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![Components
https://github.com/stuartsierra/component
(defprotocol Database
(query [this query-str]))
(defrecord SomeDatabase [config-1 config-2 other-components]
component/Lifecycle
(start [this]
(assoc this :connection (connect! config-1 config-2 other-components)))
(stop [this]
(release! (:connection this))
(dissoc this :connection))
Database
(query [this query-str] (do-query! (:connection this) query-str)))](https://image.slidesharecdn.com/microservicesinclojure-170209181649/75/Microservices-in-Clojure-14-2048.jpg)
Uploaded byLucas Cavalcanti dos Santos
Microservices in Clojure
The document discusses the implementation of microservices using Clojure, emphasizing concepts like immutability, pure functions, and the principles of ports and adapters architecture. It illustrates how Clojure’s immutability features enhance data handling and outlines the structure of microservice components for better organization and testing. It also stresses the importance of simplicity in design and architecture within the context of microservices development.
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Microservices in Clojure
- 1.
- 2. Context Microservices ~80 Clojure services ~60engineers ~10 teams 3.5 years old
- 3. OOP Objects, the mainstreamabstraction Image @ http://www.eduardopires.net.br/2015/01/solid-teoria-e-pratica/
- 4. What about FunctionalProgramming? SÃO PAULO, BRASIL
- 5. TABLE OF CONTENTS Immutability Components PureFunctions Schemas Ports and Adapters SÃO PAULO, BRASIL
- 6. Immutability SOUTHEAST BRAZIL REGIONFROM SPACE
- 7. Immutability Definition “If I’m givena value, it’s guaranteed that it won’t ever change”
- 8.
- 9. Clojure Immutability All default datastructures are immutable: -Maps, Lists, Sets -Records Mutability is explicit: atoms/refs @, dynamic vars *…*
- 10. Datomic Immutability Datomic stores thechanges/transactions, not just the data -append only -db as a value -everything is data (transaction, schema, entities)
- 11. Kafka Immutability Persistent Queues/Topics -each consumerhas its offset -ability to replay messages
- 12. AWS + Docker Immutability Abilityto spin machines with a given image/ configuration -Each build generates a docker image -Each deploy spins a new machine with the new version -As soon as the new version is healthy, old version is killed. (blue-green deployment)
- 13. Components SOUTHEAST BRAZIL REGIONFROM SPACE
- 14. Components https://github.com/stuartsierra/component (defprotocol Database (query [thisquery-str])) (defrecord SomeDatabase [config-1 config-2 other-components] component/Lifecycle (start [this] (assoc this :connection (connect! config-1 config-2 other-components))) (stop [this] (release! (:connection this)) (dissoc this :connection)) Database (query [this query-str] (do-query! (:connection this) query-str)))
- 15. System map Components {:database #SomeDatabase{...} :http-client#HttpClient{...} :kafka #Kafka{...} :auth #AuthCredentials{...} ...} -Created at startup -Entrypoints (e.g http server or kafka consumers) have access to all components the business flows need -dependencies of a given flow are threaded from the entry point until the end, one by one if possible -Thus no static access to system map! (e.g via a global atom) -Any resemblance to objects and classes is just coincidence ;)
- 16. Pure functions SOUTHEAST BRAZILREGION FROM SPACE
- 17. Pure functions Definition "Given thesame inputs, it will always produce the same output"
- 18. Simplicity Pure functions -easier toreason about, fewer moving pieces -easier to test, less need for mocking values -parallelizable by default, no need for locks or STMs
- 19. Datomic Pure functions -Datomic’s dbas a value allows us to consider a function that queries the database as a pure function -db is a snapshot of the database at a certain point in time. -So, querying the same db instance will always produce the same result
- 20. Impure functions Pure functions -functionsthat produce side effects should be marked as such. We use `!` at the end. -split code which handles and transforms data from code that handles side effects -should be moved to the borders of the flow, if possible -Consider returning a future/promise like value, so side effect results can be composed (e.g with manifold or finagle) https://github.com/ztellman/manifold https://github.com/twitter/finagle
- 21. Schema/Spec SOUTHEAST BRAZIL REGIONFROM SPACE
- 22. Schema Legacy Majority of ourcode base was written before clojure.spec existed, so I’ll be talking about the Schema library instead. Most principles apply to clojure.spec as well.
- 23. Schema/Spec Documentation -Clojure doesn’t forceyou to write types -parameter names are not enough -declaring types helps a lot when glancing at the function -values can be verified against a schema
- 24. Function declaration Schema/spec -All purefunctions declare schemas for parameters and return value -All impure functions declare for parameters and don’t declare output type if it’s not relevant. -Validated at runtime in dev/test environments, on every function call -Validation is off on production.
- 25. Wire formats Schema/Spec -Internal schemasare your domain models -Wire schemas are how you expose data to other services/ clients -If they are different, you can evolve internal schemas without breaking clients -Need an adapter layer -wire schemas are always validated on entry/exit points, specially in production -single repository for all wire schemas (for all 60+ services) -caveat: this repository has a really high churn. Beware
- 26. Growing Schemas Spec-ulation Please watchRich Hickey’s talk at Clojure Conj 2016 Spec-ulation: https://www.youtube.com/watch?v=oyLBGkS5ICk
- 27. Ports and Adapters (a.k.aHexagonal Architecture) SOUTHEAST BRAZIL REGION FROM SPACE
- 28. Ports and Adapters Definition Corelogic is independent to how we can call it (yellow) A port is an entry-point of the application (blue) An adapter is the bridge between a port and the core logic (red) http://www.dossier-andreas.net/software_architecture/ports_and_adapters.html http://alistair.cockburn.us/Hexagonal+architecture
- 29. Ports and Adapters(Nubank version) Extended Definition Pure business logic (green) Controller logic wires the flow between the ports (yellow) A port is an entry-point of the application (blue) An adapter is the bridge between a port and the core logic (red)
- 30. Ports (Components) Ports andAdapters -Ports are initialised at startup -Each port has a corresponding component -Serializes data to a transport format (e.g JSON, Transit) -Usually library code shared by all services -Tested via integration tests HTTP Kafka Datomic File Storage Metrics E-mail
- 31. Adapters (Diplomat) Ports andAdapters -Adapters are the interface to ports -Contain HTTP and Kafka consumer handlers -Adapt wire schema to internal schema -Calls and is called by controller functions -Tested with fake versions of the port components, or mocks HTTP Kafka Datomic File Storage Metrics E-mail
- 32. Controllers Ports and Adapters -Controllerswires the flow between entry-point and the side effects -Only deals with internal schemas -Delegates business logic to pure functions -Composes side effect results -Tested mostly with mocks HTTP Kafka Datomic File Storage Metrics E-mail
- 33. Business Logic Ports andAdapters -Handles and transforms immutable data -Pure functions -Best place to enforce invariants and type checks (e.g using clojure.spec) -Can be tested using generative testing -Should be the largest part of the application HTTP Kafka Datomic File Storage Metrics E-mail
- 34. Microservices Ports and Adapters -Eachservice follows about the same design -Services communicate with each other using one of the ports (e.g HTTP or Kafka) -Services DON’T share databases -HTTP responses contain hypermedia, so we can replace a service without having to change clients -Tested with end to end tests, with all services deployed
- 35. Clojure is simple Keepyour design simple Keep your architecture simple SÃO PAULO, BRASIL
- 36.