

Bill Wilder is a hands-on developer, architect, consultant, trainer, speaker, writer, and community leader focused on helping companies and individuals succeed with the cloud using the Windows Azure Platform.
Meer over Ben WilderCloud Architecture Patterns
Develop Cloud-Native Applications
Paperback Engels 2012 1e druk 9781449319779Samenvatting
If your team is investigating ways to design applications for the cloud, this concise book introduces 11 architecture patterns that can help you take advantage of cloud-platform services. You'll learn how each of these platform-agnostic patterns work, when they might be useful in the cloud, and what impact they'll have on your application architecture. You'll also see an example of each pattern applied to an application built with Windows Azure.
The patterns are organized into four major topics, such as scalability and handling failure, and primer chapters provide background on each topic. With the information in this book, you'll be able to make informed decisions for designing effective cloud-native applications.
Learn about architectural patterns for:
- Scalability. Discover the advantages of horizontal scaling. Patterns covered include Horizontally Scaling Compute, Queue-Centric Workflow, and Auto-Scaling.
- Big data. Learn how to handle large amounts of data across a distributed system. Eventual consistency is explained, along with the MapReduce and Database Sharding patterns.
- Handling failure. Understand how multitenant cloud services and commodity hardware influence your applications. Patterns covered include Busy Signal and Node Failure.
- Distributed users. Learn how to overcome delays due to network latency when building applications for a geographically distributed user base. Patterns covered include Colocation, Valet Key, CDN, and Multi-Site Deployment.
Specificaties
Lezersrecensies
Inhoudsopgave
1. Scalability Primer
-Scalability Defined
-Resource Contention Limits Scalability
-Scalability is a Business Concern
-The Cloud-Native Application
-Summary
2. Horizontally Scaling Compute Pattern
-Context
-Impact
-Mechanics
-Example: Building PoP on Windows Azure
-Summary
3. Queue-Centric Workflow Pattern
-Context
-Impact
-Mechanics
-Example: Building PoP on Windows Azure
-Summary
4. Auto-Scaling Pattern
-Context
-Impact
-Mechanics
-Example: Building PoP on Windows Azure
-Summary
5. Eventual Consistency Primer
-CAP Theorem and Eventual Consistency
-Eventual Consistency Examples
-Relational ACID and NoSQL BASE
-Impact of Eventual Consistency on Application Logic
-Summary
6. MapReduce Pattern
-Context
-Impact
-Mechanics
-Example: Building PoP on Windows Azure
-Summary
7. Database Sharding Pattern
-Context
-Impact
-Mechanics
-Example: Building PoP on Windows Azure
-Summary
8. Multitenancy and Commodity Hardware Primer
-Multitenancy
-Commodity Hardware
-Summary
9. Busy Signal Pattern
-Context
-Impact
-Mechanics
-Example: Building PoP on Windows Azure
-Summary
10. Node Failure Pattern
-Context
-Impact
-Mechanics
-Example: Building PoP on Windows Azure
-Summary
11. Network Latency Primer
-Network Latency Challenges
-Reducing Perceived Network Latency
-Reducing Network Latency
-Summary
12. Colocate Pattern
-Context
-Impact
-Mechanics
-Example: Building PoP on Windows Azure
-Summary
13. Valet Key Pattern
-Context
-Impact
-Mechanics
-Example: Building PoP on Windows Azure
-Summary
14. CDN Pattern
-Context
-Impact
-Mechanics
-Example: Building PoP on Windows Azure
-Summary
15. Multisite Deployment Pattern
-Context
-Impact
-Mechanics
-Example: Building PoP on Windows Azure
-Summary
Appendix: Further Reading
Index
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