Utilizing Kafka Connect to Integrate Classic Monoliths into Modern Microservices | Zachary Lark, LogRhythm

Sep 29, 20210 likes478 views

Having started with classic monolith applications in the late 90s and adopting a new microservice architecture in 2015, our organization needed a convenient, reliable, and low-cost way to push changes back and forth between them. One that preferably utilized technology already on hand and could exchange information between multiple data stores. In this session we will explore how Kafka Connect and its various connectors satisfied this need. We will review the two disparate tech stacks we needed to integrate, and the strategies and connectors we used to exchange information. Finally, we will cover some enhancements we made to our own processes including integrating Kafka Connect and its connectors into our CI/CD pipeline and writing tools to monitor connectors in our production environment.

Utilizing Kafka Connect to Integrate
Classic Monoliths into Modern
Microservices
@Zach_Lark
linkedin.com/in/zachary-lark

Who am I?
•Started in software
development in 2003
•Professional Services ->
Developer -> Dev Manager
-> Architect
•Using Kafka since 2016
•Started at LogRhythm in
August of 2021

Customer Hosted
History of the Monolith
PowerBuilder
1990s
Logic Logic

Customer Hosted
History of the Monolith
PowerBuilder
1990s
Logic Logic
2000s

Data Center
History of the Monolith
PowerBuilder
1990s
Logic Logic
2000s

Data Center
History of the Monolith
Java
1990s
Logic Logic
2000s

Data Center
Application Server
History of the Monolith
Java
1990s
Logic Logic
2000s

Data Center
Application Server
History of the Monolith
Java
1990s
Logic Logic
2000s
JSPs
Logic

Data Center
Application Server
History of the Monolith
Database Server
Java
1990s
Logic Logic
2000s
JSPs
Logic

Data Center
Application Server
History of the Monolith
Database Server
Java
1990s
Logic Logic
2000s
JSPs
Logic
FTP
Server

1990s 2000s
Microservices
The Age Of
2010s
Service 1 Service 2

1990s 2000s
Microservices
The Age Of
2010s
Service 1 Service 2 Service 3

1990s 2000s
Microservices
The Age Of
2010s

1990s 2000s
Microservices
The Age Of
2010s Present

Kafka Connect
Services
Kafka
Connect
Kafka
Connect

JDBC Connector Config
The type of connector being configured

JDBC Connector Config
Call out specific jdbc dialect to use
Allows for type-specific functionality for the connected database

JDBC Connector Config
Max number of tasks to allocate to the connector
For JDBC Connectors, this is governed by the number of tables being monitored

JDBC Connector Config
Topic to which records are published

JDBC Connector Config
Standard JDBC Connection info

JDBC Connector Config
Query used when poll executes
Structured to accommodate for JDBC connector to append where clause appropriate for mode

JDBC Connector Config
Mode:
* bulk: All the data every time
* incrementing: Use an incrementing column to detect changes
* timestamp: Use a timestamp column to detect changes
* timestamp+incrementing: Use a combination of both to uniquely identify changes with time

JDBC Connector Config
Used to identify an incrementing and/or timestamp column depending on mode used.

JDBC Connector Config
Attempt to map numeric values by precision to integral types
Has been replaced by numeric.mapping

JDBC Connector Config
Interval to execute connector against that data store

JDBC Connector Config
Interval which the connector polls schema for new tables

JDBC Connector Config
Specifies the name for avro schema used which matches that referenced in the code

JDBC Connector Config
Transforms used in conjunction to extract the integer portion of the field and
use its value as the message's partition key

CI/CD Pipeline with Chef
1. Manage connector configurations

CI/CD Pipeline with Chef
1. Manage connector configurations
2. Deploy Connectors to Kafka Connect

CI/CD Pipeline with Chef
End
Start
Changes?
Issue PUT
Issue
DELETE
New?
Delete?
Issue
DELETE

Thank you!
@Zach_Lark
linkedin.com/in/zachary-lark

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