En esta charla veremos las bases de una arquitectura CQRS así como su implementación utilizando Windows Azure Service Bus y SignalR. Mediante la creación de una pequeña aplicación veremos los pasos para implementar esta arquitectura, así como sus beneficios a la hora de desarrollar aplicaciones donde es necesaria una gran escalabilidad.

1. CQRS
USING WINDOWS AZURE SERVICE BUS

2. ¿Quiénes somos?
Luis Ruiz Pavón
@luisruizpavon
Roberto González
@robertogg

3. CQRS
 CQRS = “Command Query Responsibility Segregation”
 A design – pattern -architecture – Framework – Principle –
Something
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4. CQS Defined
Bertrand Meyer (via Wikipedia)
“Command Query Separation”
◦ “every method should either be a command that performs an
action, or a query that returns data to the caller, but not both. In
other words, asking a question should not change the answer.”
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5. Benefits of CQRS
 Isolated changes to the application
 User Interface can change with zero impact to storage
 Storage can be changed with zero impact to UI
 Availability is very high, as all reads are unblocked

8. Queries
 90%+ of access to our applications are READS from the datastore
 Very Fast
 Eventual Consistency
 Cache It

9. Commands
 Commands are directives to the domain to perform some action
 Commands may be declined/rejected by the domain for various reasons
 Processing a Command will result in 0:n Events raised
 Commands are always in the imperative:
 PlaceOrder, not OrderPlaced
 Handler per command
 Command can be queued
 Split into separate queues

10. Demystifying Commands
public class PlaceOrderCommand
{
//properties
public readonly Guid OrderId;
public readonly string Comment;
//ctor
public PlaceOrderCommand(Guid id, string comment)
{
OrderId = id;
Comment = comment;
}
}

11. Events
 Events are the result of some action having already happened in the Domain
 Events may never be declined/rejected; they are evidence that something
already happened
 Events are always in the past-tense:
 OrderPlaced, not PlaceOrder

12. Eventual Consistency
 Property of a system such that not all records of state guaranteed
to agree at any given point in time.
 Applicable to whole systems or parts of systems (such as a database)
 As opposed to Strongly Consistent (or Instantly Consistent)
 Eventual Consistency is natural characteristic of a useful, scalable
distributed systems

13. Why Eventual Consistency?
CAP Theorem
Consistency: all nodes see the same data at
the same time
Availability: a guarantee that every request
receives a response about whether it was
successful or failed)
Partition tolerance: the system continues to
operate despite arbitrary message loss
From: http://en.wikipedia.org/wiki/CAP_theorem

14. CQRS in Windows Azure
WE NEED:
 Compute resource to run our code
Web Roles (IIS) and Worker Roles (w/o IIS)
 Reliable Queue to communicate
Windows Azure Service Bus Queues
 Durable/Persistent Storage
SQL Azure
 Fast View
Azure Cache + NoSQL

15. Should I do CQRS?
… “Probably Not” 

16. Links
Udi Dahan: http://www.udidahan.com
Greg Young: http://goodenoughsoftware.net/
CQRS Documents: http://cqrs.files.wordpress.com/2010/11/cqrs_documents.pdf