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The Dark Side of Event Sourcing Managing Data Conversion Michiel Overeem, Marten Spoor, Slinger Jansen

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Lead Software Architect @ AFAS Software PhD Candidate @ University Utrecht @michielovereem Software Architect @ AFAS Software @martenspoor

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AFAS Software 400 employees 100 million euro revenue

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x 10.000

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x 10.000 DEV.AFAS.NL

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Adaptable Model-based and User-specific Software Ecosystems

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Copyright Nasa Goddard

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How can an event sourced system be upgraded efficiently when the (implicit) event schema changes? Operations Techniques Strategies

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Event sourcing Event BankAccountCreated (accountId: 1234567, balance: 0, owner: Michiel); accountId balance owner 1234567 0 Michiel Current state Event sourcing

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Event sourcing Event BankAccountCreated (accountId: 1234567, balance: 0, owner: Michiel); DepositPerformed (accountId : 1234567, amount: 100, balance: 100); accountId balance owner 1234567 100 Michiel Current state Event sourcing

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Event sourcing Event BankAccountCreated (accountId: 1234567, balance: 0, owner: Michiel); DepositPerformed (accountId : 1234567, amount: 100, balance: 100); WithdrawalPerformed (accountId: 1234567, amount: 50, balance: 50); accountId balance owner 1234567 50 Michiel Current state Event sourcing

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Event sourcing Event BankAccountCreated (accountId: 1234567, balance: 0, owner: Michiel); DepositPerformed (accountId : 1234567, amount: 100, balance: 100); WithdrawalPerformed (accountId: 1234567, amount: 50, balance: 50); OwnerChanged (accountId: 1234567, newOwner: Marten); accountId balance owner 1234567 50 Marten Current state Event sourcing

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The structure of an Event Store type Attribute = (string, System.Object) type Event = (string, Attribute[]) type EventStream = (string, (DateTime, Event[])[] type EventStore = EventStream[]

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But there is also a schema Which streams are known in the system? Which events are allowed in which streams? Which attributes are allowed in which events?

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Example schema: webshop Webshop EventStore Customer Stream ShoppingCart Stream CustomerSignedUp PriviligeUpgraded … AddedToChart ChangedQuantity …

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Add attribute to event CustomerSignedUp Newsletter: bool We add newsletter functionality, and users can opt-in at signup

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Add event to stream OptInOnNewsLetter Or opt-in at a later moment

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Add stream to store And of course management of newsletters Newsletter Stream Create Publish …

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Split attribute in event CustomerSignedUp FullName: string We chose the wrong attributes for name

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Split attribute in event CustomerSignedUp FullName: string We chose the wrong attributes for name CustomerSignedUp FirstName: string SurName: string

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Split event in stream CustomerSignedUp We created events that were to large

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Split event in stream We created events that were to large OptInOnNewsLetter CustomerSignedUp

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Split streams We found new streams Customer Stream CustomerSignedUp PriviligeUpgraded … Newsletter subscribers Stream OptInOnNewsLetter … …

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Store level operations Add / remove streams Merge streams / split / … streams Stream level operations Add / remove events Merge events / split / … events Event level operations Add / update / remove attributes Merge attributes / split / … attributes How can we change it?

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How to execute these operations? Data upgrade Application upgrade Executed by Basic & Complex Event Basic & Complex Stream Basic & Complex Store Techniques Strategies

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Multiple versions: always extend Webshop EventStore Customer Stream ShoppingCart Stream CustomerSignedUp PriviligeUpgraded … AddedToChart ChangedQuantity …

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Multiple versions: always extend Webshop EventStore Customer Stream ShoppingCart Stream CustomerSignedUp PriviligeUpgraded … AddedToChart ChangedQuantity … CustomerSignedUp_V2

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Is this maintainable? Becomes the codebase to complex?

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Weakening the schema Which attributes can occure in which events? Which events can occure in which streams? Which streams can originate in the system?

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Weak schema’s Webshop EventStore Customer Stream ShoppingCart Stream CustomerSignedUp PriviligeUpgraded … AddedToChart ChangedQuantity …

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Weak schema’s Webshop EventStore Customer Stream ShoppingCart Stream CustomerSignedUp PriviligeUpgraded … AddedToChart ChangedQuantity … CustomerSignedUp

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Explosion of code paths? And still not all operations are possible.

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Webshop EventStore Customer Stream ShoppingCart Stream CustomerSignedUp PriviligeUpgraded … Upcasters: Evolve the events AddedToChart ChangedQuantity …

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Webshop EventStore Customer Stream ShoppingCart Stream CustomerSignedUp PriviligeUpgraded … Upcasters: Evolve the events AddedToChart ChangedQuantity … CustomerSignedUp_V2

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What is the run-time overhead? Are all operations possible?

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Stream boundaries: sharding Webshop EventStore Customer Stream ShoppingCart Stream CustomerSignedUp PriviligeUpgraded … AddedToChart ChangedQuantity …

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Webshop EventStore 2 Stream boundaries: sharding Webshop EventStore 1 Customer Stream ShoppingCart Stream CustomerSignedUp PriviligeUpgraded … AddedToChart ChangedQuantity …

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How to execute these other operations? Techniques Data upgrade Application upgrade Executed by Executed by Basic & Complex Event Basic & Complex Stream Basic Store Complex Store Lazy transformation Upcasting Multiple versions Weak schema Strategies

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Copyright Stephen Cairns Technical versus functional immutability

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Lazy transformation

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But when is this finished? Mixed appends and updates.

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In place transformation Just find the events and fix them.

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Not for the faint of heart!

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Copy and transformation

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Change all the things! Auto backup. Could be very slow.

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Multiple versions Weak schema Upcasters Lazy transformation In place transformation Copy and transformation +/- - +/- +/- + + Operation completeness

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Multiple versions Weak schema Upcasters Lazy transformation In place transformation Copy and transformation - +/- +/- +/- + + Maintainability

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Multiple versions Weak schema Upcasters Lazy transformation In place transformation Copy and transformation + + + +/- +/- - Performance efficiency

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Multiple versions Weak schema Upcasters Lazy transformation In place transformation Copy and transformation + + + - - + Reliability

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Copyright SpaceX Data upgrade Application upgrade Executed by Executed by Basic & Complex Event Basic & Complex Stream Basic Store Complex Store Lazy transformation Upcasting Multiple versions Weak schema In place transfor- mation Copy and transfor- mation But how to deploy them? Strategies

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Big flip

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Big flip

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Big flip

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Big flip

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Big flip

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Big flip

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Blue-Green

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Blue-Green

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Blue-Green

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Blue-Green

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Blue-Green

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Rolling upgrade

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Rolling upgrade

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Rolling upgrade

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Rolling upgrade

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Rolling upgrade

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But for database deployment we need another strategy.

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Blue-Green

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Blue-Green

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Blue-Green

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Blue-Green

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Expand- Contract

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Expand- Contract

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Expand- Contract

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Expand- Contract

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Combining everything into a framework Data upgrade Deployed with Executed by Executed by Data upgrade Application upgrade Lazy transformation Upcasting In place transfor- mation Multiple versions Copy and transfor- mation Basic & Complex Event Basic & Complex Stream Basic Store Complex Store Big Flip Rolling Upgrade Blue-Green Expand- Contract Blue- Green Deployed with Combined with Weak schema

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Beware of the projectors! Order of upgrading components still matters!

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Beware of the projectors! Order of upgrading components still matters!

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Beware of the projectors! Order of upgrading components still matters!

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Beware of the projectors! Order of upgrading components still matters!

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But what about the query side?

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What’s next? 1. Do interviews. Interested? Contact me! https://goo.gl/forms/7tuBKW39EPkWnZLG3 2. Write a follow up paper with more information. 3. Publish the experiences in some form.

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Early interview results

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Do you read your events ever again? No? Then just change the snapshot.

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Move out all events belonging to old aggregates.

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Nobody uses lazy transformation.

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Domain driven design helps in preventing changes.

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There is a lack of experience sharing.

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Your context determines the best upgrade strategy. m.overeem@afas.nl / m.spoor@afas.nl @michielovereem / @martenspoor