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Version: v2.0

Kafka Eventsource

Kafka is a versatile messaging system designed to securely transfer data between various systems. Its functionality can be tailored through configuration, allowing it to serve as a reliable conduit for real-time event tracking or even function as a replicated distributed database. While it's often colloquially labeled as a queue, it's more precisely described as a hybrid system that combines characteristics and trade-offs from both queue and database systems.

A brief description of how to use Kafka plug-in in our godspeed framework as Data Source as Event Source.

Steps to use kafka plug-in in godspeed framework:

How to Use

  • Create a godspeed project from the CLI , open the created project in vscode and then add the plugin from the CLI of vscode, select the @godspeedsystems/plugins-kafka-as-datasource-as-eventsource to integrate the plugin.
> godspeed plugin add
,_, ╔════════════════════════════════════╗
(o,o) ║ Welcome to Godspeed ║
({___}) ║ World's First Meta Framework ║
" " ╚════════════════════════════════════╝
? Please select godspeed plugin to install: (Press <space> to select, <Up and Down> to move rows)
┌──────┬────────────────────────────────────┬────────────────────────────────────────────────────────────────────┐
│ │ Name │ Description │
├──────┼────────────────────────────────────┼────────────────────────────────────────────────────────────────────┤
│ ◯ │ prisma-as-datastore │ Prisma as a datasource plugin for Godspeed Framework. │
├──────┼────────────────────────────────────┼────────────────────────────────────────────────────────────────────┤
│ ◯ │ aws-as-datasource │ aws as datasource plugin for Godspeed Framework │
├──────┼────────────────────────────────────┼────────────────────────────────────────────────────────────────────┤
│ ◯ │ excel-as-datasource │ excel as datasource plugin for Godspeed Framework │
├──────┼────────────────────────────────────┼────────────────────────────────────────────────────────────────────┤
│ ◯ │ mailer-as-datasource │ mailer as datasource plugin for Godspeed Framework │
├──────┼────────────────────────────────────┼────────────────────────────────────────────────────────────────────┤
│ ❯◯ │ kafka-as-datasource-as-eventsource │ kafka as datasource-as-eventsource plugin for Godspeed Framework │
└──────┴────────────────────────────────────┴────────────────────────────────────────────────────────────────────┘

Example usage Datasource (Producer):

  1. Update configuration file based on your requirements in Datasource/kafka.yaml.

kafka config ( src/datasources/kafka.yaml )

type: kafka
clientId: "kafka_proj"
brokers: ["kafka:9092"]

kafka event for Producer ( src/events/kafka_pub.yaml )

In the event, we establish an HTTP endpoint that accepts parameters such as the topic name and message content. When this endpoint is invoked, it triggers the datasource.kafka.producer function. This function, in turn, takes the provided topic name and message as input arguments and performs the task of publishing the message to the specified Kafka topic.

# event for Publish

'http.post./kafka-pub':
fn: kafka-publish
body:
content:
application/json:
schema:
type: object
properties:
message:
type: string
required: ['message']
responses:
200:
content:
application/json:
schema:
type: object
properties:
name:
type: string

kafka workflow for Producer ( src/functions/kafka-publish.yaml )

In workflow we need to mension datasource.kafka.producer as function (fn) to Produce data.

id: kafka-publish
summary: kafka publish message
tasks:
- id: publish
fn: datasource.kafka.producer
args:
topic: "publish-producer1"
message: <% inputs.body.message%>

Example usage EventSource (Consumer):

  1. Update configuration file based on your requirements in Eventsources/kafka.yaml.

kafka config ( kafka.yaml )

type: kafka
groupId: "kafka_proj"

kafka event for consumer ( src/events/kafka_pub.yaml )

To use Consumer we need to follow the below event key format.

 kafka.{Topic}.{GroupId}

The consumer event is triggered whenever a new message arrives on the specified topic. Upon triggering, it retrieves the incoming message and forwards it to the kafka_consume function. Inside this function, the incoming message is processed, and the result is then returned.

# event for consume data from Topic
kafka.publish-producer1.kafka_proj: // event key
id: kafka__consumer
fn: kafka_consume
body:
description: The body of the query
content:
application/json:
schema:
type: string

kafka workflow for Consumer ( src/functions/kafka_consume.yaml )

# function for consume data
id: kafka-consumer
summary: consumer
tasks:
- id: set_consumer
fn: com.gs.return
args: <% inputs %>

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