Chapter 2, Basic Patterns, the operations team can manually or automatically add more UI instances to the load balancer to mitigate the flux in traffic. This server redundancy pattern is the multi-server pattern. This pattern includes a healthcheck on the instance so that, if one of the instances that the load is being distributed across is misbehaving, it will not continue to route into it.

Note

One might note that this pattern is similar to the scale out pattern except that it is not dynamic in nature. In this pattern, we are discussing the details of adding horizontal scalability in a much simpler example.

A few things should be noted before we continue, however. It has been found, in my personal usage as well as documented cases, that the servers should...

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