CodeCampIasi25Oct2014

1. Patterns for Scalability in Microsoft Azure Applications (starting at 17.00)
Alex Mang
alexmang.ro | @mangalexandru
25thof October 2014

3. •Alex Mang
•CEO @ KeyTicket Solutions
•Event management and
on-line ticketing, powered by Azure
•Microsoft BizSpark Plus
(1/4 nation-wide)
•Azure Advisor
•Husband & father
Speaker.Bio.ToString()

4. •They promised crazyscaling capacity
•… & they fulfilled their promise
•… but my apps are still under-performing
Context of cloud apps

5. Common Architecture

6. Queue-Based Load Pattern
Queue Based Load Leveling Pattern
Source: Microsoft Patterns & Practices -Cloud Design Patterns
Possible bottlenecks

7. Competing-Consumers Pattern
Source: Microsoft Patterns & Practices -Cloud Design Patterns
What about important messages?

8. Priority Queue Pattern
Competing Consumers Pattern
Source: Microsoft Patterns & Practices -Cloud Design Patterns

9. Recap
Queue-based Load:
-Removes app failure caused by 3rdparty services
Competing-Consumers:
-Ensures messages (= tasks) are processed faster, even under high load
Priority Queue:
-Ensures important tasks run first

10. DEMO
PRIORITY QUEUE PATTERN

11. •Most developers think about how data is stored in OOP manner
•In NoSQL, commonly store everything in a single entity
•In SQL, we have size constraints
•End-up in:
•Performance impact
•High prices
What about data repo. limit.?

12. •Can generate views in advance, containing data on a per-requirement basis
•Only contain data required by query
•Include current values of calculated columns or data items
•May be optimized for a single queries
•Updated a.s.a.p. (schedule / triggered)
What about data repo. limit.? (cont’)

13. Materialized-View Pattern
Source: Microsoft Patterns & Practices -Cloud Design Patterns

14. Materialized-View Pattern
Materialized View Pattern Example
Source: Microsoft Patterns & Practices -Cloud Design Patterns

15. Materialized-View Pattern
When to use
Queries are complex
Data difficult to query directly
Temporary views dramaticallyimprove perf.
Temporary views act as DTOs for UI, reporting etc.
Data store not always available (SQL Azure)
Security or privacy reasons

16. Recap
So far, I’ve talked about:
•Taking pieces of code out of the ‘front facing’ apps
•Messaging methods between apps and consumers
•Simple queue
•Priority queue
•Response queues
•Partitioning data into views
•Materialized views!
Hip-hip, Hurray!
WE CAN SCALE OUR COMPUTE ROLES! 

17. But what about data?
•Thought:
If we scale-out our compute roles…
… why not scale out our databases too?

18. Sharding Pattern
•Scale-up vs. scale-out applies to dbs. too!
•Shard = horizontal partition of overall data
•Must scale out data because:
•Storage limitations
•Concurrent requests
•Customer isolation
•Geography

19. Sharding Pattern (cont’ed)
•Horizontal partitions of data
•(a.k.a. shards)
•Same schema, different data
•Runs on its own server
•Benefits:
•Use commodity hardware
•Better performance
•Closely located geographically

20. Sharding Pattern (cont’ed)
Source: Microsoft Patterns & Practices -Cloud Design Patterns

21. Strategy
Advantages
Considerations
Lookup
•Morecontrol
•Easy shard rebalance
•Shard lookup may create additional overhead
Range
•Easy to implement
•Workswell on range queries
•Easy management
•Suboptimal balance
•Shard rebalance is difficult
Hash
•Best balance
•Requestrouting directly via hashing alg.
•Calculating hash may createadditional overhead
•Rebalance is difficult
Sharding Pattern (cont’ed)

22. DEMO
SHARDING PATTERN

23. •Microsoft Patterns & Practices:
•Cloud Design Patterns http://msdn.microsoft.com/en- us/library/dn568099.aspx
•Developing Multi-tenant Apps. for the Cloud: http://msdn.microsoft.com/en- us/library/ff966499.aspx
•Moving Applications to the Cloud: http://msdn.microsoft.com/en- us/library/ff728592.aspx
References

24. References (cont’ed)
•Get Started with Azure SQL Database Elastic Scale Preview
•http://azure.microsoft.com/en- us/documentation/articles/sql-database-elastic- scale-get-started/
•Elastic Scale Documentation Map
•http://azure.microsoft.com/en- us/documentation/articles/sql-database-elastic- scale-documentation-map/
•Elastic Scale Sample App

25. MVA
•Microsoft Virtual Academy
•On-linecurricula
•Getting started courses
•Deep dives
•“How To”s
•Live Events
•Compete against friends & colleagues

26. MVA (cont’ed)
•Personal learning paths
•Earn points for each course
•Romania TOP 10/ week / month / all-time
•WIN PRIZES (phones, tablets etc.)
www.microsoftvirtualacademy.com
•Did I mention PRIZES? 

27. Q & A

28. Thank you!

30. Patterns for Scalability in Microsoft Azure Applications
Alex Mang
alexmang.ro | @mangalexandru
25thof October 2014
Please fill the online evaluation form after event