Grokking Techtalk #39: How to build an event driven architecture with Kafka & Kafka Connect

How to build an event driven architecture
with Kafka & Kafka Connect
Nov 12, 2020
Lợi Nguyễn - Technical Architect @ VeXeRe
1

Vietnam’s largest online bus booking systemvexere.com
Name: Nguyễn Văn Lợi
Company:
● Vexere - #1 Saas based bus ticket platform in Vietnam
● Chotot - #1 Classiﬁed Marketplace in Vietnam
● Blue Orchid - A start-up founded by ex-Grab CTO
● Softfoundry - VoIP product
2

VeXeRe.com is a Vietnamese online bus ticket booking system that operates through
many transportation companies.
3

Vietnam’s largest online bus booking systemvexere.com 4

● Why event driven architecture?
● What is “Event Driven” architecture?
○ Event-carried State Transfer
○ Event Sourcing
● Event Sourcing in real world
○ What is 2 phase write?
○ MSSQL / transaction log
○ Postgresql / WAL
● What is Kafka & Kafka Connect?
○ Connector/Task/Worker
■ MSSQL Source Connector
○ Transform
○ Kafka and Kafka Connect @ vexere
○ Pros/Cons of Kafka Connect vs Custom Producer
● Use Case/Demo
○ Customer Journey Map Notiﬁcation
○ Social Proof
○ Event Sourcing + CQRS
○ Data Warehouse
● Experience / Tools / Troubleshoot
○ Tools: (kafka manager, kafka tool)
○ Troubleshoot connector
○ Monitoring
○ Domain Event vs Event Sourcing Event
● Q & A & Discussion
6

Phase Challenges
Launch ● Business Idea Profitability
● Limit resource:
○ Time
○ Technology
○ Money
Growth/Expansion ● Increasing Customers
● Increasing Feature
● Adding New Products/BU

● Event-carried State Transfer
● Event Sourcing
9

10

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● Two representation of the world:
○ Application State: the current representation of the world, and
○ log of all the events: that changed that world
● The test definition of Event Sourcing:
○ at any time we can blow away the application state and confidently rebuild it from
the log.
● Benefit:
○ Audits
○ Debugging
13

● What is “Event Driven” architecture?
○ Event-carried State Transfer
○ Event Sourcing
14

15

16
Insert without WAL

17
Insertion operations with WAL

18

19

20

○ Transform
○ How we use Kafka and Kafka Connect @ vexere
21

● topic
● producer
● consumer
● broker
● partition
● consumer group
22

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Kafka Connect is a framework to stream data into and out of Apache Kafka
● Connectors – the high level abstraction that coordinates data streaming by managing tasks
● Tasks – the implementation of how data is copied to or from Kafka
● Workers – the running processes that execute connectors and tasks
● Converters – the code used to translate data between Connect and the system sending or receiving data
● Transforms – simple logic to alter each message produced by or sent to a connector
● Dead Letter Queue – how Connect handles connector errors
29

No coding required, just json conﬁg:
30

Pros Cons
● Many Connectors (source/sink)
● No coding required
● Simple transform only
● Hard to customize or write your own
connector
37

■ MSSQL Source Connector
○ Transform
○ How we use Kafka and Kafka Connect @ vexere
38

● Monitor kafka connect job
● AlwaysOn Cluster Conﬁg
● Database schema evolution
39

In Kafka Connect, task is being killed and will not recover until manually
restarted
Solution:
● Cronjob to monitor task status, then restart task by calling restful to
task api
● Dead Letter Queue to handle error in:
○ Convert
○ Transform
41

Reference: https://debezium.io/documentation/reference/connectors/sqlserver.html#sqlserver-schema-evolution

● NVARCHAR(max) is not supported in CDC table (cannot record before value,
only have after update value)

● Experience / Tools / Troubleshoot
○ Tools: (kafka manager, kafka tool)
○ Troubleshoot connector
○ Monitoring
45

Reward
Thay đổi thông tin tài xế, biển số xe
Đánh giá sau chuyến điThanh toán

Calculated from Ticket & Booking event
47

Separate read & write model
Write model: MSSQL
Read model: Elasticsearch
MSSQL ⇒ Kafka ⇒ Kafka consumer ⇒ Elasticsearch
48

Example: Real Time sync data from MSSQL ⇒ Stagging Postgres ⇒ Bigquery
Note:
● be careful when backﬁll data
● If we new column, we have to trigger dummy update to trigger all record event
=> a lot of trash in transaction log ==> need to write your own job
49

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Reference: https://www.enterpriseintegrationpatterns.com/patterns/messaging/index.html

● https://martinfowler.com/articles/201701-event-driven.html
● https://www.confluent.io/blog/announcing-kafka-connect-building-large-scale-low-latenc
y-data-pipelines/
● https://docs.microsoft.com/en-us/sql/relational-databases/track-changes/about-change-
data-capture-sql-server?view=sql-server-2017
● https://docs.confluent.io/current/connect/concepts.html
● https://www.slideshare.net/ConfluentInc/from-zero-to-hero-with-kafka-connect
● https://www.innoq.com/en/blog/domain-events-versus-event-sourcing/#eventsfromeven
tsourcing%E2%89%A0domainevents
52

Grokking Techtalk #39: How to build an event driven architecture with Kafka & Kafka Connect

Grokking Techtalk #39: How to build an event driven architecture with Kafka & Kafka Connect

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