Reactive Web Architectures

Dynatrace Brown-Bag Session

Transcript

1. Reactive
   Web Architectures
   Dynatrace Brown-Bag Session
   24.09.2020
   

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2. David Leitner
   Coding Architect
   david.leitner@squer.at
   duffleit
   

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3. reactive
   programming with, or designing
   upon, asynchronous data streams.
   

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4. Space
   Time
   Collections
   Iterator Generator
   Value
   Getter Setter
   Promise
   Deferred Resolver
   Stream
   Reader Emitter
   

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5. The relationship between them is implicit, an idea that only exists in the
   mind of the programmers. It should be explicit, a part of the language,
   and existing for all time. Counter and Double should be bound.
   = the Destiny Operator
   

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6. Stream
   Caller
   Receiver
   Caller Receiver
   propagate change
   observe change
   trigger change
   directly
   The reactive programming paradigm is based on asynchronous
   streams which propagate change. This differs from imperative
   programming, where statements are used to change a program’s state.
   

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8. UserImage .
   Username
   Click Stream
   User Data Stream
   Error Stream
   Error Panel
   observes
   observes
   Http Service
   

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9. IS THE NEW
   

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10. The Reactive Manifesto
    Message
    Driven
    Responsive
    Elastic Resilient
    Value
    Form
    Means
    Maintainability Extendibility
    

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11. Microservice A
    Microservice B
    Message
    Driven
    Responsive
    Elastic Resilient
    Value
    Form
    Means
    

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12. Microservice A
    Microservice B
    Message
    Driven
    Responsive
    Elastic Resilient
    Value
    Form
    Means
    Microservice B
    

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13. Microservice A
    Microservice B
    Message
    Driven
    Responsive
    Elastic Resilient
    Value
    Form
    Means
    Microservice B
    Stream
    

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14. Microservice A
    Microservice B
    Message
    Driven
    Responsive
    Elastic Resilient
    Value
    Form
    Means
    

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15. Message
    Driven
    Responsive
    Elastic Resilient
    Value
    Form
    Means
    Microservice A
    Stream
    Microservice B
    

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16. We support
    Back-Pressure Stream
    Provider Consumer
    events are stored until
    consumed
    Stream
    Provider Consumer A
    Consumer C
    Consumer B
    scaling out consumers
    We can scale-out
    by Location Transparency
    

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17. We move from a
    pull-based design,
    to an asynchronous
    push-based design.
    

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18. GraphQL
    Consumer Driven APIs
    Native Schema Support
    Streaming Support
    

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19. Microservice A
    Microservice B
    Microservice C
    Web Application
    Stream
    Stream
    

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20. Microservice A
    Microservice B
    Microservice C
    Web Application
    Stream
    BFF
    HTTP
    Mobile App
    BFF
    Hydration
    

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21. Lambda A
    Lambda B
    Lambda C
    Client
    Event Stream
    BFF
    Hydration
    Stateful
    3 Factor Architecture
    Factor #1: Realtime GraphQL
    Factor #2: Reliable eventing
    Factor #3: Async serverless
    

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22. This stuff is cool,
    but think twice (!) if reactive
    architectures really fit your
    problem at hand.
    

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25. supports
    15% off with dynatrace15.
    
    

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