Data Strategies for Microservice Architectures

[ Presented together with Edson Yanaga at Microservices Day Atlanta, January 23, 2018
https://www.redhat.com/en/events/red-hat-microservices-day-atlanta#event-tab-1 ]

Transcript

1. Data Strategies for Microservice
   Architectures
   Edson Yanaga
   Director of Developer Experience
   @yanaga
   Marius Bogoevici
   Chief Architect, Data Streaming
   @mariusbogoevici
   

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2. Code is easy,
   state is hard
   

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3. POJOs as an
   (Anemic) Domain Model
   

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4. ‘Traditional’ application design
   

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5. Applying Domain Driven Design
   

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6. Persistent Data
   

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7. Strategy: One Database per Microservice
   

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8. Virtualization: where physical separation is hard
   

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9. Volatile data: caching and sharing state
   

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10. Reducing latency via caching
    

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11. Sharing state - replication and partitioning
    

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12. Propagating state change:
    Event Sourcing & CDC
    

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13. Communication: synchronous/asynchronous
    1: ship
    2: update state
    3: update state update state update state
    OrderCreated
    

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14. Event Sourcing
    OrderCreated
    Id: 1
    OrderUpdated
    Id: 1
    OrderCreated
    Id: 2
    

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15. Change Data Capture
    

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16. CQS
    (Command-Query Separation)
    

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17. “Asking a question should not
    change the answer”
    (Bertrand Meyer)
    

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18. CQRS
    (Command Query
    Responsibility Segregation)
    

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19. Join developers.redhat.com
    19
    CQRS (Command Query Responsibility Segregation)
    

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20. Join developers.redhat.com
    2
    0
    CQRS with separate data stores
    

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21. CQRS & Event Sourcing
    

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22. Why CQRS?
    

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23. Performance
    

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24. Distribution
    Availability
    Integration
    Analytics
    

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25. Join developers.redhat.com
    2
    5
    Canonical Source of Information
    (Write Data Store)
    

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26. Join developers.redhat.com
    26
    Canonical Source of Information
    (Write Data Store)
    Read Data Store Read Data Store
    

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27. Join developers.redhat.com
    27
    Canonical Source of Information
    (Write Data Store)
    Read Data Store Read Data Store
    Events Events
    

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28. Different choices of
    technology depending on the
    requirements
    

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29. Latency
    Size
    Staleness
    Ownership
    Security
    Type?
    

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30. Join developers.redhat.com
    30
    http://infinispan.org/
    In-memory Data Grids
    

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31. Join developers.redhat.com
    31
    http://teiid.jboss.org/
    Data Virtualization
    

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32. Join developers.redhat.com
    32
    http://debezium.io/
    Change Data Capture
    

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33. Join
    developers.redhat.com
    Feedback welcome!
    @mariusbogoevici
    @yanaga
    

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34. plus.google.com/+RedHat
    linkedin.com/company/red-hat
    youtube.com/user/RedHatVideos
    facebook.com/redhatinc
    twitter.com/RedHatNews
    Thank you!
    

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