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![What is Event Sourcing?
DB
Order {
items=[itemA, itemB]
}](https://image.slidesharecdn.com/eventsourcing-whatcouldgowrong2-190410152653/75/Andrzej-Ludwikowski-Event-Sourcing-what-could-possibly-go-wrong-Codemotion-Rome-2019-8-2048.jpg)
![What is Event Sourcing?
DB
DB
Order {
items=[itemA, itemB]
}
ItemAdded(itemA)
ItemAdded(itemC)
ItemRemoved(itemC)
ItemAdded(itemB)](https://image.slidesharecdn.com/eventsourcing-whatcouldgowrong2-190410152653/75/Andrzej-Ludwikowski-Event-Sourcing-what-could-possibly-go-wrong-Codemotion-Rome-2019-9-2048.jpg)
![ES from domain perspective
● commands, events, state
● 2 methods on state
○ process(command: Command): List[Event]
○ apply(event: Event): State](https://image.slidesharecdn.com/eventsourcing-whatcouldgowrong2-190410152653/75/Andrzej-Ludwikowski-Event-Sourcing-what-could-possibly-go-wrong-Codemotion-Rome-2019-34-2048.jpg)
![import org.axonframework.commandhandling.*
import org.axonframework.eventsourcing.*
@Aggregate(repository = "userAggregateRepository")
public class User {
@AggregateIdentifier
private UserId userId;
private String passwordHash;
@CommandHandler
public boolean handle(AuthenticateUserCommand cmd) {
boolean success = this.passwordHash.equals(hashOf(cmd.getPassword()));
if (success) {
apply(new UserAuthenticatedEvent(userId));
}
return success;
}
@EventSourcingHandler
public void on(UserCreatedEvent event) {
this.userId = event.getUserId();
this.passwordHash = event.getPassword();
}
private String hashOf(char[] password) {
return DigestUtils.sha1(String.valueOf(password));
}
}](https://image.slidesharecdn.com/eventsourcing-whatcouldgowrong2-190410152653/75/Andrzej-Ludwikowski-Event-Sourcing-what-could-possibly-go-wrong-Codemotion-Rome-2019-37-2048.jpg)
![import akka.Done
import com.lightbend.lagom.scaladsl.*
import play.api.libs.json.{Format, Json}
import com.example.auction.utils.JsonFormats._
class UserEntity extends PersistentEntity {
override def initialState = None
override def behavior: Behavior = {
case Some(user) => Actions().onReadOnlyCommand[GetUser.type, Option[User]] {
case (GetUser, ctx, state) => ctx.reply(state)
}.onReadOnlyCommand[CreateUser, Done] {
case (CreateUser(name), ctx, state) => ctx.invalidCommand("User already exists")
}
case None => Actions().onReadOnlyCommand[GetUser.type, Option[User]] {
case (GetUser, ctx, state) => ctx.reply(state)
}.onCommand[CreateUser, Done] {
case (CreateUser(name), ctx, state) => ctx.thenPersist(UserCreated(name))(_ => ctx.reply(Done))
}.onEvent {
case (UserCreated(name), state) => Some(User(name))
}
}
}](https://image.slidesharecdn.com/eventsourcing-whatcouldgowrong2-190410152653/75/Andrzej-Ludwikowski-Event-Sourcing-what-could-possibly-go-wrong-Codemotion-Rome-2019-38-2048.jpg)
![import java.time.Instant
import info.ludwikowski.es.user.domain.UserCommand.*
import info.ludwikowski.es.user.domain.UserEvent.*
import scala.util.{Failure, Success, Try}
final case class User (userId: UserId, name: String, email: Email) {
def applyEvent(userEvent: UserEvent): Try[User] = ??? //pattern matching
def process(userCommand: UserCommand): Try[List[UserEvent]] = ??? //pattern matching
}
object User {
def from(u: UserCreated): User = User(u.userId, u.name, u.email)
}](https://image.slidesharecdn.com/eventsourcing-whatcouldgowrong2-190410152653/75/Andrzej-Ludwikowski-Event-Sourcing-what-could-possibly-go-wrong-Codemotion-Rome-2019-40-2048.jpg)
![Avro schema management
package user.domain
UserCreated(
userId: UserId,
operationId: OperationId,
createdAt: Instant,
name: String,
email: Email
) extends UserEvent
{
"type" : "record",
"name" : "UserCreated",
"namespace" :
"info.ludwikowski.es.user.domain",
"fields" : [ {
"name" : "userId",
"type" : "string" }, {
"name" : "operationId",
"type" : "string" }, {
"name" : "createdAt",
"type" : "long" }, {
"name" : "name",
"type" : "string" }, {
"name" : "email",
"type" : "string"
} ]
}](https://image.slidesharecdn.com/eventsourcing-whatcouldgowrong2-190410152653/75/Andrzej-Ludwikowski-Event-Sourcing-what-could-possibly-go-wrong-Codemotion-Rome-2019-70-2048.jpg)
![Avro schema management
package user.domain
UserCreated(
userId: UserId,
operationId: OperationId,
createdAt: Instant,
name: String,
email: Email
) extends UserEvent
{
"type" : "record",
"name" : "UserCreated",
"namespace" :
"info.ludwikowski.es.user.domain",
"fields" : [ {
"name" : "userId",
"type" : "string" }, {
"name" : "operationId",
"type" : "string" }, {
"name" : "createdAt",
"type" : "long" }, {
"name" : "name",
"type" : "string" }, {
"name" : "email",
"type" : "string"
} ]
}](https://image.slidesharecdn.com/eventsourcing-whatcouldgowrong2-190410152653/75/Andrzej-Ludwikowski-Event-Sourcing-what-could-possibly-go-wrong-Codemotion-Rome-2019-73-2048.jpg)
![Protocol Buffers vs. Avro
{
"type" : "record",
"name" : "UserCreated",
"namespace" :
"info.ludwikowski.es.user.domain",
"fields" : [ {
"name" : "userId",
"type" : "string" }, {
"name" : "operationId",
"type" : "string" }, {
"name" : "createdAt",
"type" : "long" }, {
"name" : "name",
"type" : "string" }, {
"name" : "email",
"type" : "string"
} ]
}
message UserCreatedEvent {
string user_id = 1;
string operation_id = 2;
int64 created_at = 3;
string name = 4;
string email = 5;
}](https://image.slidesharecdn.com/eventsourcing-whatcouldgowrong2-190410152653/75/Andrzej-Ludwikowski-Event-Sourcing-what-could-possibly-go-wrong-Codemotion-Rome-2019-74-2048.jpg)
Uploaded byCodemotion
Andrzej Ludwikowski - Event Sourcing - what could possibly go wrong? - Codemotion Rome 2019
The document discusses the risks and considerations surrounding event sourcing in software architecture, including performance, scalability, and eventual consistency challenges. It explores different levels of event sourcing and CQRS implementations, along with various alternatives and best practices. The presentation also emphasizes the importance of schema evolution and highlights the complexities of scaling event-driven systems.
In this document
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Introduction to the event sourcing concept and potential issues involved, presented by Andrzej Ludwikowski.
About the presenter, Andrzej Ludwikowski, and affiliations with SoftwareMill.
Explanation of event sourcing via examples of database state and logs of state changes.
Historical overview of event sourcing, mentioning ancient practices and its emergence in modern applications.
Advantages of event sourcing including complete logging of state changes, improved debugging, performance, and scalability.
Introduction of Command Query Responsibility Segregation (CQRS) in the context of event sourcing.
Different levels of event sourcing implementation along with their advantages and disadvantages.
Discussion of alternatives to event sourcing, such as change data capture, and additional relevant concepts.
Different methods and frameworks for implementing event sourcing and relevant considerations.
Various methods of event storage suitable for event sourcing like RDBMS, MongoDB, Kafka, and more.Discussion on serialization formats for events focusing on binary, text formats, and their implications. Managing schema evolution's importance in serialized events, particularly with Avro and Protobuf.
Managing state updates, handling duplicates, and employing compensation actions in event-sourced applications.
Challenges in distributed systems such as split-brain scenarios and best practices for clustering.
Summary of key takeaways from the presentation on event sourcing and its related complexities.
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Andrzej Ludwikowski - Event Sourcing - what could possibly go wrong? - Codemotion Rome 2019
- 1. Event Sourcing - whatcould go wrong? Andrzej Ludwikowski
- 2. Event Sourcing -what could go wrong? Andrzej Ludwikowski Rome | March 22 - 23, 2019
- 3. About me ➔ ➔ ludwikowski.info ➔github.com/aludwiko ➔ @aludwikowski
- 4.
- 5.
- 6.
- 7. SoftwareMill ● Hibernate Envers ●Alpakka Kafka ● Sttp ● Scala Clippy ● Quicklens ● MacWire
- 8. What is EventSourcing? DB Order { items=[itemA, itemB] }
- 9. What is EventSourcing? DB DB Order { items=[itemA, itemB] } ItemAdded(itemA) ItemAdded(itemC) ItemRemoved(itemC) ItemAdded(itemB)
- 10. History ● 9000 BC,Mesopotamian Clay Tablets, e.g. for market transactions
- 11. History ● 2005, EventSourcing “Enterprise applications that use Event Sourcing are rarer, but I have seen a few applications (or parts of applications) that use it.”
- 12. Why Event Sourcing? ●complete log of every state change ● debugging ● performance ● scalability
- 13. ES and CQRS CommandService Domain Events Client Query Service Data access Commands Queries Read modelRead modelRead models
- 14. ES and CQRSlevel 1 Command Service Domain Events Client Query Service Data access Commands Queries Read modelRead modelRead models Transaction
- 15. ES and CQRSlevel 1 ● Entry-level, synchronous & transactional event sourcing ● slick-eventsourcing
- 16. ES and CQRSlevel 1 + easy to implement + easy to reason about + 0 eventual consistency - performance - scalability
- 17. ES and CQRSlevel 2 Command Service Domain Events Client Query Service Data access Commands Queries Read modelRead modelRead models Updater Transaction
- 18. ES and CQRSlevel 2 +/- performance +/- scalability - eventual consistency - increased events DB load - lags
- 19. ES and CQRSlevel 3 Command Service Domain Events Client Query Service Data access Commands Queries Read modelRead modelRead models Updater Transaction event bus
- 20. ES and CQRSlevel 3.1 Command Service Domain Events Client Query Service Data access Commands Queries Read modelRead modelRead models Updater event bus Transaction
- 21. ES and CQRSlevel 3.1.1 Command Service Domain Events Client Query Service Data access Commands Queries Read modelRead modelRead models Updater event bus Transaction
- 22. ES and CQRSlevel 3.1.1 Command Service Domain Events Client Query Service Data access Commands Queries Read modelRead modelRead models Updater event bus Transaction At-least-once delivery
- 23. ES and CQRSlevel 3.1.1 Command Service Domain Events Client Query Service Data access Commands Queries Read modelRead modelRead models Updater event bus Transaction
- 24. ES and CQRSlevel 3.1.1 Command Service Domain Events Client Query Service Data access Commands Queries Read modelRead modelRead models Updater event bus Transaction
- 25. ES and CQRSlevel 3.1.1 Command Service Domain Events Client Query Service Data access Commands Queries Read modelRead modelRead models Updater event bus Transaction
- 26. ES and CQRSlevel 3.1.1 Command Service Domain Events Client Query Service Data access Commands Queries Read modelRead modelRead models Updater event bus Transaction
- 27. ES and CQRSlevel 3.1.1 Command Service Domain Events Client Query Service Data access Commands Queries Read modelRead modelRead models Updater event bus Transaction
- 28. ES and CQRSlevel 3.1.1 Command Service Domain Events Client Query Service Data access Commands Queries Read modelRead modelRead models Updater event bus Transaction ?
- 29. ES and CQRSlevel 3.2 Events Client Query Service Data access Commands Queries Read modelRead modelRead models Updater event bus Command Service Domain Command Service Domain Command Service Domain Transaction ` Sharded Cluster
- 30. ES and CQRSlevel 3.x + performance + scalability - eventual consistency - complex implementation
- 31. ES and CQRSalternatives ● Change Capture Data (CDC) logging instead of event bus? ● event bus instead of DB?
- 32. Not covered butworth to check ● Command Sourcing ● Event Collaboration
- 33. ES implementation? ● custom ●library ● framework
- 34. ES from domainperspective ● commands, events, state ● 2 methods on state ○ process(command: Command): List[Event] ○ apply(event: Event): State
- 35. ES from applicationperspective ● snapshotting ● fail-over ● recover ● debugging ● sharding ● serialization & schema evolution ● concurrency access ● etc.
- 36. import javax.persistence.*; import java.util.List; @Entity publicclass Issue { @EmbeddedId private IssueId id; private String name; private IssueStatus status; @OneToMany(cascade = CascadeType.MERGE) private List<IssueComment> comments; ... public void changeStatusTo(IssueStatus newStatus) { if (this.status == IssueStatus.DONE && newStatus == IssueStatus.NEW || this.status == IssueStatus.NEW && newStatus == IssueStatus.DONE) { throw new RuntimeException(String.format("Cannot change issue status from %s to %s", this.status, newStatus)); } this.status = newStatus; } ... }
- 37. import org.axonframework.commandhandling.* import org.axonframework.eventsourcing.* @Aggregate(repository= "userAggregateRepository") public class User { @AggregateIdentifier private UserId userId; private String passwordHash; @CommandHandler public boolean handle(AuthenticateUserCommand cmd) { boolean success = this.passwordHash.equals(hashOf(cmd.getPassword())); if (success) { apply(new UserAuthenticatedEvent(userId)); } return success; } @EventSourcingHandler public void on(UserCreatedEvent event) { this.userId = event.getUserId(); this.passwordHash = event.getPassword(); } private String hashOf(char[] password) { return DigestUtils.sha1(String.valueOf(password)); } }
- 38. import akka.Done import com.lightbend.lagom.scaladsl.* importplay.api.libs.json.{Format, Json} import com.example.auction.utils.JsonFormats._ class UserEntity extends PersistentEntity { override def initialState = None override def behavior: Behavior = { case Some(user) => Actions().onReadOnlyCommand[GetUser.type, Option[User]] { case (GetUser, ctx, state) => ctx.reply(state) }.onReadOnlyCommand[CreateUser, Done] { case (CreateUser(name), ctx, state) => ctx.invalidCommand("User already exists") } case None => Actions().onReadOnlyCommand[GetUser.type, Option[User]] { case (GetUser, ctx, state) => ctx.reply(state) }.onCommand[CreateUser, Done] { case (CreateUser(name), ctx, state) => ctx.thenPersist(UserCreated(name))(_ => ctx.reply(Done)) }.onEvent { case (UserCreated(name), state) => Some(User(name)) } } }
- 39.
- 40. import java.time.Instant import info.ludwikowski.es.user.domain.UserCommand.* importinfo.ludwikowski.es.user.domain.UserEvent.* import scala.util.{Failure, Success, Try} final case class User (userId: UserId, name: String, email: Email) { def applyEvent(userEvent: UserEvent): Try[User] = ??? //pattern matching def process(userCommand: UserCommand): Try[List[UserEvent]] = ??? //pattern matching } object User { def from(u: UserCreated): User = User(u.userId, u.name, u.email) }
- 41. ES packaging ● snapshotting ●fail-over ● recover ● debugging ● sharding ● serialization & schema evolution ● concurrency access ● etc.
- 42. ES packaging ● domainlogic ● domain validation ● 0 ES framework imports
- 43. library vs. framework ●Akka Persistence vs. Lagom
- 44. Event storage ● file ●RDBMS ● Event Store ● MongoDB ● Kafka ● Cassandra
- 45. Event storage forAkka Persistence ● file ● RDBMS ● Event Store ● MongoDB ● Kafka ● Cassandra
- 46. akka-persistence-jdbc trap val theTag= s"%$tag%" sql""" SELECT "#$ordering", "#$deleted", "#$persistenceId", "#$sequenceNumber", "#$message", "#$tags" FROM ( SELECT * FROM #$theTableName WHERE "#$tags" LIKE $theTag AND "#$ordering" > $theOffset AND "#$ordering" <= $maxOffset ORDER BY "#$ordering" ) WHERE rownum <= $max"""
- 47. akka-persistence-jdbc trap SELECT *FROM events_journal WHERE tags LIKE ‘%some_tag%’;
- 48. Cassandra perfect forES? ● partitioning by design ● replication by design ● leaderless (no single point of failure) ● optimised for writes (2 nodes = 100 000 tx/s) ● near-linear horizontal scaling
- 49. ScyllaDB ? ● Cassandrawithout JVM ○ same protocol, SSTable compatibility ● C++ and Seastar lib ● up to 1,000,000 IOPS/node ● not fully supported by Akka Persistence
- 50. Event serialization ● plaintext ○ JSON ○ XML ○ YAML ● binary ○ java serialization ○ Avro ○ Protocol Buffers (Protobuf) ○ Thrift ○ Kryo
- 51. Plain text Binary human-readabledeserialization required
- 52. Plain text Binary human-readabledeserialization required precision issues (JSON IEEE 754, DoS) -
- 53. Plain text Binary human-readabledeserialization required precision issues (JSON IEEE 754, DoS) - storage consumption compress
- 54. Plain text Binary human-readabledeserialization required precision issues (JSON IEEE 754, DoS) - storage consumption compress slow fast
- 55. Plain text Binary human-readabledeserialization required precision issues (JSON IEEE 754, DoS) - storage consumption compress slow fast poor schema evolution support full schema evolution support
- 56. Binary ● java serialization ●Avro ● Protocol Buffers (Protobuf) ● Thrift ● Kryo
- 57. Binary ● java serialization ●Avro ● Protocol Buffers (Protobuf) ● Thrift ● Kryo
- 58. Binary ● java serialization ●Avro ● Protocol Buffers (Protobuf) ● Thrift ● Kryo
- 59. Binary ● java serialization ●Avro ● Protocol Buffers (Protobuf) ● Thrift ● Kryo
- 60. Multi-language support ● Avro ○C, C++, C#, Go, Haskell, Java, Perl, PHP, Python, Ruby, Scala ● Protocol Buffers (Protobuf) ○ even more than Avro
- 61.
- 62.
- 63. Full compatibility Application Events ● backward- V2 can read V1 V1 V2
- 64. ● forward -V2 can read V3 Full compatibility Application Events V1, V2 V2 Application Application V2 V3
- 65. Schema evolution -full compatibility Protocol Buffers Avro Add field + (optional) + (default value) Remove field + + (default value) Rename field + + (aliases) https://martin.kleppmann.com/2012/12/05/schema-evolution-in-avro-protocol-buffers-thrift.html
- 66. Protobuf schema management //user-events.proto messageUserCreatedEvent { string user_id = 1; string operation_id = 2; int64 created_at = 3; string name = 4; string email = 5; } package user.application UserCreatedEvent( userId: String, operationId: String, createdAt: Long, name: String, email: String )
- 67. Protobuf schema management packageuser.domain UserCreated( userId: UserId, operationId: OperationId, createdAt: Instant, name: String, email: Email ) extends UserEvent package user.application UserCreatedEvent( userId: String, operationId: String, createdAt: Long, name: String, email: String )
- 68. Protobuf schema management ●def toDomain(event: UserCreatedEvent): UserEvent.UserCreated ● def toSerializable(event: UserEvent.UserCreated): UserCreatedEvent
- 69. Protobuf schema management +clean domain - a lot of boilerplate code
- 70. Avro schema management packageuser.domain UserCreated( userId: UserId, operationId: OperationId, createdAt: Instant, name: String, email: Email ) extends UserEvent { "type" : "record", "name" : "UserCreated", "namespace" : "info.ludwikowski.es.user.domain", "fields" : [ { "name" : "userId", "type" : "string" }, { "name" : "operationId", "type" : "string" }, { "name" : "createdAt", "type" : "long" }, { "name" : "name", "type" : "string" }, { "name" : "email", "type" : "string" } ] }
- 71. Avro deserialization Bytes DeserializationObject Reader SchemaWriter Schema
- 72. Avro writer schemasource ● add schema to the payload ● custom solution ○ schema in /resources ○ schema in external storage (must be fault-tolerant) ○ Darwin project ● Schema Registry
- 73. Avro schema management packageuser.domain UserCreated( userId: UserId, operationId: OperationId, createdAt: Instant, name: String, email: Email ) extends UserEvent { "type" : "record", "name" : "UserCreated", "namespace" : "info.ludwikowski.es.user.domain", "fields" : [ { "name" : "userId", "type" : "string" }, { "name" : "operationId", "type" : "string" }, { "name" : "createdAt", "type" : "long" }, { "name" : "name", "type" : "string" }, { "name" : "email", "type" : "string" } ] }
- 74. Protocol Buffers vs.Avro { "type" : "record", "name" : "UserCreated", "namespace" : "info.ludwikowski.es.user.domain", "fields" : [ { "name" : "userId", "type" : "string" }, { "name" : "operationId", "type" : "string" }, { "name" : "createdAt", "type" : "long" }, { "name" : "name", "type" : "string" }, { "name" : "email", "type" : "string" } ] } message UserCreatedEvent { string user_id = 1; string operation_id = 2; int64 created_at = 3; string name = 4; string email = 5; }
- 75. Avro schema management +less boilerplate code +/- clean domain - reader & writer schema distribution
- 76. Avro + less boilerplatecode +/- clean domain - reader & writer schema distribution Protobuf + clean domain - a lot of boilerplate code
- 79.
- 81. Immutable vs. mutablestate? ● add/remove ImmutableList 17.496 ops/s ● add/remove TreeMap 2201.731 ops/s
- 83. Fixing state ● healingcommand
- 84. Updating all aggregates User(id)Command(user_id)Event(user_id)Event(user_id)Event(user_id)
- 85.
- 86.
- 87.
- 88.
- 89. Event + seq_noEvent+ seq_no Handling duplicates Events Read modelRead modelRead models Updater event bus Event + seq_no read model update + seq_no
- 90. Broken read model Events admodel ead model Read models Updater event bus
- 91. Broken read model Events admodel ead model Read models Updater event bus read model update + offset (manual offset management)
- 92. Multi aggregate transactionalupdate ● rethink aggregates boundaries ● compensating action ○ optimistic ○ pessimistic
- 93. Pessimistic compensation action Useraccount Cinema hall
- 94. Pessimistic compensation action Useraccount Cinema hall charged
- 95. Pessimistic compensation action Useraccount Cinema hall charged booked
- 96. Pessimistic compensation action Useraccount Cinema hall charged booked sold out
- 97. Pessimistic compensation action Useraccount Cinema hall charged booked booked sold out
- 98. Pessimistic compensation action Useraccount Cinema hall charged booked booked sold out
- 99. Pessimistic compensation action Useraccount Cinema hall charged booked booked sold out refund
- 100. Optimistic compensation action Useraccount Cinema hall charged booked sold out
- 101. Optimistic compensation action Useraccount Cinema hall booked booked sold out overbooked
- 102. Optimistic compensation action Useraccount Cinema hall charged booked booked sold out overbooked ?
- 103. Saga, post-processing Command Service Domain Events Client QueryService Data access Commands Queries Read modelRead modelRead models Updater event bus Transaction
- 104. Saga, post-processing Command Service Domain Events QueryService Data access Commands Queries Read modelRead modelRead models Updater event bus Transaction
- 105. Saga, post-processing Command Service Domain Events Client QueryService Data access Commands Queries Read modelRead modelRead models Updater event bus Transaction
- 106. Saga, post-processing ● shouldbe persistable ● events order should be irrelevant ● time window limitation ● compensating action must be commutative
- 107. Saga, post-processing ● Sagaswith ES ● DDD, Saga & Event-sourcing ● Applying Saga Pattern
- 108. ES with RODO/GDPR ●“right to forget” with: ○ data shredding (and/or deleting) ■ events, state, views, read models ○ retention policy ■ message brokers, backups, logs ○ data before RODO migration
- 109. ES and CQRSlevel 3.2 Events Client Query Service Data access Commands Queries Read modelRead modelRead models Updater event bus Command Service Domain Command Service Domain Command Service Domain Transaction Sharding Clustering
- 110. Cluster = splitbrain 1 5 4 3 Load balancer 2
- 111. Cluster = splitbrain 1 5 4 3 Load balancer 2 User(1) Command(1)
- 112. Cluster = splitbrain 1 5 4 3 Load balancer 2 User(1)
- 113. Cluster = splitbrain 1 5 4 3 Load balancer 2 User(1)
- 114. Cluster = splitbrain 1 5 4 3 Load balancer 2 User(1) Command(1) User(1)
- 115. Cluster = splitbrain 1 5 4 3 Load balancer 2 User(1) Command(1) User(1) Command(1)
- 116. Cluster best practises ●remember about the split brain ● very good monitoring & alerting ● a lot of failover tests ● cluster also on dev/staging ● keep it as small as possible (code base, number of nodes, etc.)
- 117. Summary ● carefully chooseES lib/framework ● understand event/command/state schema evolution ● eventual consistency is your friend ● scaling is complex ● database inside-out ● log-based processing mindset
- 119.
- 120. Thank you andQ&A ➔ ➔ ludwikowski.info ➔ github.com/aludwiko ➔ @aludwikowski
- 121.