Skip to content

Latest commit

 

History

History
122 lines (88 loc) · 4.2 KB

Setup.md

File metadata and controls

122 lines (88 loc) · 4.2 KB
Raw

Step 1: Host Kafka

Assuming that you have Docker and Go installed on your machine, let’s create a directory for the project named kafka-notify. Then, you will pull Bitnami’s Kafka Docker image for the Kafka setup, providing a hassle-free installation:

mkdir kafka-notify && cd kafka-notify

curl -sSL \
https://raw.githubusercontent.com/bitnami/containers/main/bitnami/kafka/docker-compose.yml > docker-compose.yml

Before starting the Kafka broker, there’s a slight modification required in the docker-compose.yml file. Find the following string:

Step 2: Modify Kafka to host it on local

Before starting the Kafka broker, there’s a slight modification required in the docker-compose.yml file. Find the following string:

KAFKA_CFG_ADVERTISED_LISTENERS=PLAINTEXT://:9092

Replace it with

KAFKA_CFG_ADVERTISED_LISTENERS=PLAINTEXT://localhost:9092

Step 3: Running the kafka broker

The above change ensures Kafka advertises its listener on localhost, which allows our local Go application to connect seamlessly. Now, you can start the Kafka broker via the following Docker command:

docker-compose up -d

Step 4: Setting up folder structure

Next, you’ll need to create a few directories to organize the project files. The cmd/producer and cmd/consumer directories will contain the main application files, and the pkg/models directory will store the model declarations:

mkdir -p cmd/producer cmd/consumer pkg/models

# for windows
#mkdir cmd\producer
#mkdir cmd\consumer
#mkdir pkg\models

Step 4: Setting up connection from gin- API to kafka via SARAMA

The last step is to initialize Go modules and install external packages. You’ll be using sarama to establish a connection with the Kafka broker and gin to handle the API endpoints for the notification system:

go mod init kafka-notify
go get github.com/IBM/sarama github.com/gin-gonic/gin

How to Create the User and Notification Models

Step 6: Get the models for Objects created

With the workspace set up, the first step is to create the User and Notification structs. Move to the pkg/models directory, then create a new file named models.go and declare these structs within it:

package models

type User struct {
    ID   int    `json:"id"`
    Name string `json:"name"`
}

type Notification struct {
    From    User   `json:"from"`
    To      User   `json:"to"`
    Message string `json:"message"`
}

Step 7: Get the producer and consumer code.

How to Run

  1. Start the producer Open up a terminal, move into the kafka-notify directory, and run the producer with the following command:
go run cmd/producer/producer.go
  1. Start the consumer Open up a second terminal window, navigate to the kafka-notify directory, and start the consumer by running:
go run cmd/consumer/consumer.go
  1. Sending notifications With both producer and consumer running, you can simulate sending notifications. Open up a third terminal and use the below curl commands to send notifications:
curl -X POST http://localhost:8080/send \
-d "fromID=2&toID=1&message=Bruno started following you."

User 2 (Bruno) receives a notification from User 1 (Emma):

curl -X POST http://localhost:8080/send \
-d "fromID=1&toID=2&message=Emma mentioned you in a comment: 'Great seeing you yesterday, @Bruno!'"

User 1 (Emma) receives a notification from User 4 (Lena):

curl -X POST http://localhost:8080/send \
-d "fromID=4&toID=1&message=Lena liked your post: 'My weekend getaway!'"
  1. Retrieving notifications Finally, you can fetch the notifications of a specific user. You can use the below curl commands to fetch notifications:

Retrieving notifications for User 1 (Emma):

curl http://localhost:8081/notifications/1 Output:

{"notifications": [{"from": {"id": 2, "name": "Bruno"}, "to": {"id": 1, "name": "Emma"}, "message": "Bruno started following you."}]} {"notifications": [{"from": {"id": 4, "name": "Lena"}, "to": {"id": 1, "name": "Emma"}, "message": "Lena liked your post: 'My weekend getaway!'"}]} In the above output, you see a JSON response listing all the notifications for Emma. As you send more notifications, they accumulate, and you can fetch them using the consumer’s API.