A Lap Around of Cloud Design Patterns – Microsoft Patterns & Practices


Patterns & Practices are key indicators of any application development life-cycle whether it’s Windows Store / Desktop app, Web , Cloud , mobility or LOB app. Microsoft P & P leverages few new patterns as well for Cloud based apps. Lets have a summation as followed:

1. Cache-aside Pattern.

2. Circuit Breaker Pattern.

3. Compensating Transaction Pattern.

4. Compensating Consumers Pattern.

5. Compute Resource Consolidation Pattern.

6. Command and Query Responsibility Segregation(CQRS) Pattern.

7. Event Sourcing Pattern.

8. External Configuration Pattern.

9. Federated Identity Pattern.

10. Gatekeeper Pattern.

11. Health Endpoint Monitoring Pattern.

12. Index Table Pattern.

13. Leader Election Pattern.

14. Materialized View Pattern.

15. Pipes and Filters Pattern.

16. Priority Queue Pattern.

17. Queue based Load leveling Pattern.

18. Retry Pattern.

19. Run time Reconfiguration Pattern.

20. Scheduler Agent Supervisor Pattern.

21. Sharding Pattern.

22. Static Content Hosting Pattern.

23. Throttling Pattern.

24. Valet Key Pattern.

25. Asynchronous messaging Pattern.

26. Autoscaling Guidance.

27. Caching Guidance

28.Compute Partitioning Guidance.

29. Data Consistency Primer.

30. Data Partitioning Guidance.

31. Data Replication & Synchronization Guidance.

32. Instrumentation & Telemetry Guidance.

33. Multiple Data Center Deployment Guidance.

34. Service Metering Guidance.

 

Take a look of this link to deep dive into each of pattern’s architecture , key scenario considerations.

To have a complete overview on the projects executed by P&P team, have a look at this site.

 

 

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About Anindita
Anindita Basak is working as Big Data Cloud Consultant in Microsoft. Worked in multiple MNCs as Developer & Senior Developer on Microsoft Azure, Data Platform, IoT & BI , Data Visualization, Data warehousing & ETL & of course in Hadoop platform.She played both as FTE & v- employee in Azure platform teams of Microsoft.Passionate about .NET , Java, Python & Data Science. She is also an active Big Data & Cloud Trainer & would love share her experience in IT Training Industry. She is an author, forum contributor, blogger & technical reviewer of various books on Big Data Hadoop, HDInsight, IoT & Data Science, SQL Server PDW & PowerBI.

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